Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.
The podcast Eye On A.I. is created by Craig S. Smith. The podcast and the artwork on this page are embedded on this page using the public podcast feed (RSS).
This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.
To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai
Can AI Ever Reach AGI? Pedro Domingos Explains the Missing Link
In this episode of Eye on AI, renowned computer scientist and author of The Master Algorithm, Pedro Domingos, breaks down what’s still missing in our race toward Artificial General Intelligence (AGI) — and why the path forward requires a radical unification of AI's five foundational paradigms: Symbolists, Connectionists, Bayesians, Evolutionaries, and Analogizers.
Topics covered:
Why deep learning alone won’t achieve AGI
How reasoning by analogy could unlock true machine creativity
The role of evolutionary algorithms in building intelligent systems
Why transformers like GPT-4 are impressive—but incomplete
The danger of hype from tech leaders vs. the real science behind AGI
What the Master Algorithm truly means — and why we haven’t found it yet
Pedro argues that creativity is easy, reliability is hard, and that reasoning by analogy — not just scaling LLMs — may be the key to Einstein-level breakthroughs in AI.
Whether you're an AI researcher, machine learning engineer, or just curious about the future of artificial intelligence, this is one of the most important conversations on how to actually reach AGI.
📚 About Pedro Domingos: Pedro is a professor at the University of Washington and author of the bestselling book The Master Algorithm, which explores how the unification of AI's "five tribes" could produce the ultimate learning algorithm.
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(00:00) The Five Tribes of AI Explained
(02:23) The Origins of The Master Algorithm
(08:22) Designing with Bit Strings: Radios, Robots & More
(10:46) Fitness Functions vs Reward Functions in AI
(15:51) What Is Reasoning by Analogy in AI?
(18:38) Kernel Machines and Support Vector Machines Explained
(22:23) Case-Based Reasoning and Real-World Use Cases
(27:38) Are AI Tribes Still Siloed or Finally Collaborating?
(32:42) Why AI Needs a Deeply Unified Master Algorithm
(36:40) Creativity vs Reliability in AI
(39:14) Can AI Achieve Scientific Breakthroughs?
(41:26) Why Reasoning by Analogy Is AI’s Missing Link
(45:10) Evolutionaries: The Most Distant Tribe in AI
(48:41) Will Quantum Computing Help AI Reach AGI?
(53:15) Are We Close to the Master Algorithm?
(57:44) Tech Leaders, Hype & the Reality of AGI
(01:04:06) The AGI Spectrum: Where We Are & What’s Missing
(01:06:18) Pedro’s Research Focus
This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less.
On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved.
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In this episode of Eye on AI, Craig Smith sits down with Brice Challamel, Head of AI Products and Innovation at Moderna, to explore how one of the world’s leading biotech companies is embedding artificial intelligence across every layer of its business—from drug discovery to regulatory approval.
Brice breaks down how Moderna treats AI not just as a tool, but as a utility—much like electricity or the internet—designed to empower every employee and drive innovation at scale. With over 1,800 GPTs in production and thousands of AI solutions running on internal platforms like Compute and MChat, Moderna is redefining what it means to be an AI-native company.
Key topics covered in this episode:
How Moderna operationalizes AI at scale
GenAI as the new interface for machine learning
AI’s role in speeding up drug approvals and clinical trials
The future of personalized cancer treatment (INT)
Moderna’s platform mindset: AI + mRNA = next-gen medicine
Collaborating with the FDA using AI-powered systems
Don’t forget to like, comment, and subscribe for more interviews at the intersection of AI and innovation.
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(00:00) Preview
(02:49) Brice Challamel’s Background and Role at Moderna
(05:51) Why AI Is Treated as a Utility at Moderna
(09:01) Moderna's AI Infrastructure
(11:53) GenAI vs Traditional ML
(14:59) Combining mRNA and AI as Dual Platforms
(18:15) AI’s Impact on Regulatory & Clinical Acceleration
(23:46) The Five Core Applications of AI at Moderna
(26:33) How Teams Identify AI Use Cases Across the Business
(29:01) Collaborating with the FDA Using AI Tools
(33:55) How Moderna Is Personalizing Cancer Treatments
(36:59) The Role of GenAI in Medical Care
(40:10) Producing Personalized mRNA Medicines
(42:33) Why Moderna Doesn’t Sell AI Tools
(45:30) The Future: AI and Democratized Biotech
This episode is sponsored by Indeed.
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In this episode, renowned AI researcher Pedro Domingos, author of The Master Algorithm, takes us deep into the world of Connectionism—the AI tribe behind neural networks and the deep learning revolution.
From the birth of neural networks in the 1940s to the explosive rise of transformers and ChatGPT, Pedro unpacks the history, breakthroughs, and limitations of connectionist AI. Along the way, he explores how supervised learning continues to quietly power today’s most impressive AI systems—and why reinforcement learning and unsupervised learning are still lagging behind.
We also dive into:
The tribal war between Connectionists and Symbolists
The surprising origins of Backpropagation
How transformers redefined machine translation
Why GANs and generative models exploded (and then faded)
The myth of modern reinforcement learning (DeepSeek, RLHF, etc.)
The danger of AI research narrowing too soon around one dominant approach
Whether you're an AI enthusiast, a machine learning practitioner, or just curious about where intelligence is headed, this episode offers a rare deep dive into the ideological foundations of AI—and what’s coming next.
Don’t forget to subscribe for more episodes on AI, data, and the future of tech.
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(00:00) What Are Generative Models?
(03:02) AI Progress and the Local Optimum Trap
(06:30) The Five Tribes of AI and Why They Matter
(09:07) The Rise of Connectionism
(11:14) Rosenblatt’s Perceptron and the First AI Hype Cycle
(13:35) Backpropagation: The Algorithm That Changed Everything
(19:39) How Backpropagation Actually Works
(21:22) AlexNet and the Deep Learning Boom
(23:22) Why the Vision Community Resisted Neural Nets
(25:39) The Expansion of Deep Learning
(28:48) NetTalk and the Baby Steps of Neural Speech
(31:24) How Transformers (and Attention) Transformed AI
(34:36) Why Attention Solved the Bottleneck in Translation
(35:24) The Untold Story of Transformer Invention
(38:35) LSTMs vs. Attention: Solving the Vanishing Gradient Problem
(42:29) GANs: The Evolutionary Arms Race in AI
(48:53) Reinforcement Learning Explained
(52:46) Why RL Is Mostly Just Supervised Learning in Disguise
(54:35) Where AI Research Should Go Next
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
In this episode of Eye on AI, Craig Smith sits down with Barr Moses, Co-Founder & CEO of Monte Carlo, the pioneer of data and AI observability. Together, they explore the hidden force behind every great AI system: reliable, trustworthy data.
With AI adoption soaring across industries, companies now face a critical question: Can we trust the data feeding our models? Barr unpacks why data quality is more important than ever, how observability helps detect and resolve data issues, and why clean data—not access to GPT or Claude—is the real competitive moat in AI today.
What You’ll Learn in This Episode:
Why access to AI models is no longer a competitive advantage
How Monte Carlo helps teams monitor complex data estates in real-time
The dangers of “data hallucinations” and how to prevent them
Real-world examples of data failures and their impact on AI outputs
The difference between data observability and explainability
Why legacy methods of data review no longer work in an AI-first world
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(00:00) Intro
(01:08) How Monte Carlo Fixed Broken Data
(03:08) What Is Data & AI Observability?
(05:00) Structured vs Unstructured Data Monitoring
(08:48) How Monte Carlo Integrates Across Data Stacks
(13:35) Why Clean Data Is the New Competitive Advantage
(16:57) How Monte Carlo Uses AI Internally
(19:20) 4 Failure Points: Data, Systems, Code, Models
(23:08) Can Observability Detect Bias in Data?
(26:15) Why Data Quality Needs a Modern Definition
(29:22) Explosion of Data Tools & Monte Carlo’s 50+ Integrations
(33:18) Data Observability vs Explainability
(36:18) Human Evaluation vs Automated Monitoring
(39:23) What Monte Carlo Looks Like for Users
(46:03) How Fast Can You Deploy Monte Carlo?
(51:56) Why Manual Data Checks No Longer Work
(53:26) The Future of AI Depends on Trustworthy Data
This episode is sponsored by Thuma.
Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.
To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai
What happens when AI agents start negotiating, automating workflows, and rewriting how the enterprise world operates?
In this episode of the Eye on AI podcast, Will Grannis, CTO of Google Cloud, reveals how Google is leading the charge into the next frontier of artificial intelligence: agentic AI. From multi-agent systems that can file your expenses to futuristic R2-D2-style assistants in real-time race strategy, this episode dives deep into how AI is no longer just about models—it's about autonomous action.
In this episode, we explore:
How AgentSpace is transforming how enterprises build AI agents
The evolution from rule-based workflows to intelligent orchestration
Real-world use cases: expense automation, content creation, code generation
Trust, sovereignty, and securing agentic systems at scale
The future of multi-agent ecosystems and AI-driven scientific discovery
How large enterprises can match startup agility using their data advantage
Whether you're a founder, engineer, or enterprise leader—this episode will shift how you think about deploying AI in the real world.
Subscribe for more deep dives with tech leaders and AI visionaries.
Drop a comment with your thoughts on where agentic AI is headed!
(00:00) Preview and Intro
(02:34) Will Grannis’ Role at Google Cloud
(05:14) Origins of Agentic Workflows at Google
(09:10) How Generative AI Changed the Agent Game
(12:29) Agents, Tool Access & Trust Infrastructure
(14:01) What is Agent Space?
(16:30) Creative & Marketing Agents in Action
(23:29) Core Components of Building Agents
(25:29) Introducing the Agent Garden
(28:06) The “Cloud of Connected Agents” Concept
(33:53) Solving Agent Quality & Self-Evaluation
(37:19) The Future of Autonomous Finance Agents
(40:55) How Enterprises Choose Cloud Partners for Agents
(43:50) Google Cloud’s Principles in Practice
(46:27) Gemini’s Context Power in Cybersecurity
(49:50) Robotics and R2D2-Inspired AI Projects
(52:39) How to Try Agent Space Yourself
This episode is sponsored by Thuma.
Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.
To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai
Visa’s President of Technology, Rajat Taneja, pulls back the curtain on the $3.3 billion AI transformation powering one of the world’s most trusted financial networks.
In this episode, Taneja shares how Visa—a company processing over $16 trillion annually across 300 billion real-time transactions—is leveraging AI not just to stop fraud, but to redefine the future of commerce.
From deep neural networks trained on decades of transaction data to generative AI tools powering next-gen agentic systems, Visa has quietly been an AI-first company since the 1990s. Now, with 500+ petabytes of data and 2,900 open APIs, it’s preparing for a future where agents, biometrics, and behavioral signals shape every interaction.
Taneja also reveals how Visa’s models can mimic bank decisions in milliseconds, stop enumeration attacks, and even detect fraud based on how you type. This is AI at global scale—with zero room for error.
What You’ll Learn in This Episode:
How Visa’s $3.3B data platform powers 24/7 AI-driven decisioning
The fraud models behind stopping $40 billion in criminal transactions
What “agentic commerce” means—and why Visa is betting big on it
How Visa uses behavioral biometrics to detect account takeovers
Why Visa rebuilt its infrastructure for the AI era—10 years ahead of the curve
The role of generative AI, biometric identity, and APIs in the next wave of payments
The future of commerce isn’t just cashless—it’s intelligent, autonomous, and trust-driven.
If you’re curious about how AI is redefining payments, security, and digital identity at massive scale, this episode is essential viewing.
Subscribe for more deep dives into the future of AI, commerce, and innovation.
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(00:00) Introduction
(02:57) Meet Rajat Taneja, Visa’s President of Technology
(04:02) Scaling AI for 300 Billion Transactions Annually
(05:27) The Models Behind Visa’s Fraud Detection
(08:02) Visa’s In-House AI Models vs Open-Source Tools
(10:54) Inside Visa’s $3.3B AI Data Platform
(12:29) Visa’s Role in E-Commerce Innovation
(16:24) Biometrics, Identity & Tokenization at Visa
(21:14) Visa’s Vision for AI-Driven Commerce
This episode is sponsored by the DFINITY Foundation.
DFINITY Foundation's mission is to develop and contribute technology that enables the Internet Computer (ICP) blockchain and its ecosystem, aiming to shift cloud computing into a fully decentralized state.
Find out more at https://internetcomputer.org/
In this episode of Eye on AI, Yoav Shoham, co-founder of AI21 Labs, shares his insights on the evolution of AI, touching on key advancements such as Jamba and Maestro. From the early days of his career to the latest developments in AI systems, Yoav offers a comprehensive look into the future of artificial intelligence.
Yoav opens up about his journey in AI, beginning with his academic roots in game theory and logic, followed by his entrepreneurial ventures that led to the creation of AI21 Labs. He explains the founding of AI21 Labs and the company's mission to combine traditional AI approaches with modern deep learning methods, leading to innovations like Jamba—a highly efficient hybrid AI model that’s disrupting the traditional transformer architecture.
He also introduces Maestro, AI21’s orchestrator that works with multiple large language models (LLMs) and AI tools to create more reliable, predictable, and efficient systems for enterprises. Yoav discusses how Maestro is tackling real-world challenges in enterprise AI, moving beyond flashy demos to practical, scalable solutions.
Throughout the conversation, Yoav emphasizes the limitations of current large language models (LLMs), even those with reasoning capabilities, and explains how AI systems, rather than just pure language models, are becoming the future of AI. He also delves into the philosophical side of AI, discussing whether models truly "understand" and what that means for the future of artificial intelligence.
Whether you’re deeply invested in AI research or curious about its applications in business, this episode is filled with valuable insights into the current and future landscape of artificial intelligence.
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(00:00) Introduction: The Future of AI Systems
(02:33) Yoav’s Journey: From Academia to AI21 Labs
(05:57) The Evolution of AI: Symbolic AI and Deep Learning
(07:38) Jurassic One: AI21 Labs’ First Language Model
(10:39) Jamba: Revolutionizing AI Model Architecture
(16:11) Benchmarking AI Models: Challenges and Criticisms
(22:18) Reinforcement Learning in AI Models
(24:33) The Future of AI: Is Jamba the End of Larger Models?
(27:31) Applications of Jamba: Real-World Use Cases in Enterprise
(29:56) The Transition to Mass AI Deployment in Enterprises
(33:47) Maestro: The Orchestrator of AI Tools and Language Models
(36:03) GPT-4.5 and Reasoning Models: Are They the Future of AI?
(38:09) Yoav’s Pet Project: The Philosophical Side of AI Understanding
(41:27) The Philosophy of AI Understanding
(45:32) Explanations and Competence in AI
(48:59) Where to Access Jamba and Maestro
This episode is sponsored by Indeed.
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Greg Osuri’s Vision for Decentralized Cloud Computing | The Future of AI & Web3 Infrastructure
The cloud is broken—can decentralization fix it? In this episode, Greg Osuri, founder of Akash Network, shares his groundbreaking approach to decentralized cloud computing and how it's disrupting hyperscalers like AWS, Google Cloud, and Microsoft Azure.
Discover how Akash Network’s peer-to-peer marketplace is slashing cloud costs, unlocking unused compute power, and paving the way for AI-driven infrastructure without Big Tech’s control.
What You'll Learn in This Episode: - Why AI training is hitting an energy bottleneck and how decentralization solves it - How Akash Network creates a global marketplace for underutilized compute power - The role of blockchain in securing cloud resources and enforcing smart contracts - The privacy risks of hyperscalers—and why sovereign AI in the home is the future - How Akash Network is evolving from a resource marketplace to a full-fledged services economy - The future of AI, energy-efficient cloud solutions, and decentralized infrastructure
The battle for the future of cloud computing is on—and decentralization is winning. If you're interested in AI, blockchain, Web3, or the economics of cloud infrastructure, this episode is a must-watch!
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(00:00) Introduction & The Biggest Challenges in AI Training (02:36) Greg Osuri’s Background (04:50) The Problem with AWS, Google Cloud & Traditional Cloud Providers (06:40) How To Use Blockchain for a Decentralized Cloud (10:17) Akash Network’s Marketplace Matches Compute Buyers & Sellers (14:42) Security & Privacy: Protecting Users from Data Risks (18:25) The Energy Crisis: Why Hyperscalers Are Unsustainable (21:51) The Future of AI: Decentralized Cloud & Home AI Computing (26:42) How AI Workloads Are Routed & Optimized (30:24) Big Companies Using Akash Network: NVIDIA, Prime Intellect & More (45:49) Building a Decentralized AI Services Marketplace (55:09) Why the Future of AI Needs a Decentralized Cloud
This episode is brought to you by Extreme Networks, the company radically improving customer experiences with AI-powered automation for networking. Extreme is driving the convergence of AI, networking, and security to transform the way businesses connect and protect their networks, delivering faster performance, stronger security, and a seamless user experience. Visit extremenetworks.com to learn more. ———————————————————————————————————————— The Role of AI in Education | Dylan Arena on Learning, AI Tutoring & The Future of Teaching How can AI enhance education without replacing the human touch? In this episode, Dylan Arena, Chief Data Science and AI Officer at McGraw Hill, shares his insights on the intersection of AI and learning. Dylan’s background in learning sciences and technology design has shaped his approach to AI-powered tools that help students and teachers—not replace them. He discusses how AI can augment human relationships in education, improve personalized learning, and assist teachers with real-time insights while avoiding the pitfalls of over-reliance on automation. With AI playing an increasingly central role in education, are we at risk of losing the essential human connections that define great learning experiences? What You’ll Learn in This Episode: - Why AI should be used to enhance not replace teachers - The risks and rewards of AI-powered tutoring - How AI-driven assessments can improve personalized learning - Why AI chatbots in education need careful ethical considerations - The future of gamification and AI-driven engagement in classrooms - How McGraw Hill is integrating AI into its learning platforms If you care about the future of education, AI, and ethical tech development, this episode is a must-watch. ———————————————————————————————————————— This episode is sponsored by Oracle. Oracle Cloud Infrastructure (OCI) is a blazing-fast and secure platform for your infrastructure, database, application development, plus all your AI and machine learning workloads. OCI costs 50% less for compute and 80% less for networking—so you’re saving a pile of money. Thousands of businesses have already upgraded to OCI, including MGM Resorts, Specialized Bikes, and Fireworks AI. Cut your current cloud bill in HALF if you move to OCI now: https://oracle.com/eyeonai ———————————————————————————————————————— Chapters: (00:00) The Role of AI in Augmenting Human Learning (02:10) Dylan’s Background in Learning Sciences & AI (08:23) The Risks of AI-Powered Education Tools (11:08) AI Tutoring: Can It Replace Human Teachers? (16:28) AI’s Role in Personalized Learning & Adaptive Assessments (22:47) How AI Can Assist, Not Replace, Teachers (29:36) The Future of AI-Driven Gamification in Education (36:41) Ethical Concerns Around AI Chatbots & Student Relationships (45:02) The Impact of AI on Student Learning & Memory Retention (50:19) How McGraw Hill is Innovating with AI in Education (54:44) Final Thoughts: AI’s Role in Shaping the Future of Learning
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
Can AI learn like humans? In this episode, Patrick Pilarski, Canada CIFAR AI Chair and professor at the University of Alberta, breaks down The Alberta Plan—a bold roadmap for achieving Artificial General Intelligence (AGI) through reinforcement learning and real-time experience-based AI.
Unlike large pre-trained models that rely on massive datasets, The Alberta Plan champions continual learning, where AI evolves from raw sensory experience, much like a child learning through trial and error. Could this be the key to unlocking true intelligence?
Pilarski also shares insights from his groundbreaking work in bionic medicine, where AI-powered prosthetics are transforming human-machine interaction. From neuroprostheses to reinforcement learning-driven robotics, this conversation explores how AI can enhance—not just replace—human intelligence.
What You’ll Learn in This Episode:Why reinforcement learning is a better path to AGI than pre-trained models
The four core principles of The Alberta Plan and why they matter
How AI-driven bionic prosthetics are revolutionizing human-machine integration
The battle between reinforcement learning and traditional control systems in robotics
Why continual learning is critical for AI to avoid catastrophic forgetting
How reinforcement learning is already powering real-world breakthroughs in plasma control, industrial automation, and beyond
The future of AI isn’t just about more data—it’s about AI that thinks, adapts, and learns from experience.
If you're curious about the next frontier of AI, the rise of reinforcement learning, and the quest for true intelligence, this episode is a must-watch.
Subscribe for more AI deep dives!
(00:00) The Alberta Plan: A Roadmap to AGI
(02:22) Introducing Patrick Pilarski
(05:49) Breaking Down The Alberta Plan’s Core Principles
(07:46) The Role of Experience-Based Learning in AI
(08:40) Reinforcement Learning vs. Pre-Trained Models
(12:45) The Relationship Between AI, the Environment, and Learning
(16:23) The Power of Reward in AI Decision-Making
(18:26) Continual Learning & Avoiding Catastrophic Forgetting
(21:57) AI in the Real World: Applications in Fusion, Data Centers & Robotics
(27:56) AI Learning Like Humans: The Role of Predictive Models
(31:24) Can AI Learn Without Massive Pre-Trained Models?
(35:19) Control Theory vs. Reinforcement Learning in Robotics
(40:16) The Future of Continual Learning in AI
(44:33) Reinforcement Learning in Prosthetics: AI & Human Interaction
(50:47) The End Goal of The Alberta Plan
This episode is brought to you by Sonar, the creators of SonarQube Server, Cloud, IDE, and the open source Community Build.
Sonar unlocks actionable code intelligence, helping to redefine the software development lifecycle by use of AI and AI agentic systems, to continuously improve quality and security
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Visit http://sonarsource.com/eyeonai to try SonarQube for free today.
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The Future of AI is Open-Source | Manos Koukoumidis on UMI & The AI Revolution
Is closed AI holding back innovation? In this episode, Manos Koukoumidis, CEO of Oumi, makes the case for why the future of AI must be open-source. OUMI (Open Universal Machine Intelligence) is redefining how AI is built—offering fully open models, open data, and open collaboration to make AI development more transparent, accessible, and community-driven.
Big Tech has dominated AI, but UMI is challenging the status quo by creating a platform where anyone can train, fine-tune, and deploy AI models with just a few commands. Could this be the Linux moment for AI?
What You’ll Learn in This Episode:Why open-source AI is the only sustainable path forward
The difference between “open-source” AI and true open AI
How OUMI enables researchers and enterprises to build better AI models
Why Big Tech’s closed AI systems are losing their competitive edge
The impact of open AI on healthcare, science, and enterprise innovation
The future of AI models—will proprietary AI survive?
The AI revolution is happening—and it’s open-source. If you care about the future of AI, innovation, and ethical tech development, this episode is a must-watch.
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This episode is sponsored by Thuma.
Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.
To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai
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(00:00) The True Meaning of Open-Source AI
(02:15) The Open vs. Closed AI Debate
(07:54) Why Open AI Models Are Safer
(10:34) Defining Open Data
(13:21)Beating GPT-4-O with an Open AI Model
(16:36) Open AI in Healthcare
(19:31) Why Open Models Will Dominate
(23:07) How OUMI Makes AI Training Fully Accessible & Reproducible
(28:44) UMI’s Collaboration with Universities
(32:29) The Shift Toward Open A
(36:41) Can We Build Truly Open AI Models from Scratch?
(40:20) The Role of Open AI in Eliminating Bias
(45:02) Will Open AI Replace Proprietary AI Models?
(50:19) How OUMI Works
(54:44) The Open AI Revolution Has Begun
This episode is sponsored by Thuma.
Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.
To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai
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AI deployment is broken—can it be fixed? In this episode, Tuhin Srivatsa, CEO & Co-Founder of Baseten, reveals how his company is DISRUPTING AI infrastructure, making it easier, faster, and more cost-effective to deploy and scale AI models in production.
As enterprises increasingly turn to open-source AI models and grapple with the high costs and complexity of scaling, Baseten offers a game-changing solution that eliminates bottlenecks and simplifies the process. Discover how Baseten is taking on AWS SageMaker, OpenAI, and cloud-based AI deployment platforms to reshape the future of AI model deployment.
What You’ll Learn in This Episode:Why AI deployment & scaling is one of the biggest challenges in 2025
How Baseten enables enterprises to run AI models faster & more efficiently
The shift from closed-source to open-source AI models—and why it matters
The hidden costs of AI inference & how to optimize for performance
Why most AI models fail in production and how to prevent it
The future of AI infrastructure: What comes next for scalable AI
Whether you’re a machine learning engineer, AI researcher, startup founder, or enterprise leader, this episode is packed with actionable insights to help you scale AI models without the headaches.
Don’t miss this conversation on the next era of AI deployment!
#AI #ArtificialIntelligence #MachineLearning #Baseten #AIDeployment #AIScaling #Inference #MLInfrastructure #TechPodcast
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(00:00) Tuhin Srivatsa’s Journey in AI & Baseten
(01:50) What is AI Infrastructure & Why It Matters
(03:30) How Baseten Optimizes AI Model Deployment
(05:19) Why Most AI Deployments Fail (And How to Fix It)
(09:17) The Future of Open-Source AI Models in Enterprise
(11:01) How Baseten Automates AI Scaling & Inference
(14:12) Why AI Developers Struggle with Cloud-Based AI Tools
(18:47) The Real Cost of AI Inference (And How to Reduce It)
(20:44) Why AI Scaling is the Biggest Challenge in 2025
(26:55) Can AI Run on Non-NVIDIA Chips? (The Hardware Debate)
(31:23) The Future of AI Model Deployment & Inference
(37:05) How AI Agents & Reasoning Models Are Changing the Game
(40:39) The Truth About AI Hype vs. Reality
(45:04) How to Get Started with Baseten
(45:48) The Future of AI Infrastructure
This episode is sponsored by Indeed.
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Dominic Williams’ Bold Vision for The Internet Computer (ICP) | The Future of Decentralized Computing
The internet is broken—can blockchain fix it? In this episode, Dominic Williams, the visionary behind The Internet Computer (ICP) and founder of DFINITY, reveals his plan to build a decentralized alternative to cloud computing. Discover how ICP is challenging Big Tech, replacing traditional IT infrastructure, and creating a tamper-proof, autonomous internet powered by smart contracts.
What You'll Learn in This Episode:
Why Dominic Williams believes the current internet is flawed
How ICP aims to replace centralized cloud providers like AWS & Google Cloud
The role of smart contracts in making the internet more secure and censorship-resistant
The mission of DFINITY and how it started in 2016
The future of Web3, decentralized applications (dApps), and blockchain governance
Don't miss this deep dive into the future of the internet! If you're interested in blockchain, decentralization, and the next evolution of the web, this episode is for you.
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(00:00) The Origins of The Internet Computer
(02:57) Dominic Williams’ Background in Tech
(04:28) Early Innovations in Distributed Computing
(07:08) The Birth of a 'World Computer' Concept
(11:22) Reimagining IT: A Decentralized Alternative
(13:45) The Creation of DFINITY and ICP
(16:29) How ICP Differs from Traditional Blockchains
(22:05) The Problem with Cloud-Based Blockchains
(25:35) How ICP Ensures True Decentralization
(29:25) AI & The Self-Writing Internet
(35:24) How ICP Hosts AI & Smart Contracts
(40:23) Understanding Reverse Gas and ICP’s Economy
(45:03) The Vision: A Truly Decentralized Internet
(49:09) How To Use The Internet Computer
(52:01) The Role of Nodes & Incentives in ICP
(56:53) The Future of Web3 & Decentralized Applications
(01:05:49) The Misconception of ‘On-Chain’ & Blockchain Hype
This episode is sponsored by Thuma.
Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.
To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai
In this episode of the Eye on AI podcast, Pedro Domingos—renowned AI researcher and author of The Master Algorithm—joins Craig Smith to break down the Symbolist approach to artificial intelligence, one of the Five Tribes of Machine Learning.
Pedro explains how Symbolic AI dominated the field for decades, from the 1950s to the early 2000s, and why it’s still playing a crucial role in modern AI. He dives into the Physical Symbol System Hypothesis, the idea that intelligence can emerge purely from symbol manipulation, and how AI pioneers like Marvin Minsky and John McCarthy built the foundation for rule-based AI systems.
The conversation unpacks inverse deduction—the Symbolists' "Master Algorithm"—and how it allows AI to infer general rules from specific examples. Pedro also explores how decision trees, random forests, and boosting methods remain some of the most powerful AI techniques today, often outperforming deep learning in real-world applications.
We also discuss why expert systems failed, the knowledge acquisition bottleneck, and how machine learning helped solve Symbolic AI’s biggest challenges. Pedro shares insights on the heated debate between Symbolists and Connectionists, the ongoing battle between logic-based reasoning and neural networks, and why the future of AI lies in combining these paradigms.
From AlphaGo’s hybrid approach to modern AI models integrating logic and reasoning, this episode is a deep dive into the past, present, and future of Symbolic AI—and why it might be making a comeback.
Don't forget to like, subscribe, and hit the notification bell for more expert discussions on AI, technology, and the future of intelligence!
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(00:00) Pedro Domingos onThe Five Tribes of Machine Learning
(02:23) What is Symbolic AI?
(04:46) The Physical Symbol System Hypothesis Explained
(07:05) Understanding Symbols in AI
(11:51) What is Inverse Deduction?
(15:10) Symbolic AI in Medical Diagnosis
(17:35) The Knowledge Acquisition Bottleneck
(19:05) Why Symbolic AI Struggled with Uncertainty
(20:40) Machine Learning in Symbolic AI – More Than Just Connectionism
(24:08) Decision Trees & Their Role in Symbolic Learning
(26:55) The Myth of Feature Engineering in Deep Learning
(30:18) How Symbolic AI Invents Its Own Rules
(31:54) The Rise and Fall of Expert Systems – The CYCL Project
(38:53) Symbolic AI vs. Connectionism
(41:53) Is Symbolic AI Still Relevant Today?
(43:29) How AlphaGo Combined Symbolic AI & Neural Networks
(45:07) What Symbolic AI is Best At – System 2 Thinking
(47:18) Is GPT-4o Using Symbolic AI?
This episode is sponsored by Thuma.
Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.
To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai
In this episode of the Eye on AI podcast, Pedro Domingos, renowned AI researcher and author of The Master Algorithm, joins Craig Smith to explore the evolution of machine learning, the resurgence of Bayesian AI, and the future of artificial intelligence.
Pedro unpacks the ongoing battle between Bayesian and Frequentist approaches, explaining why probability is one of the most misunderstood concepts in AI. He delves into Bayesian networks, their role in AI decision-making, and how they powered Google’s ad system before deep learning. We also discuss how Bayesian learning is still outperforming humans in medical diagnosis, search & rescue, and predictive modeling, despite its computational challenges.
The conversation shifts to deep learning’s limitations, with Pedro revealing how neural networks might be just a disguised form of nearest-neighbor learning. He challenges conventional wisdom on AGI, AI regulation, and the scalability of deep learning, offering insights into why Bayesian reasoning and analogical learning might be the future of AI.
We also dive into analogical learning—a field championed by Douglas Hofstadter—exploring its impact on pattern recognition, case-based reasoning, and support vector machines (SVMs). Pedro highlights how AI has cycled through different paradigms, from symbolic AI in the '80s to SVMs in the 2000s, and why the next big breakthrough may not come from neural networks at all.
From theoretical AI debates to real-world applications, this episode offers a deep dive into the science behind AI learning methods, their limitations, and what’s next for machine intelligence.
Don’t forget to like, subscribe, and hit the notification bell for more expert discussions on AI, technology, and the future of innovation!
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(00:00) Introduction
(02:55) The Five Tribes of Machine Learning Explained
(06:34) Bayesian vs. Frequentist: The Probability Debate
(08:27) What is Bayes' Theorem & How AI Uses It
(12:46) The Power & Limitations of Bayesian Networks
(16:43) How Bayesian Inference Works in AI
(18:56) The Rise & Fall of Bayesian Machine Learning
(20:31) Bayesian AI in Medical Diagnosis & Search and Rescue
(25:07) How Google Used Bayesian Networks for Ads
(28:56) The Role of Uncertainty in AI Decision-Making
(30:34) Why Bayesian Learning is Computationally Hard
(34:18) Analogical Learning – The Overlooked AI Paradigm
(38:09) Support Vector Machines vs. Neural Networks
(41:29) How SVMs Once Dominated Machine Learning
(45:30) The Future of AI – Bayesian, Neural, or Hybrid?
(50:38) Where AI is Heading Next
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
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In this episode of Eye on AI, Vall Herard, CEO of Saifr.ai, joins Craig Smith to explore how AI is transforming compliance in financial services.
Saifr.ai acts as a "grammar check" for regulatory compliance, ensuring AI-generated content meets SEC, FINRA, and global financial regulations. Vall explains how Saifr integrates into Microsoft Word, Outlook, and Adobe, reducing compliance risks in marketing, emails, and AI chatbots.
We also discuss Saifr.ai’s partnership with Microsoft, AI’s role in regulated industries, and how businesses can safely adopt generative AI without violating compliance laws. - How does AI reduce compliance friction? - Why is regulatory oversight a barrier to AI adoption? - What does AI safety really mean for financial services?
Find out in this deep dive into AI, compliance, and the future of regulation.
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Strengthen your compliance controls with AI: https://saifr.ai/
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(00:00) Introduction to Generative AI and Compliance (02:47) Meet Vall Herard, CEO of Saifr.ai (05:28) What Saifr.ai Does and Its Mission (08:25) How Saifr.ai Ensures Regulatory Compliance (12:13) Overcoming AI Adoption Barriers in Finance (19:58) Saifr.ai’s Partnership with Microsoft (24:11) How SaferAI Integrates with Microsoft Office (29:33) AI in Podcast and Audio Compliance Review (33:54) Saifr.ai’s Business Model and Pricing (38:09) How Saifr.ai Works with Generative AI Chatbots (42:36) Supporting Multiple Languages for Compliance (50:08) Future Outlook
In this episode of the Eye on AI podcast, Tyler Xuan Saltsman, CEO of Edgerunner, joins Craig Smith to explore how AI is reshaping military strategy, logistics, and defense technology—pushing the boundaries of what’s possible in modern warfare.
Tyler shares the vision behind Edgerunner, a company at the cutting edge of generative AI for military applications. From logistics and mission planning to autonomous drones and battlefield intelligence, Edgerunner is building domain-specific AI that enhances decision-making, ensuring national security while keeping humans in control.
We dive into how AI-powered military agents work, including the LoRA (Low-Rank Adaptation) model, which fine-tunes AI to think and act like military specialists—whether in logistics, aircraft maintenance, or real-time combat scenarios. Tyler explains how retrieval-augmented generation (RAG) and small language models allow warfighters to access mission-critical intelligence without relying on the internet, bringing real-time AI support directly to the battlefield.
Tyler also discusses the future of drone warfare—how AI-driven, vision-enabled drones can neutralize threats autonomously, reducing reliance on human pilots while increasing battlefield efficiency. With autonomous swarms, AI-powered kamikaze drones, and real-time situational awareness, the landscape of modern warfare is evolving fast.
Beyond combat, we explore AI’s role in security, including advanced weapons detection systems that can safeguard military bases, schools, and public spaces. Tyler highlights the urgent need for transparency in AI, contrasting Edgerunner’s open and auditable AI models with the black-box approaches of major tech companies.
Discover how AI is transforming military operations, from logistics to combat strategy, and what this means for the future of defense technology.
Don’t forget to like, subscribe, and hit the notification bell for more deep dives into AI, defense, and cutting-edge technology!
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00:00) Introduction – AI for the Warfighter
(01:34) How AI is Transforming Military Logistics(
04:44) Running AI on the Edge – No Internet Required
(06:49) AI-Powered Mission Planning & Risk Mitigation
(14:32) The Future of AI in Drone Warfare
(22:17) AI’s Role in Strategic Defense & Economic Warfare
(26:34) The U.S.-China AI Race – Are We Falling Behind?
(35:17) The Future of AI in Warfare
In this episode of the Eye on AI podcast, Matt Price, CEO of Crescendo, joins Craig Smith to discuss how generative AI is reshaping customer service and blending seamlessly with human expertise to create next-level customer experiences.
Matt shares the story behind Crescendo, a company at the forefront of revolutionizing customer service by integrating advanced AI technology with human-driven solutions. With a focus on outcome-based service delivery and quality assurance, Crescendo is setting a new standard for customer engagement.
We dive into Crescendo’s innovative approach, including its use of large language models (LLMs) combined with proprietary IP to deliver consistent, high-quality support across 56 languages. Matt explains how Crescendo’s AI tools are designed to handle routine tasks while enabling human agents to focus on complex, empathy-driven interactions—resulting in higher job satisfaction and better customer outcomes.
Matt highlights how Crescendo is redefining the BPO industry, combining AI and human capabilities to reduce costs while improving the quality of customer interactions. From enhancing agent retention to enabling scalable, multilingual support, Crescendo’s impact is transformative.
Discover how Matt and his team are designing a future where AI and humans work together to deliver exceptional customer experiences—reimagining what’s possible in the world of customer service.
Don’t forget to like, subscribe, and hit the notification bell for more insights into AI, technology, and innovation!
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(00:00) Introduction to Matt Price and Crescendo
(01:49) The rise of AI in customer service
(05:34) Using AI and human expertise for better customer experiences
(07:47) How Gen AI reduces costs and improves engagement
(09:37) Challenges in customer service design and innovation
(11:32) Moving from hidden chatbots to front-and-center customer interaction
(14:08) Training human agents to work seamlessly with AI
(17:02) Using AI to analyze and improve service interactions
(19:15) Outcome-based pricing vs traditional headcount models
(21:53) Improving contact center roles with AI integration
(25:08) The importance of curating accurate knowledge bases for AI
(28:05) Crescendo’s acquisition of PartnerHero and its impact
(30:39) Scaling customer service with AI-human collaboration
(32:06) Multilingual support: AI in 56 languages
(33:49) The vast market potential of AI-driven customer service
(36:28) How Crescendo is reshaping customer service with AI innovation
(42:42) Building customer profiles for personalized support
In this special episode of the Eye on AI podcast, Sepp Hochreiter, the inventor of Long Short-Term Memory (LSTM) networks, joins Craig Smith to discuss the profound impact of LSTMs on artificial intelligence, from language models to real-time robotics. Sepp reflects on the early days of LSTM development, sharing insights into his collaboration with Jürgen Schmidhuber and the challenges they faced in gaining recognition for their groundbreaking work. He explains how LSTMs became the foundation for technologies used by giants like Amazon, Apple, and Google, and how they paved the way for modern advancements like transformers. Topics include: - The origin story of LSTMs and their unique architecture. - Why LSTMs were crucial for sequence data like speech and text. - The rise of transformers and how they compare to LSTMs. - Real-time robotics: using LSTMs to build energy-efficient, autonomous systems. The next big challenges for AI and robotics in the era of generative AI. Sepp also shares his optimistic vision for the future of AI, emphasizing the importance of efficient, scalable models and their potential to revolutionize industries from healthcare to autonomous vehicles. Don’t miss this deep dive into the history and future of AI, featuring one of its most influential pioneers. (00:00) Introduction: Meet Sepp Hochreiter (01:10) The Origins of LSTMs (02:26) Understanding the Vanishing Gradient Problem (05:12) Memory Cells and LSTM Architecture (06:35) Early Applications of LSTMs in Technology (09:38) How Transformers Differ from LSTMs (13:38) Exploring XLSTM for Industrial Applications (15:17) AI for Robotics and Real-Time Systems (18:55) Expanding LSTM Memory with Hopfield Networks (21:18) The Road to XLSTM Development (23:17) Industrial Use Cases of XLSTM (27:49) AI in Simulation: A New Frontier (32:26) The Future of LSTMs and Scalability (35:48) Inference Efficiency and Potential Applications (39:53) Continuous Learning and Adaptability in AI (42:59) Training Robots with XLSTM Technology (44:47) NXAI: Advancing AI in Industry
In this episode of the Eye on AI podcast, Paras Jain, CEO and Co-founder of Genmo, joins Craig Smith to explore the cutting-edge world of AI-driven video generation, the open-source revolution, and the future of creative storytelling.
Paras shares the story behind Genmo, a company at the forefront of advancing video generation technologies, and their groundbreaking model, Mochi One. With a focus on motion quality and prompt adherence, Genmo is redefining what's possible in generative AI for video, offering unmatched precision and creative possibilities.
We delve into the innovative approach behind Mochi One, including its state-of-the-art architecture, which enables fast, high-quality video generation. Paras explains how Genmo’s commitment to open source empowers developers and researchers worldwide, fostering rapid advancements, customization, and the creation of new tools, like video-to-video editing.
The conversation touches on key themes such as scalability, synthetic data pipelines, and the transformative potential of AI in creating immersive virtual worlds. Paras also explores how Genmo is bridging the gap between cutting-edge AI and practical applications, from TikTok-ready videos to future possibilities like interactive environments and real-time video game-like experiences.
Discover how Paras and his team are shaping the future of video creation, blending art, science, and open collaboration to push the boundaries of generative AI.
Don’t forget to like, subscribe, and hit the notification bell for more insightful conversations on AI, technology, and innovation!
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(00:00) Introduction to Paras Jain and Genmo
(01:45) Video generation with Mochi One
(04:41) Open-source AI in video generation
(06:08) Building Mochi One
(12:03) Simulating complex physics in video models
(14:35) Reducing latency: Fast video generation at scale
(20:34) Tackling cost challenges for longer videos
(23:14) Character consistency in AI-generated videos
(27:17) Why video models represent intelligence's next frontier
(30:18) How diffusion models create sharp, realistic videos
(34:02) Visualizing the denoising process in video generation
(39:36) Exploring user-generated video creations with Mochi One
(42:05) Monetizing open-source AI for video generation
(45:47) Video generation's potential in the metaverse
(47:19) Collaborating with universities to advance AI
(48:39) The future of generative AI
This episode is sponsored by Oracle.
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In this episode of the Eye on AI podcast, Jamie Lerner, CEO of Quantum, joins Craig Smith to discuss the future of data storage, unstructured data management, and AI’s transformative role in modern workflows.
Jamie shares his journey leading Quantum, a company revolutionizing the storage and management of unstructured data for industries like healthcare, media, and AI research. With decades of expertise in creating innovative data solutions, Quantum is at the forefront of enabling efficient, secure, and scalable data workflows.
We dive into Quantum’s cutting-edge technologies, from high-speed flash storage systems like the Myriad file system to cost-effective, long-term archival solutions such as tape systems. Jamie unpacks how Quantum supports AI-powered workflows, enabling seamless data movement, metadata tagging, and policy-driven automation for unstructured data like medical imaging, genomics, and video archives.
Jamie also explores the critical role of data sovereignty in today’s global landscape, the growing importance of "forever archives," and how Quantum’s tools help organizations balance exponential data growth with flat budgets. He sheds light on innovations like synthetic DNA and compressed storage mediums, providing a glimpse into the future of data storage.
Don’t forget to like, subscribe, and hit the notification bell for more engaging discussions on AI, technology, and innovation!
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(00:00) Introduction to Jamie Lerner and Quantum
(02:21) Quantum’s Focus on Unstructured Data Storage
(05:19) Structured vs. Unstructured Data: Key Differences
(07:52) Managing Data Workflows with AI and Automation
(10:55) Quantum’s Role in Long-Term Data Archives
(13:32) Data Sovereignty and Security
(16:18) How Data is Stored and Protected Across Mediums
(19:54) Metadata in AI and Data Management
(21:29) Quantum’s Role in Building Forever Archives
(24:16) Tape Storage: Efficiency and Longevity
(29:11) Innovations in Data Storage
(34:39) Competing in the Evolving Data Storage Industry
(37:56) Innovations in Flash Storage
(40:55) Balancing Cost and Efficiency in Data Storage
(44:28) The Future of Data Storage and AI Integration
(50:07) Quantum’s Vision for the Future
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
In this episode of the Eye on AI podcast, we dive into the transformative world of AI compute infrastructure with Mitesh Agrawal, Head of Cloud/COO at Lambda
Mitesh takes us on a journey from Lambda Labs' early days as a style transfer app to its rise as a leader in providing scalable, deep learning infrastructure. Learn how Lambda Labs is reshaping AI compute by delivering cutting-edge GPU solutions and accessible cloud platforms tailored for developers, researchers, and enterprises alike.
Throughout the episode, Mitesh unpacks Lambda Labs’ unique approach to optimizing AI infrastructure—from reducing costs with transparent pricing to tackling the global GPU shortage through innovative supply chain strategies. He explains how the company supports deep learning workloads, including training and inference, and why their AI cloud is a game-changer for scaling next-gen applications.
We also explore the broader landscape of AI, touching on the future of AI compute, the role of reasoning and video models, and the potential for localized data centers to meet the growing demand for low-latency solutions. Mitesh shares his vision for a world where AI applications, powered by Lambda Labs, drive innovation across industries.
Tune in to discover how Lambda Labs is democratizing access to deep learning compute and paving the way for the future of AI infrastructure.
Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest in AI, deep learning, and transformative tech!
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(00:00) Introduction and Lambda Labs' Mission
(01:37) Origins: From DreamScope to AI Compute Infrastructure
(04:10) Pivoting to Deep Learning Infrastructure
(06:23) Building Lambda Cloud: An AI-Focused Cloud Platform
(09:16) Transparent Pricing vs. Hyperscalers
(12:52) Managing GPU Supply and Demand
(16:34) Evolution of AI Workloads: Training vs. Inference
(20:02) Why Lambda Labs Sticks with NVIDIA GPUs
(24:21) The Future of AI Compute: Localized Data Centers
(28:30) Global Accessibility and Regulatory Challenges
(32:13) China’s AI Development and GPU Restrictions
(39:50) Scaling Lambda Labs: Data Centers and Growth
(45:22) Advancing AI Models and Video Generation
(50:24) Optimism for AI's Future
(53:48) How to Access Lambda Cloud
This episode is sponsored by RapidSOS. Close the safety gap and transform your emergency response with RapidSOS.
Visit https://rapidsos.com/eyeonai/ today to learn how AI-powered safety can protect your people and boost your bottom line.
In this episode of the Eye on AI podcast, we explore the world of AI inference technology with Rodrigo Liang, co-founder and CEO of SambaNova Systems.
Rodrigo shares his journey from high-performance chip design to building SambaNova, a company revolutionizing how enterprises leverage AI through scalable, power-efficient solutions. We dive into SambaNova’s groundbreaking achievements, including their record-breaking inference models, the Lama 405B and 70B, which deliver unparalleled speed and accuracy—all on a single rack consuming less than 10 kilowatts of power.
Throughout the conversation, Rodrigo highlights the seismic shift from AI training to inference, explaining why production AI is now about speed, efficiency, and real-time applications. He details SambaNova’s approach to open-source models, modular deployment, and multi-tenancy, enabling enterprises to scale AI without costly infrastructure overhauls.
We also discuss the competitive landscape of AI hardware, the challenges of NVIDIA’s dominance, and how SambaNova is paving the way for a new era of AI innovation. Rodrigo explains the critical importance of power efficiency and how SambaNova’s technology is unlocking opportunities for enterprises to deploy private, secure AI systems on-premises and in the cloud.
Discover how SambaNova is redefining AI for enterprise adoption, enabling real-time AI, and setting new standards in efficiency and scalability.
Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest breakthroughs in AI, technology, and enterprise innovation!
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In this episode of the Eye on AI podcast, we dive into the critical issue of data quality for AI systems with Sedarius Perrotta, co-founder of Shelf.
Sedarius takes us on a journey through his experience in knowledge management and how Shelf was built to solve one of AI’s most pressing challenges—unstructured data chaos. He shares how Shelf’s innovative solutions enhance retrieval-augmented generation (RAG) and ensure tools like Microsoft Copilot can perform at their best by tackling inaccuracies, duplications, and outdated information in real-time.
Throughout the episode, we explore how unstructured data acts as the "fuel" for AI systems and why its quality determines success. Sedarius explains Shelf's approach to data observability, transparency, and proactive monitoring to help organizations fix "garbage in, garbage out" issues, ensuring scalable and trusted AI initiatives.
We also discuss the accelerating adoption of generative AI, the future of data management, and why building a strategy for clean and trusted data is vital for 2025 and beyond. Learn how Shelf enables businesses to unlock the full potential of their unstructured data for AI-driven productivity and innovation.
Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest advancements in AI, data management, and next-gen automation!
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(00:00) Introduction and Shelf's Mission (03:01) Understanding SharePoint and Data Challenges (05:29) Tackling Data Entropy in AI Systems (08:13) Using AI to Solve Data Quality Issues (12:30) Fixing AI Hallucinations with Trusted Data (21:01) Gen AI Adoption Insights and Trends (28:44) Benefits of Curated Data for AI Training (37:38) Future of Unstructured Data Management
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In this episode of the Eye on AI podcast, we explore the cutting-edge world of AI-powered autonomy with Nathan Michael, CTO of Shield AI.
Nathan shares his journey from academia to leading one of the most innovative companies in defense technology, revealing how Shield AI is transforming autonomous systems to operate in the most challenging environments.
Throughout the episode, Nathan dives into Shield AI's groundbreaking technologies, including the revolutionary Hivemind platform, which enables drones and uncrewed jets to think, adapt, and act independently—even in GPS-denied and communication-jammed conditions. He explains how these systems are deployed across defense and commercial applications, reshaping intelligence, surveillance, and reconnaissance missions with unprecedented precision and resilience.
We also discuss the future of warfare and technology, from the commoditization of AI-driven autonomy to the ethical and strategic considerations of deploying these systems at scale. Nathan offers insights into how rapid iteration cycles and resilient intelligence will define the next era of defense innovation, ensuring mission success in increasingly complex scenarios.
Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest advancements in AI, robotics, and the future of autonomous systems!
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(00:00) Introduction to Shield AI and Hivemind
(03:02) Nathan Michael's journey to Shield AI
(06:07) Shield AI's mission and technology overview
(10:18) VBAT: A versatile tail-sitter aircraft
(12:44) Hivemind's swarm capabilities and applications
(14:32) Ethics and societal guardrails for autonomous systems
(17:24) Combat applications of quadcopters
(19:12) Navigating and mapping unknown environments
(20:38) Use of VBAT in Ukraine operations
(22:10) Intelligence gathering and mission versatility
(24:42) Transforming warfare with AI-driven autonomy
(28:47) Teaming and communication in autonomous swarms
(32:29) Communication networks in jammed conditions
(35:34) Coordinated exploration with autonomous systems
(38:13) Exploring buildings with quadcopter teams
(40:57) Crewed-uncrewed teaming in modern combat
(43:28) Global competition in AI and autonomy
(46:03) Use of autonomous drones in Ukraine
(50:28) Shield AI's vision: Proliferation of resilient intelligence
(55:26) Expanding AI autonomy to commercial applications
This episode is sponsored by RapidSOS. Close the safety gap and transform your emergency response with RapidSOS.
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In this episode of the Eye on AI podcast, we delve into the role of AI in product management with Christian Marek, VP of Product at Productboard.
Christian shares his journey in shaping the future of product management, exploring how AI is changing the way we ideate, build, and deliver customer-centric products.
Throughout the episode, Christian unveils Productboard's innovative AI-driven solutions, including the groundbreaking Productboard Pulse, which accelerates ideation and discovery by aggregating and analyzing customer feedback. He explains how AI enables product managers to prioritize features, write detailed specifications, and align product roadmaps with organizational goals—all while driving ROI and delivering exceptional customer experiences.
We also discuss the evolution of product management, from its origins to its rise as a mainstream discipline in organizations of all sizes. Christian offers insights into how AI tools are reshaping the product management landscape, making it more efficient, collaborative, and impactful than ever before.
Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest breakthroughs in AI, product innovation, and customer-centric technology!
Checkout Productboard Pulse: https://www.productboard.com/product/voice-of-customer/
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(00:00) Introduction
(03:18) What is Productboard?
(05:04) Christian Marek’s Journey
(07:20) Defining Product Management
(08:45) How Productboard Was Born
(10:05) Transforming Product Management
(14:32) Exploring Use Cases: Existing and New Product Development
(18:13) Scaling Productboard
(20:33) Managing Complex Projects Without Productboard
(24:59) Industries Using Productboard
(26:29) Why Startups Benefit from Productboard
(29:25) Closing the Feedback Loop on Product Management
(33:16) Non-Digital Applications of Productboard
(36:27) AI Model Selection
(39:48) The Future of Product Management with AI
(43:30) C-Suite Engagement and ROI with Productboard
(45:15) How to Get Started with Productboard
This episode is sponsored by Oracle.
Oracle Cloud Infrastructure, or OCI is a blazing fast and secure platform for your infrastructure, database, application development, plus all your AI and machine learning workloads. OCI costs 50% less for compute and 80% less for networking. So you’re saving a pile of money. Thousands of businesses have already upgraded to OCI, including MGM Resorts, Specialized Bikes, and Fireworks AI.
Cut your current cloud bill in HALF if you move to OCI now: https://oracle.com/eyeonai
In this episode of the Eye on AI podcast, Tariq Shaukat, CEO of Sonar, joins Craig Smith to explore the future of code quality, security, and AI’s role in software development.
Tariq shares his journey from leading roles at Google Cloud and Bumble to helming Sonar, a company disrupting code assurance for developers worldwide. With over 7 million users and support for 30+ programming languages, Sonar has become a critical tool in ensuring clean, maintainable, and secure code.
We dive into Sonar’s innovative AI Code Assurance Workflow, which integrates seamlessly with generative AI tools like Copilot and Codium. Tariq discusses how Sonar addresses the challenges of AI-generated code, tackling issues like security vulnerabilities, maintainability problems, and the accountability crisis in today’s coding landscape.
Tariq also unpacks the importance of hybrid deterministic and AI-driven approaches, the role of design and architecture in modern software development, and how Sonar is helping companies manage tech debt across billions of lines of code.
With Sonar’s recent enterprise-grade SaaS launch and commitment to reducing developer toil, this episode offers valuable insights for developers, tech leaders, and anyone interested in the evolving intersection of AI and software engineering.
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(00:00) Introduction to Tariq Shaukat and Sonar
(01:23) Overview of SonarQube
(03:03) Deterministic Systems and AI Integration
(07:36) Challenges of AI-Generated Code
(10:12) Early Issue Detection in Development
(12:33) Accountability in AI Code Generation
(16:20) Importance of Rigorous Code Reviews
(19:34) Managing Tech Debt with Continuous Improvement
(22:16) Why Sonar Focuses on Integration
(25:08) Reviewing Billion-Line Code Bases with Sonar
(29:37) Tailoring Sonar for Specific Codebases and Workflows
(32:40) Avoiding Overwhelming Developers with Noise
(37:49) Governance and Managing Complex Codebases
(40:50) Addressing Tech Debt in Legacy Systems
(45:07) Sonar’s Open-Source Model and Philosophy
(48:11) What’s Next for Sonar
Launch, run, and protect your business to make it official TODAY at https://www.legalzoom.com and use promo code EYEONAI to get 10% off any LegalZoom business formation product excluding subscriptions and renewals.
In this episode of the Eye on AI podcast, Matt Panousis, Co-Founder & COO @ LipDub AI, shares the journey behind the platforms a cutting-edge AI-powered lip-syncing tool revolutionizing the dubbing industry.
Matt joins Craig to explore the future of content localization, the evolution of LipDub, and how generative AI is transforming how audiences experience video content worldwide.
As a leader in AI and visual effects, Matt discusses how LipDub integrates advanced AI to enable real-time lip-syncing for dubbed audio, making Hollywood-quality dubbing affordable and accessible. From processing hours of video footage to handling complex, dynamic scenes, LipDub is empowering content creators to reach global audiences like never before.
We explore the challenges of creating realistic lip movements, the importance of mouth internals, textures, and fidelity, and how tools like LipDub stand apart from competitors like Rasque AI. Matt also introduces Vanity AI, LipDub’s sister technology for automated digital makeup and de-aging, used by MARZ for high-end visual effects work.
Learn how LipDub is redefining the possibilities of content localization with AI and what the future holds as this technology evolves.
Don’t miss this deep dive into AI-powered innovation with Matt Panousis. Like, subscribe, and hit the notification bell for more episodes exploring cutting-edge advancements in AI!
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(00:00) Introduction & Matt Panousis Background (02:45) Origins of MARZ and LipDub (04:20) LipDub vs. Competitors (06:15) Integration with Dubbing Solutions (08:00) LipDub Technical Process (10:20) Competition (12:20) Time and Cost (14:00) Target Markets and Use Cases (19:00) Future Developments (22:00) Translation and Timing Challenges (28:00) Ethical Concerns and Misuse (30:30) Digital Watermarking (32:25) Real-World Examples and Future Products (34:00) Team Building and Research (37:00) Building the Advisory Board (38:10) Securing Research Talent (40:00) Funding and the Board (40:35) Future Products
Launch, run, and protect your business to make it official TODAY at https://www.legalzoom.com and use promo code EYEONAI to get 10% off any LegalZoom business formation product excluding subscriptions and renewals.
In this episode of the Eye on AI podcast, Matt Panousis, Co-Founder & COO @ LipDub AI, shares the journey behind the platforms a cutting-edge AI-powered lip-syncing tool revolutionizing the dubbing industry.
Matt joins Craig to explore the future of content localization, the evolution of LipDub, and how generative AI is transforming how audiences experience video content worldwide.
As a leader in AI and visual effects, Matt discusses how LipDub integrates advanced AI to enable real-time lip-syncing for dubbed audio, making Hollywood-quality dubbing affordable and accessible. From processing hours of video footage to handling complex, dynamic scenes, LipDub is empowering content creators to reach global audiences like never before.
We explore the challenges of creating realistic lip movements, the importance of mouth internals, textures, and fidelity, and how tools like LipDub stand apart from competitors like Rasque AI. Matt also introduces Vanity AI, LipDub’s sister technology for automated digital makeup and de-aging, used by MARZ for high-end visual effects work.
Learn how LipDub is redefining the possibilities of content localization with AI and what the future holds as this technology evolves.
Don’t miss this deep dive into AI-powered innovation with Matt Panousis. Like, subscribe, and hit the notification bell for more episodes exploring cutting-edge advancements in AI!
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Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Introduction & Matt Panousis Background (02:45) Origins of MARZ and LipDub (04:20) LipDub vs. Competitors (06:15) Integration with Dubbing Solutions (08:00) LipDub Technical Process (10:20) Competition (12:20) Time and Cost (14:00) Target Markets and Use Cases (19:00) Future Developments (22:00) Translation and Timing Challenges (28:00) Ethical Concerns and Misuse (30:30) Digital Watermarking (32:25) Real-World Examples and Future Products (34:00) Team Building and Research (37:00) Building the Advisory Board (38:10) Securing Research Talent (40:00) Funding and the Board (40:35) Future Products
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
In this episode of the Eye on AI podcast, we explore the cutting-edge world of semiconductor innovation and its role in the future of artificial intelligence with Kai Beckmann, CEO of Merck KGaA.
Kai takes us on a journey into the heart of semiconductor manufacturing, revealing how next-generation chips are driving the AI revolution. From the complex process of creating advanced chips to the increasing demands of AI on semiconductor technology, Kai shares how Merck is pioneering materials science to unlock unprecedented levels of computational power.
Throughout the conversation, Kai explains how AI’s growth is reshaping the semiconductor industry, with innovations like edge AI, heterogeneous integration, and 3D chip architectures pushing the boundaries of performance. He highlights how Merck is using artificial intelligence to accelerate material discovery, reduce experimentation cycles, and create smarter, more efficient processes for the chips that power everything from smartphones to data centers.
Kai also delves into the global landscape of semiconductor manufacturing, discussing the challenges of supply chains, the cyclical nature of the industry, and the rapid technological advancements needed to meet AI’s demands. He explains why the semiconductor sector is entering the "Age of Materials," where breakthroughs in materials science are enabling the next wave of AI-driven devices.
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(00:00) Introduction
(02:48) Merck KGaA
(05:21) Foundations of Semiconductor Manufacturing
(07:57) How Chips Are Made
(09:24) Exploring Materials Science
(13:59) Growth and Trends in the Semiconductor Industry
(15:44) Semiconductor Manufacturing
(17:34) AI’s Growing Demands on Semiconductor Tech
(20:34) The Future of Edge AI
(22:10) Using AI to Disrupt Material Discovery
(24:58) How AI Accelerates Innovation in Semiconductors
(27:32) Evolution of Semiconductor Fabrication Processes
(30:08) Advanced Techniques: Chiplets, 3D Stacking, and Beyond
(32:29) Merck’s Role in Global Semiconductor Innovation
(34:03) Major Markets for Semiconductor Manufacturing
(37:18) Challenges in Reducing Latency and Energy Consumption
(40:21) Exploring New Conductive Materials for Efficiency
This episode is sponsored by Shopify.
Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
In this episode of the Eye on AI podcast, Andrew D. Feldman, Co-Founder and CEO of Cerebras Systems, unveils how Cerebras is disrupting AI inference and high-performance computing.
Andrew joins Craig Smith to discuss the groundbreaking wafer-scale engine, Cerebras’ record-breaking inference speeds, and the future of AI in enterprise workflows. From designing the fastest inference platform to simplifying AI deployment with an API-driven cloud service, Cerebras is setting new standards in AI hardware innovation.
We explore the shift from GPUs to custom architectures, the rise of large language models like Llama and GPT, and how AI is driving enterprise transformation. Andrew also dives into the debate over open-source vs. proprietary models, AI’s role in climate mitigation, and Cerebras’ partnerships with global supercomputing centers and industry leaders.
Discover how Cerebras is shaping the future of AI inference and why speed and scalability are redefining what’s possible in computing.
Don’t miss this deep dive into AI’s next frontier with Andrew Feldman.
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(00:00) Intro to Andrew Feldman & Cerebras Systems
(00:43) The rise of AI inference
(03:16) Cerebras’ API-powered cloud
(04:48) Competing with NVIDIA’s CUDA
(06:52) The rise of Llama and LLMs
(07:40) OpenAI's hardware strategy
(10:06) Shifting focus from training to inference
(13:28) Open-source vs proprietary AI
(15:00) AI's role in enterprise workflows
(17:42) Edge computing vs cloud AI
(19:08) Edge AI for consumer apps
(20:51) Machine-to-machine AI inference
(24:20) Managing uncertainty with models
(27:24) Impact of U.S.–China export rules
(30:29) U.S. innovation policy challenges
(33:31) Developing wafer-scale engines
(34:45) Cerebras’ fast inference service
(37:40) Global partnerships in AI
(38:14) AI in climate & energy solutions
(39:58) Training and inference cycles
(41:33) AI training market competition
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In this episode of the Eye on AI podcast, Varun Mohan, Co-Founder and CEO of Codeium, shares the journey behind building one of the most innovative AI-powered coding tools available today.
Varun joins Craig Smith to explore the future of software development, the evolution of Codeium, and how generative AI is revolutionizing the way developers interact with codebases.
As a leader in AI and software engineering, Varun discusses how Codeium integrates advanced AI to enable real-time code completion, refactoring, and even end-to-end application building. From processing billions of lines of code to making complex legacy systems like COBOL more accessible, Codeium is empowering developers to work smarter and faster.
We delve into the challenges of managing massive codebases, the importance of maintaining security and self-hosted solutions, and how tools like Codeium stand apart from competitors like Copilot and CodeWhisperer. Varun also introduces **Cascade**, the AI assistant within Codeium’s custom IDE, Windsurf, which merges human ingenuity with AI's reasoning capabilities for a seamless coding experience.
Other fascinating topics include the role of AI in onboarding developers to complex systems, its ability to handle rare programming languages, and how Codeium is reshaping the software lifecycle from design to deployment.
Learn how Codeium is redefining the possibilities of software development with AI, and what the future holds as this technology continues to evolve.
Don’t miss this deep dive into AI-powered innovation with Varun Mohan. Like, subscribe, and hit the notification bell for more episodes exploring cutting-edge advancements in AI!
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(00:00) Introduction to Varun Mohan and Codeium
(05:32) Introducing Codeium: AI-powered coding revolution
(08:42) Competing with Copilot and CodeWhisperer
(11:46) Using Codeium to streamline software development
(14:01) Features of Cascade: Refactoring and automation
(17:26) Building applications from scratch with Codeium
(22:00) Enterprise adoption and recognition by JPMorgan Chase
(23:14) The pivot to Codeium and lessons learned
(24:32) The vision for Codeium’s future
This episode of Eye on AI is sponsored by Citrusx.
Unlock reliable AI with Citrusx! Our platform simplifies validation and risk management, empowering you to make smarter decisions and stay compliant. Detects and mitigate AI vulnerabilities, biases, and errors with ease.
Visit http://email.citrusx.ai/eyeonai to download our free fairness use case and see the solution in action.
In this episode of the Eye on AI podcast, Terry Sejnowski, a pioneer in neural networks and computational neuroscience, joins Craig Smith to discuss the future of AI, the evolution of ChatGPT, and the challenges of understanding intelligence.
Terry, a key figure in the deep learning revolution, shares insights into how neural networks laid the foundation for modern AI, including ChatGPT’s groundbreaking generative capabilities. From its ability to mimic human-like creativity to its limitations in true understanding, we explore what makes ChatGPT remarkable and what it still lacks compared to human cognition.
We also dive into fascinating topics like the debate over AI sentience, the concept of "hallucinations" in AI models, and how language models like ChatGPT act as mirrors reflecting user input rather than possessing intrinsic intelligence. Terry explains how understanding language and meaning in AI remains one of the field’s greatest challenges.
Additionally, Terry shares his perspective on nature-inspired AI and what it will take to develop systems that go beyond prediction to exhibit true autonomy and decision-making.
Learn why AI models like ChatGPT are revolutionary yet incomplete, how generative AI might redefine creativity, and what the future holds for AI as we continue to push its boundaries.
Don’t miss this deep dive into the fascinating world of AI with Terry Sejnowski. Like, subscribe, and hit the notification bell for more cutting-edge AI insights!
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(00:00) Introduction to Terry Sejnowski and His Work
(03:02) The Origins of Modern AI and Neural Networks
(05:29) The Deep Learning Revolution and ImageNet
(07:11) Understanding ChatGPT and Generative AI
(12:34) Exploring AI Creativity
(16:03) Lessons from Gaming AI: AlphaGo and Backgammon
(18:37) Early Insights into AI’s Affinity for Language
(24:48) Syntax vs. Semantics: The Purpose of Language
(30:00) How Written Language Transformed AI Training
(35:10) Can AI Become Sentient?
(41:37) AI Agents and the Next Frontier in Automation
(45:43) Nature-Inspired AI: Lessons from Biology
(50:02) Digital vs. Biological Computation: Key Differences
(54:29) Will AI Replace Jobs?
(57:07) The Future of AI
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
In this episode of the Eye on AI podcast, Avthar Sewrathan, Lead Technical Product Marketing Manager at Timescale joins Craig Smith to explore how Postgres is transforming AI development with cutting-edge tools and open-source innovation.
With its robust, extensible framework, Postgres has become the go-to database for AI applications, from semantic search to retrieval-augmented generation (RAG). Avthar takes us through Timescale's journey from its IoT origins to disrupting the way developers handle vector search, embedding management, and high-performance AI workloads—all within Postgres.
We dive into Timescale's tools like PGVector, PGVector Scale, and PGAI Vectorizer, uncovering how they aid developers to build AI-powered systems without the complexity of managing multiple databases. Avthar explains how Postgres seamlessly handles structured and unstructured data, making it the perfect foundation for next-gen AI applications.
Learn how Postgres supports AI-driven use cases across industries like IoT, finance, and crypto, and why its open-source ecosystem is key to fostering collaboration and innovation.
Tune in to discover how Postgres is redefining AI databases, why Timescale’s tools are a game-changer for developers, and what the future holds for AI innovation in the database space.
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(00:00) Introduction to Avthar and Timescale
(02:35) The origins of Timescale and TimescaleDB
(05:06) What makes Postgres unique and reliable
(07:17) Open-source philosophy at Timescale
(12:04) Timescale's early focus on IoT and time series data
(16:17) Applications in finance, crypto, and IoT
(19:03) Postgres in AI: From RAG to semantic search
(22:00) Overcoming scalability challenges with PGVector Scale
(24:33) PGAI Vectorizer: Managing embeddings seamlessly
(28:09) The PGAI suite: Tools for AI developers
(30:33) Vectorization explained: Foundations of AI search
(32:24) LLM integration within Postgres
(35:26) Natural language interfaces and database workflows
(38:11) Structured and unstructured data in Postgres
(41:17) Postgres for everything: Simplifying complexity
(44:52) Timescale’s accessibility for startups and enterprises
(47:46) The power of open source in AI
This episode is sponsored by Oracle.
Oracle Cloud Infrastructure, or OCI is a blazing fast and secure platform for your infrastructure, database, application development, plus all your AI and machine learning workloads. OCI costs 50% less for compute and 80% less for networking. So you’re saving a pile of money. Thousands of businesses have already upgraded to OCI, including MGM Resorts, Specialized Bikes, and Fireworks AI.
Cut your current cloud bill in HALF if you move to OCI now: https://oracle.com/eyeonai
In this episode of the Eye on AI podcast, Jeff Boudier, Head of Product and Growth at Hugging Face, joins Craig Smith to uncover how the platform is empowering AI builders and driving the open-source AI revolution.
With a mission to democratize AI, Jeff walks us through Hugging Face's journey from a chatbot for teens to the leading platform hosting over 1 million public AI models, datasets, and applications. We explore how Hugging Face is bridging the gap between enterprises and open-source innovation, enabling developers to build cutting-edge AI solutions with transparency and collaboration.
Jeff dives deep into Hugging Face’s tools and features, from hosting private and public models to fostering a thriving ecosystem of AI builders. He shares insights on the transformative impact of technologies like Transformers, transfer learning, and no-code solutions that make AI accessible to more creators than ever before.
We also discuss Hugging Face’s latest innovation, ‘Hugs,’ designed to help enterprises seamlessly integrate open-source AI within their infrastructure while retaining full control over their data and models.
Tune in to discover how Hugging Face is shaping the future of AI development, why open-source models are catching up with proprietary ones, and what trends are driving innovation across AI disciplines.
Don’t forget to like, subscribe, and hit the notification bell for more!
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(00:00) Introduction to Jeff Boudier
(02:16) How Hugging Face Empowers AI Builders
(05:26) Transition from Chatbot to Leading AI Platform
(07:07) Hosting AI Models: Public and Private Options
(10:13) What Does Hosting Models on Hugging Face Mean?
(14:22) Hugging Face vs. GitHub: Key Differences
(19:09) Navigating 1 Million Models on the Hugging Face Hub
(22:33) Leaderboards and Filtering AI Models
(25:26) Building Applications with Hugging Face Models
(28:03) AI Innovation: From Code to Model-Driven Development
(30:45) Frameworks for Agentic Systems and Hugging Chat
(35:20) Open Source vs. Proprietary AI: The Future
(40:41) Introducing ‘Hugs’: Open AI for Enterprises
(44:59) The Role of No-Code in AI Development
(47:26) Hugging Face’s Vision
This episode is sponsored by Legal Zoom.
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In this episode of the Eye on AI podcast, we dive into the world of Artificial General Intelligence (AGI) with Ben Goertzel, CEO of SingularityNET and a leading pioneer in AGI development.
Ben shares his vision for building machines that go beyond task-specific capabilities to achieve true, human-like intelligence. He explores how AGI could reshape society, from revolutionizing industries to redefining creativity, learning, and autonomous decision-making.
Throughout the conversation, Ben discusses his unique approach to AGI, which combines decentralized AI systems and blockchain technology to create open, scalable, and ethically aligned AI networks. He explains how his work with SingularityNET aims to democratize AI, making AGI development transparent and accessible while mitigating risks associated with centralized control.
Ben also delves into the philosophical and ethical questions surrounding AGI, offering insights into consciousness, the role of empathy, and the potential for building machines that not only think but also align with humanity’s best values. He shares his thoughts on how decentralized AGI can avoid the narrow, profit-driven goals of traditional AI and instead evolve in ways that benefit society as a whole.
This episode offers a thought-provoking glimpse into the future of AGI, touching on the technical challenges, societal impact, and ethical considerations that come with creating truly intelligent machines.
Ben’s perspective will leave you questioning not only what AGI can achieve, but also how we can guide it toward a positive future.
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(00:00) Introduction to Ben Goertzel
(01:21) Overview of "The Consciousness Explosion"
(02:28) Ben’s Background in AI and AGI
(04:39) Exploring Consciousness and AI
(08:22) Panpsychism and Views on Consciousness
(10:32) The Path to the Singularity
(13:28) Critique of Modern AI Systems
(18:30) Perspectives on Human-Level AI and Creativity
(21:42) Ben’s AGI Paradigm and Approach
(25:39) OpenCog Hyperon and Knowledge Graphs
(31:12) Integrating Perception and Experience in AI
(34:02) Robotics in AGI Development
(35:06) Virtual Learning Environment for AGI
(39:01) Creativity in AI vs. Human Intelligence
(44:21) User Interaction with AGI Systems
(48:22) Funding AGI Research Through Cryptocurrency
(53:03) Final Thoughts on Compassionate AI
(55:21) How to Get "The Consciousness Explosion" Book
This episode of the Eye on AI podcast is sponsored by JLL.
JLL's AI solutions are transforming the real estate landscape, accelerating growth, streamlining operations and unlocking hidden value in properties and portfolios. From predictive analytics to intelligent automation, JLL is creating smarter buildings, more efficient workplaces and sustainable cities.
To learn more about JLL and AI, visit: jll.com/AI
In this episode of the *Eye on AI* podcast, we explore the world of AI at Google Cloud with Nenshad Bardoliwalla, Director of Product Management for Vertex AI.
Nenshad unpacks the three core layers of Vertex AI: the Model Garden, where users can access and evaluate a diverse range of models; the Model Builder, which supports model fine-tuning and prompt optimization; and the Agent Builder, designed to develop AI agents that can perform complex, goal-oriented tasks.
He shares insights into model evaluation strategies, the role of Google’s Tensor Processing Units (TPUs) in scaling AI infrastructure, and how enterprises can choose the right models based on performance, cost, and regulatory requirements.
Nenshad also delves into the challenges and opportunities of AI prompt optimization, highlighting Google’s approach to ensuring consistent outputs across different models. He discusses the ethical considerations in AI design, emphasizing the need for human oversight and clear guardrails to maintain safety.
Whether you’re in AI, tech, or curious about AI's potential impact, this episode is packed with insights on next-gen AI deployment.
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(00:00) Introduction to Nenshad Bardoliwalla & Vertex AI
(01:52) Overview of Vertex AI's Three Core Layers
(05:35) Nenshad's Journey to Google Cloud
(06:36) Choosing the Right AI Model
(08:00) Google’s AI Infrastructure & Tensor Processing Units (TPUs)
(10:15) Model Builder: Fine-Tuning & Prompt Optimization
(12:11) Agent Builder: Building AI Agents with Tools & Planning
(17:57) Model Evaluation & Prompt Management
(21:23) Generative AI for Business Analysts
(23:24) AI Model Modality & Use Case Selection
(25:23) Popularity Distribution of AI Models
(28:18) Prompt Optimization Tools
(34:20) Building AI Agents: Real-World Use Cases & Ethical Safeguards
(40:13) The Capabilities & Limitations of AI Agents
(45:48) TPU vs. GPU
(50:33) Future of AI at Google Cloud
This episode of Eye on AI is sponsored by Citrusx.
Navigating the complexities of AI risk management? Citrusx has you covered. Their innovative platform helps you make better business decisions and achieve reliable AI outcomes while staying compliant with regulatory standards. Citrusx enables you to manage AI risks effortlessly, connecting all stakeholders and providing continuous validation. Their solution can detect and mitigate vulnerabilities, biases, and errors, ensuring the accuracy, robustness, and compliance of AI models
Visit https://email.citrusx.ai/eyeonai to book your free demo today!
In this episode of the Eye on AI podcast, we dive into process intelligence with Manuel Haug, Field CTO at Celonis.
Manuel shares how process mining is transforming business operations by connecting directly to digital systems to map workflows, optimize processes, and boost efficiency. He explains how Celonis builds digital twins of business processes, allowing companies to visualize and resolve inefficiencies with data-driven insights.
Manuel also explores the role of AI in process optimization, discussing the integration of generative AI and AI agents in Celonis. From automating repetitive tasks to enabling strategic decision-making, Manuel details how AI agents can enhance workflows, reduce costs, and deliver measurable productivity gains across industries.
Tune in to learn how AI agents are evolving, the potential of process intelligence graphs, and how Celonis is pioneering the future of autonomous enterprises.
Whether you're in business, tech, or curious about the impact of AI, this episode offers valuable insights into next-gen process optimization.
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(00:00) Introduction to Manuel Haug & Celonis
(01:07) Understanding Process Intelligence
(07:14) Integrating AI into Process Mining
(12:12) Generative AI’s Role in Process Optimization
(15:18) Challenges of Large-Scale Process Integration
(20:24) Role of AI Agents in Process Automation
(23:43) AI Maturity & Implementation in Enterprises
(27:23) Real-Life AI Agent Examples
(30:47) Building and Integrating AI Agents
(34:53) Future of AI Agents in Enterprises
(37:56) Introducing the Process Intelligence Graph
(39:20) Addressing Data Privacy Concerns
This episode is sponsored by RapidSOS. Close the safety gap and transform your emergency response with RapidSOS.
Visit https://rapidsos.com/eyeonai/ today to learn how AI-powered safety can protect your people and boost your bottom line.
In this episode of the Eye on AI podcast, we dive deep into the world of AI agents with Ece Kamar, VP of Research and Managing Director of AI Frontiers Lab at Microsoft.
Ece shares her unique insights on the future of AI, discussing how AI agents are reshaping the way we interact with technology and perform tasks.
Throughout the episode, Ece explains the groundbreaking potential of AI agents, describing how they act as autonomous entities that can perceive, learn, and carry out complex tasks in real time. She discusses the revolutionary shift from traditional AI models to agentic workflows, highlighting how multi-agent systems like Microsoft's AutoGen are creating scalable solutions for industries and everyday life. Ece also shares her thoughts on building responsible AI, touching on the ethical challenges and safety concerns that come with the rise of autonomous agents.
We explore how multi-agent systems can scale to millions of agents, and how they are transforming enterprises by automating complex workflows, personalizing customer experiences, and pushing the boundaries of AI development. Ece’s perspective on the future of AI in scientific discovery, as well as her work in responsible AI, offers a thought-provoking glimpse into what lies ahead.
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(00:00) Preview and Introduction
(03:11) What Are AI Agents?
(04:43) Building Responsible AI at Microsoft
(10:55) The Rise of Agentic Workflows
(12:30) Multi-Agent Systems and AutoGen
(18:04) Scaling Multi-Agent Systems
(20:22) The Creation and Evolution of AutoGen
(23:07) Real-World Applications of AutoGen
(25:52) Large-Scale Simulations with AI Agents
(27:36) The Role of AI Agents in Scientific Discovery
(31:20) AI Agents and Complex Reasoning
(36:49) Challenges in Defining Agent Boundaries
(39:12) The Risk of Agents Interacting with Each Other
(43:59) Building Trustworthy and Safe AI Agents
(48:44) Learning from Human Factors in Automation
(50:50) Why Speed and Coordination Matter in AI Development
(55:08) The Future of AI Agents in Enterprises
(57:47) Low-Code/No-Code Development for AI Agents
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
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In this episode of the Eye on AI podcast, we sit down with Mark Surman, President of Mozilla, to explore the future of open-source AI and how Mozilla is leading the charge for privacy, transparency, and ethical technology.
Mark shares Mozilla’s vision for AI, detailing the company’s innovative approach to building trustworthy AI and the launch of Mozilla AI. He explains how Mozilla is working to make AI open, accessible, and secure for everyone—just as it did for the web with Firefox. We also dive into the growing importance of federated learning and AI governance, and how Mozilla Ventures is supporting groundbreaking companies like Flower AI.
Throughout the conversation, Mark discusses the critical need for open-source AI alternatives to proprietary models like OpenAI and Meta’s LLaMA. He outlines the challenges with closed systems and highlights Mozilla’s work in giving users the freedom to choose AI models directly in Firefox.
Mark provides a fascinating look into the future of AI and how open-source technologies can create trillions in economic value while maintaining privacy and inclusivity. He also sheds light on the global race for AI innovation, touching on developments from China and the impact of public AI funding.
Don’t forget to like, subscribe, and hit the notification bell to stay up to date with the latest trends in AI, open-source tech, and machine learning!
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(00:00) Introduction to Mark Surman and Mozilla’s Mission
(02:01) The Evolution of Mozilla: From Firefox to AI
(04:40) Open-Source Movement and Mozilla’s Legacy
(06:58) The Role of Open-Source in AI
(11:06) Advancing Federated Learning and AI Governance
(14:10) Integrating AI Models into Firefox
(16:28) Open vs Closed Models
(22:09) Partnering with Non-Profit AI Labs for Open-Source AI
(25:08) How Meta’s Strategy Compares to OpenAI and Others
(27:58) Global Competition in AI Innovation
(31:17) The Cost of Training AI Models
(33:36) Public AI Funding and the Role of Government
(37:40) The Geopolitics of AI and Open Source
(41:35) Mozilla’s Vision for the Future of AI and Responsible Tech
This episode is sponsored by Speechmatics. Check it out at www.speechmatics.com/realtime
Today, we're joined by Dr. Thomas G. Dietterich, a pioneer in machine learning who recently was honored with the Award for Research Excellence from the International Joint Conference on Artificial Intelligence, one of the top awards for AI researchers.
Dietterich traces the field's progression from early rule-based systems to modern machine learning paradigms and delves into his work on novel category detection and open set problems. He also discusses the evolution of ensemble methods in the context of large language models (LLMs), highlighting the shift from combining many cheap models to more selective approaches with expensive models.
He advocates for a foundation model approach to capture the variability of the world.
Join us for a deep dive into the future of AI, where Thomas explains why the development of novel materials and drugs may have the most transformative impact on our economy. Plus, hear about his latest work on multi-instance learning, weak supervision, and the role of reinforcement learning in real-world applications like wildfire management.
Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest trends and insights in AI and machine learning!
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(00:00) Introduction to Thomas Dietterich's Machine Learning Journey
(02:34) The Early Days of Machine Learning and AI Systems
(04:29) Tackling the Multiple Instance Problem in Drug Design
(05:41) AI in Sustainability
(07:17) The Challenge of Novelty Detection in AI Systems
(08:00) Addressing the Open Set Problem in Cybersecurity and Computer Vision
(09:11) The Evolution of Deep Learning in Computer Vision
(11:21) How Deep Learning Handles Novel Representations
(12:01) Foundation Models and Self-Supervised Learning
(14:11) Vision Transformers vs. Convolutional Neural Networks
(16:05) The Role of Multi-Instance Learning in Weakly Labeled Data
(18:36) Ensemble Learning and Deep Networks in Machine Learning
(20:33) The Future of AI: Large Language Models and Their Applications
(23:51) Symbolic Regression and AI’s Role in Scientific Discovery
(34:44) AI in Wildfire Management: Using Reinforcement Learning
(39:32) AI-Driven Problem Formulation and Optimization in Industry
(41:30) The Future of AI Reasoning Systems and Problem Solving
(45:03) The Limits of Large Language Models in Scientific Research
(50:12) Closing Thoughts: Open Challenges and Opportunities in AI
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. NetSuite is offering a one-of-a-kind flexible financing program.
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In this episode of the Eye on AI podcast, we dive into the world of quantum consciousness with Stuart Hameroff, a pioneer in the field of consciousness studies and co-developer of the controversial Orch OR theory.
Stuart Hameroff takes us on a journey through the intersection of quantum mechanics and the human mind, explaining how microtubules within neurons could be the key to unlocking the mysteries of consciousness.
Stuart delves into his work with physicist Roger Penrose, where they propose that consciousness arises from quantum processes in the brain, deeply embedded in the fabric of spacetime itself. We explore how this theory challenges mainstream neuroscience, which often reduces the mind to simple neural activity, and instead suggests that consciousness may have a profound connection to the universe's underlying structure.
Throughout the conversation, Stuart addresses the debate over AI consciousness, asserting that true conscious experience cannot arise from mere computation but requires quantum processes. He shares insights on the latest experiments in anesthesia and quantum biology, offering a fresh perspective on how the brain might function on a deeper, quantum level.
Join us as we unpack the groundbreaking Orch OR theory and what it could mean for the future of science, technology, and our understanding of reality.
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(00:00) Preview
(03:26) Consciousness and Dualism vs. Materialism
(04:51) Anesthesia and Consciousness: Hameroff's Perspective
(07:30) Roger Penrose's Perspective on Consciousness
(09:51) Penrose's Explanation of Quantum Superposition
(12:52) The Collapse of Quantum Superposition and Consciousness
(14:41) Microtubules and Their Role in Consciousness
(17:08) Critique of Current Neuroscience Approaches
(22:28) Discovering the Microtubule’s Role in Information Processing
(26:08) Microtubules as Cellular Automata
(28:48) The Role of Frohlich Coherence in Quantum Biology
(31:27) Meeting Roger Penrose and Connecting with His Work
(33:52) Collaboration with Penrose: Developing the Theory
(37:05) Challenges and Criticisms of the Theory
(43:06) Advances in Quantum Consciousness Research
(46:18) Hierarchical Models in the Brain
(51:10) Entanglement and Consciousness
(55:03) The Mystery of Anesthesia’s Selective Impact on Consciousness
(57:07) Quantum Effects and Anesthesia’s Mechanism
(01:00:22) The Search for Anesthesia’s Target Protein
(01:04:30) Experimental Evidence for Quantum Effects in Biology
(01:09:33) Consciousness as a Quantum Physical Effect
This episode is sponsored by Bloomreach. Bloomreach is a cloud-based e-commerce experience platform and B2B service specializing in marketing automation, product discovery, and content management systems.
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In this episode of the Eye on AI podcast, we sit down with Pedro Domingos, professor of computer science and author of The Master Algorithm and 2040, to dive deep into the future of artificial intelligence, machine learning, and AI governance.
Pedro shares his expertise in AI, offering a unique perspective on the real dangers and potential of AI, far from the apocalyptic fears of superintelligence taking over. We explore his satirical novel, 2040, where an AI candidate for president—Prezibot—raises questions about control, democracy, and the flaws in both AI systems and human decision-makers.
Throughout the episode, Pedro sheds light on Silicon Valley’s utopian dreams clashing with its dystopian realities, highlighting the contrast between tech innovation and societal challenges like homelessness. He discusses how AI has already integrated into our daily lives, from recommendation systems to decision-making tools, and what this means for the future.
We also unpack the ongoing debate around AI safety, the limits of current AI models like ChatGPT, and why he believes AI is more of a tool to amplify human intelligence rather than an existential threat. Pedro offers his insights into the future of AI development, focusing on how symbolic AI and neural networks could pave the way for more reliable and intelligent systems.
Don’t forget to like, subscribe, and hit the notification bell to stay updated on the latest insights into AI, machine learning, and tech culture.
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(00:00) Preview and Introduction
(01:06) Pedro's Background and Contributions to AI
(03:36) The Satirical Take on AI in '2040'
(05:42) AI Safety Debate: Geoffrey Hinton vs. Yann LeCun
(08:06) Debunking AI's Real Risks
(12:45) Satirical Elements in '2040': HappyNet and Prezibot
(17:57) AI as a Decision-Making Tool: Potential and Risks
(22:55) The Limits of AI as an Arbiter of Truth
(27:35) Crowdsourced AI: PreziBot 2.0 and Real-Time Decision Making
(29:54) AI Governance and the Kill Switch Debate
(37:42) Integrating AI into Society: Challenges and Optimism
(47:11) Pedro's Current Research and Future of AI
(55:17) Scaling AI and the Future of Reinforcement Learning
In this episode of the Eye on AI podcast, Craig Smith sits down with Bill Moore BCGX to explore the development of Gene, an AI-powered co-host transforming the way we engage with conversational AI.
Bill walks us through the journey of creating Gene, a real-time conversational agent built to interact seamlessly with human hosts. He shares insights into the technical challenges they faced, from improving latency to expanding context windows, and how Speechmatics' cutting-edge speech-to-text technology helped achieve over 90% accuracy in real-time.
We dive deep into the ethics of AI, particularly gender representation, as the conversation touches on why assigning gender to AI assistants can reinforce outdated stereotypes. Gene, as a gender-neutral conversational AI, challenges these norms, providing a clear distinction between human-like interaction and AI-driven dialogue.
Join us for an in-depth discussion on the future of AI in media, the balance between human creativity and AI’s analytical power, and the ethical considerations every company should be mindful of when integrating AI into their operations.
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(00:00) Introduction to Gene: BCG's Conversational AI
(02:19) Bill Moore’s Background
(04:22) Early Challenges in Building Real-Time AI
(07:20) Technical Aspects: Prompting and Configuring Gene
(09:28) The Use of Vector Databases and Sparse Priming
(12:01) How Gene Handles Long Conversations
(14:46) Building Conversational AI
(19:07) Gene Introduces Itself: AI as a Podcast Co-Host
(22:00) The Ethics of AI
(29:35) Should AI Have a Physical Representation?
(32:05) AI and Children: Nurturing Healthy Interactions
(36:16) Adoption of Conversational AI in Businesses
(38:11) Ethical Considerations for AI in the Future
This episode is sponsored by Shopify.
Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
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In this episode of the Eye on AI podcast, Craig Smith sits down with Michael Martin, CEO of RapidSOS, to explore how AI and connected devices are aiding emergency response and public safety.
With billions of sensor feeds from over 540 million devices—including wearables, vehicles, and security systems—RapidSOS integrates life-saving data to provide real-time support for 911 and first responders across the U.S. and beyond. Michael shares how their platform is reducing response times, improving accuracy, and transforming the way emergencies are handled by public safety agencies.
We dive deep into RapidSOS’s AI-powered platform, which fuses human and machine intelligence to deliver faster, more effective emergency responses. Michael also discusses the challenges of scaling such technology globally, the role of AI in predictive emergency management, and the importance of integrating these solutions into legacy systems used by first responders.
Whether it’s saving lives through faster 911 responses, preventing emergencies before they happen, or leveraging AI to enhance public safety, this episode offers a compelling look at the future of emergency services. Join us to uncover how technology is reshaping public safety and emergency response on a global scale.
Don’t forget to like, subscribe, and hit the notification bell for more cutting-edge discussions on AI, emergency services, and technology innovation!
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(00:00) Preview
(01:58) RapidSOS and Michael Martin’s Journey
(06:39) Integration w/ Wearable Devices and Home Systems
(11:59) RapidSOS’s Use Cases
(23:12) RapidSOS’ Foundational Models
(31:31) How RapidSOS Handles Data
(36:11) How RapidSOS Aids Public Safety
(49:56) Is RapidSOS Integrated into Hospitals?
(53:00) EmergencyProfile.org Role In Helping First Responders
(55:36) The Future of Public Safety with AI and RapidSOS
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
In this episode of the Eye on AI podcast, Craig Smith sits down with Noa Srebrnik from Citrusx to explore how AI is transforming risk management and compliance in high-risk industries like finance and insurance.
With a background spanning regulation, risk, and technology, Noa guides us through Citrusx’s innovative approach to enabling organizations to leverage AI responsibly while adhering to complex regulatory environments.
We dive deep into Citrusx’s AI platform, designed to validate, monitor, and explain AI models, ensuring transparency, fairness, and compliance. Noa explains how their proprietary synthetic data technology identifies hidden risks, allowing companies to confidently scale AI solutions across different use cases without compromising governance.
We also discuss the evolving regulatory landscape, including the challenges of navigating fragmented AI regulations in the U.S. and the EU AI Act’s influence on high-risk sectors.
Join us as we uncover how AI can drive innovation while maintaining regulatory accountability and why risk management is crucial for the future of AI in finance and beyond.
Don’t forget to like, subscribe, and hit the notification bell for more in-depth discussions on AI, regulation, and risk management!
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This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
In this episode of the Eye on AI podcast, Craig Smith sits down with Krishna Rangasayee, CEO of SiMa.ai, to explore the innovations in AI at the edge and how embedded systems are transforming industries like robotics, automotive, and industrial automation.
Krishna brings over 30 years of experience in software and silicon design, leading us through SiMa.ai's vision of disrupting edge computing with their Machine Learning System on Chip (MLSoC).
We dive deep into how SiMa.ai’s chips are designed to accelerate AI workloads at the edge, providing unmatched performance and efficiency compared to cloud-based solutions.
We also discuss the future of AI hardware, including the role of open-source platforms, the challenges of scaling AI in embedded systems, and why the edge market is poised to outgrow the cloud in the coming years.
Krishna shares his insights on the importance of AI software architecture, how SiMa.ai’s platform simplifies integration for developers, and the emerging potential of neuromorphic and quantum computing.
Join us as we delve into the next big AI gold rush, the edge market, and learn why AI-powered edge devices will reshape the way industries operate.
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(00:00) Preview and Introduction
(02:13) SiMa.ai's Focus on Chip Design for the Edge
(05:38) How is SiMa.ai Different from NVIDIA’s CUDA?
(08:29) The Evolution of Chip Architecture
(11:50) AI’s Move to the Edge Market?
(19:19) Industries Driving Demand for SiMa.ai's Technology
(21:25) How Do Edge Applications Work?
(25:09) Chips Design for Edge Devices
(33:01) SiMa.ai Scaling Plans
(36:12) What is SiMa.ai Focusing On in the Future?
(40:30) SiMa.ai’s Fundraising Journey
(42:57) Hiring and Retaining Top Talent in the Industry
(46:01) The Future of Chip Technology
This episode is sponsored by Bloomreach.
Bloomreach is a cloud-based e-commerce experience platform and B2B service specializing in marketing automation, product discovery, and content management systems.
Check out Bloomreach: https://www.bloomreach.com
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In this episode of the Eye on AI podcast, we sit down with Randall Degges, Head of Developer Relations and Security at Snyk, to uncover the impact of AI on cybersecurity and software development.
Randall shares his 20+ years of experience as a software developer and security expert, leading us through Snyk's innovative approach to developer security. We dive into how Snyk is changing vulnerability detection and code generation by leveraging a hybrid AI model—combining symbolic AI for accurate detection and generative AI for smart fixes.
We explore the challenges and opportunities of using AI in code security, discussing whether AI-generated code can ever fully replace human coders or if it's best suited as a powerful tool in a developer's arsenal. Randall also addresses the risks of AI hallucinations in code generation and how Snyk mitigates these through rigorous testing and validation.
Join us as we discuss the future of coding, the role of AI in software development, and how developers can stay ahead in this rapidly evolving landscape.
Don’t forget to like, subscribe, and hit the notification bell for more expert insights into the latest AI and cybersecurity trends.
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(00:00) Preview and Intro
(00:34) Randall Degges Background
(01:33) The Role of AI in Security at Snyk
(03:28) Symbolic vs. Generative AI in Code Security
(04:57) How Snyk Uses Rule-Based AI for Detection
(06:48) Challenges with AI-Generated Code Fixes
(09:08) The Future of AI in Code Generation
(11:56) Integrating AI with Developer Tools
(16:06) Risks of AI-Generated Code and Internet Saturation
(22:25) The Hybrid AI Approach for Code Security
(26:31) Future of AI and Its Impact on Developers
(30:02) Snyk's Integration with IDEs and Research Initiatives
(33:48) Autonomous Fixes and the Future of AI in Development
(41:04) DeepCode AI Fix Engine and Snyk’s ID Plugin
(46:38) Will AI Replace Developers?
(50:16) AI Readiness Report Insights
(52:59) Tech Layoffs and Opportunities in AI
In this episode of the Eye on AI podcast, we sit down with Peter Guagenti, President and Chief Marketing Officer at Tabnine, to explore the role of AI in software development.
Peter takes us through his journey from web developer and engineering lead to leading Tabnine, a pioneer of AI code assistance.
We delve into the innovative ways Tabnine is pushing the boundaries of AI, from enhancing code generation to ensuring privacy with its Protected Model—offering enterprises fully private AI solutions tailored to their specific needs. Peter discusses how Tabnine is addressing the challenges of fit-to-purpose AI, making AI tools more context-aware and personalized to the workflows of individual engineering teams.
Peter also sheds light on the future of AI in software development, addressing the pressing question: Can AI truly replace developers, or is it destined to be a powerful collaborator?
Learn how AI can elevate software engineering teams, helping them overcome the repetitive tasks that slow down progress and focus on the creative aspects that push the industry forward.
Don’t forget to like, subscribe, and hit the notification bell for more in-depth conversations on the latest AI advancements.
This episode of Eye on AI is sponsored by BetterHelp.
If you’re thinking of starting therapy, give BetterHelp a try. It’s entirely online. Designed to be convenient, flexible, and suited to your schedule. Just fill out a brief questionnaire to get matched with a licensed therapist, and switch therapists any time for no additional charge.
Visit https://www.betterhelp.com/eyeonai today to get 10% off your first month.
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(00:00) Preview and Introduction
(00:38) Peter Guagenti's Background
(01:20) Tabnine’s Origins
(03:49) Innovating in AI Code Assistance
(05:10) The Path to Autonomous Code Generation
(07:49) Human Oversight in Autonomous AI
(10:17) Misconceptions About AI Replacing Engineers
(14:15) Future of Software Development with AI
(17:04) Autonomous JIRA Tool and Broader Applications
(22:36) Leveraging Vector Databases for Context
(27:34) Balancing Contextual Data for AI
(29:54) Expanding Generative AI Use Cases
(34:16) Ensuring Code Quality with AI
(37:17) Curating Quality Data for AI Models
(41:17) The Need for Skilled Coders in AI
(42:59) Future of Generative AI Beyond LLMs
(47:00) Case Studies: Tabnine’s Impact on Productivity
(51:49) Conclusion: Building Trust in AI Technology
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In this episode of the Eye on AI podcast, we sit down with Xun Wang, Chief Technology Officer at Bloomreach, to explore the power of AI in the world of e-commerce.
Xun takes us on a journey through his career, from his early days at NVIDIA, where he played a pivotal role in the evolution of parallel computing and GPU technology, to his current leadership at Bloomreach, a company at the forefront of AI-driven commerce solutions.
He shares how Bloomreach is disrupting the e-commerce landscape with its AI-powered platform, helping brands and retailers enhance customer experiences through personalized search and recommendations.
We dive deep into the technical side of Bloomreach's AI services, including Loomi AI, which integrates various AI capabilities such as search, recommendations, and segmentation. Xun explains how these services work together to deliver highly personalized shopping experiences that boost engagement and conversion rates.
Xun sheds light on the company’s innovative use of generative AI and large language models to improve search relevance and personalization, offering listeners a glimpse into the future of e-commerce.
Tune in to discover how Bloomreach is leveraging cutting-edge AI technologies like two-tower neural networks and their Customer Data Engine (CDE) to redefine the online shopping experience.
Join us as we explore the intersection of AI and commerce, and learn how Bloomreach is setting new standards for personalized online experiences.
Don’t forget to like, subscribe, and hit the notification bell for more deep dives into the latest AI innovations.
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
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In this episode of the Eye on AI podcast, we explore the cutting-edge intersection of AI and biotechnology with Raphael Townshend, founder and CEO of Atomic AI.
Raphael delves into the revolutionary potential of AI in RNA drug discovery, highlighting Atomic AI's innovative approach. He shares his journey from studying electrical engineering and computer science at UC Berkeley to developing advanced AI models for understanding RNA structures, analogous to DeepMind's AlphaFold for proteins.
We dive deep into the intricacies of RNA's role in the human genome and its untapped potential in treating diseases previously considered undruggable. Raphael explains how Atomic AI's core model, Atom 1, is designed to predict RNA shapes with unprecedented accuracy, enabling the design of new drugs that target RNA instead of proteins. He discusses the significance of RNA in the context of mRNA vaccines, particularly the COVID-19 vaccine, and the challenges of making these vaccines more stable and accessible.
The conversation also covers the technical aspects of using AI, including transformer-based models and in-house data generation, to enhance RNA drug discovery. Raphael shares insights into the company's progress, from cell testing to upcoming animal trials, and the broader implications of integrating AI in biotechnology.
Join us as we uncover the future of RNA-based therapies, the innovative use of AI in drug discovery, and the groundbreaking advancements that could transform the landscape of medicine. Don't forget to like, subscribe, and hit the notification bell for more expert insights into the latest AI innovations.
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In this episode of the Eye on AI podcast, we dive into the world of AI forecasting with Danny Halawi, a PhD student at UC Berkeley.
Danny shares his groundbreaking research on using large language models (LLMs) to predict future events with accuracy, rivaling human forecasters and prediction markets.
Danny recounts his journey from studying computer security and fraud detection to exploring the potential of AI in forecasting geopolitical events and beyond. He introduces us to the sophisticated architecture of his AI system, which leverages real-time data from prediction markets and advanced machine learning techniques to generate reliable forecasts.
We explore the complexities of judgmental forecasting versus time series forecasting and how AI can enhance decision-making in various fields. Danny discusses the challenges of training AI models for high-stakes predictions, the role of super forecasters, and the fascinating dynamics of prediction markets. He also sheds light on the ethical considerations and future possibilities of integrating AI into our decision-making processes.
Join us as we delve into the future of AI forecasting, the potential of superhuman predictions, and the exciting developments that could reshape our understanding of the future. Don't forget to like, subscribe, and hit the notification bell for more expert insights into the latest AI innovations.
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(01:28) The Importance of AI
(02:50) Danny's Background and Interest in AI
(04:01) Automated AI Forecasting and Safety Implications
(07:34) Judgmental Forecasting Explained
(11:01) Accuracy and Challenges in Prediction Markets
(16:01) Aggregating Predictions for Better Accuracy
(19:25) Data Collection and Model Accuracy
(23:18) Improving Model Accuracy Over Time
(25:31) Data Sources and Model Training
(29:20) Summarizing Information for Predictions
(34:08) Potential of Reinforcement Learning in Forecasting
(37:50) Automating Information Collection and Summarization
(39:01) Training the Model for Accurate Predictions
(45:04) Challenges with Uncertain Predictions
(50:14) Potential Applications and Future Directions
(52:26) The Future of AI Forecasting and Its Impact
In this episode of the Eye on AI podcast, we explore the forefront of voice-powered AI technology with Trevor Back, Chief Product Officer at Speechmatics. Discover how Speechmatics is pushing the boundaries of speech recognition and conversational AI with their latest innovation, Flow.
Trevor shares his journey from a background in computational astrophysics to becoming a key figure in AI at DeepMind and now Speechmatics. He delves into the development and potential of Flow, a groundbreaking tool combining automatic speech recognition (ASR), large language models (LLMs), and text-to-speech synthesis, aimed at creating seamless and responsive voice interactions.
We explore the wide-ranging applications of Speechmatics' technology across industries, including media, call centers, and education. Trevor discusses the challenges of achieving high accuracy in speech recognition, especially in diverse and noisy environments, and how Speechmatics addresses these challenges with their unique approach to training models.
Listen in as we uncover the intricacies of handling multiple languages, improving diarization, and the future goals of understanding complex audio cues like emotion and sarcasm. Learn about the company's vision for integrating voice technology into everyday products, making technology more accessible and user-friendly.
Don't miss this insightful conversation on the future of voice technology, AI in business, and its role in the evolving landscape of AI. Like, subscribe, and hit the notification bell for more expert discussions on cutting-edge advancements in AI.
This episode is sponsored by Shopify.
Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
Checkout Speechmatics, the most accurate AI speech technology - with AI transcription & real-time translation components.: https://www.speechmatics.com/
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Craig Smith Twitter: https://twitter.com/craigss
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(00:00) Introduction and Background
(01:49) Trevor Back's Journey into AI
(04:02) DeepMind and Early AI Applications
(07:30) Speechmatics' Mission and Focus
(12:06) Key Applications of Speechmatics Technology
(14:25) Achieving High Accuracy and Low Latency
(17:52) Language Coverage and Challenges
(21:27) Future of Voice Technology and AGI
(24:52) Integrating Large Language Models
(27:31) Handling Multiple Voices and Diarization
(29:32) Real-world Applications and Challenges
(35:20) Demonstration of Flow and Capabilities
(41:14) Endpoint Prediction and Interruption
(43:53) Real-time Interactions and Future Prospects
(45:34) Launch Event and Future Plans
(50:13) New Language Releases and Compliance
In this episode of the Eye on AI podcast, we delve into the power of AI in business and data science and data management with Shub Bhowmick, CEO and co-founder of Tredence.
Explore how Tredence is revolutionizing industries by integrating AI and data science to drive business outcomes. Shub shares his journey from management consulting to leading a team of 2,500 data scientists and engineers. Learn how Tredence is supercharging Fortune 200 clients across retail, consumer packaged goods (CPG), financial services, healthcare, and more, with custom AI solutions.
We dive deep into the challenges and opportunities in leveraging AI, particularly in the CPG sector, and how Tredence addresses data silos, enhances data quality, and implements real-time data processing. Shub also discusses the implementation of generative AI, detailing the company's journey from foundational models to enterprise adoption and responsible AI practices.
Discover Tredence's Gen AI as a service platform, designed to help enterprises navigate the complexities of AI integration, optimize infrastructure, and unlock business value through innovative AI solutions. Shub highlights real-world applications of AI, such as demand forecasting and predictive analytics, demonstrating how these technologies can significantly reduce costs and improve efficiency.
Gain insights into Tredence's growth strategy, including their expansion into new verticals, service lines, and geographies. Shub emphasizes the importance of a multidisciplinary approach, combining domain expertise with cutting-edge technology to deliver customized, impactful AI solutions.
Don't miss out on this insightful conversation. Like, subscribe, and hit the notification bell for more expert discussions on the technologies driving the AI revolution
This episode of Eye on AI is sponsored by BetterHelp.
If you’re thinking of starting therapy, give BetterHelp a try. It’s entirely online. Designed to be convenient, flexible, and suited to your schedule. Just fill out a brief questionnaire to get matched with a licensed therapist, and switch therapists any time for no additional charge.
Visit https://www.betterhelp.com/eyeonai today to get 10% off your first month.
This episode is sponsored by Shopify.
Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(02:42) Introducing Shub Bhowmick, CEO of Tredence
(03:29) What Tredence Does and Their Clients
(04:32) Why Tredence Focuses on Consumer Packaged Goods
(06:18) AI Transformation Example in Retail
(09:24) Building a Solid Data Foundation
(10:42) Improving Reporting with Real-Time Data
(11:44) Starting the AI and Data Science Journey
(13:32) How Tredence Uses Generative AI
(14:10) Stages of Implementing Generative AI
(19:09) Applying AI Across Different Industries
(23:43) Overview of Gen AI as a Service Platform
(25:37) Features and Benefits of the Platform
(28:42) How Gen AI is Integrated into Businesses
(33:02) Tredence's Unique Approach to AI Solutions
(36:08) Importance of Domain-Specific AI Solutions
(40:42) Tredence's Growth and Expansion Plans
(47:57) Size and Reach of Tredence
(50:01) Competing in the AI Market
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
In this episode of the Eye on AI podcast, join us as we sit down with Dr. Sethuraman Panchanathan, Director of the National Science Foundation (NSF), where we explore the impact of AI on research and innovation.
Dr. Panchanathan delves into his journey from PhD student in machine learning to leading one of the most pivotal science organizations in the world. With a background in vector quantization and neural networks, his extensive experience positions him at the forefront of AI advancements.
Discover how the NSF is revolutionizing AI through strategic investments and initiatives like the AI Institutes and the National AI Research Resource (NAIR). Dr. Panchanathan explains how these programs democratize access to cutting-edge computational resources, fostering innovation across diverse regions and disciplines.
Learn about NSF’s $828 million investment in AI for 2023 and the agency’s unique approach to allocating funds across various scientific domains. Dr. Panchanathan shares insights on the importance of partnerships with industries, educational institutions, and international bodies, emphasizing the need for a collaborative ecosystem to drive AI progress.
He also touches on the role of AI in addressing societal challenges and the ethical considerations in AI development.
Tune in to understand how NSF is leading the charge in AI research and development, ensuring the US remains at the cutting edge of technological innovation.
Don't forget to like, subscribe, and hit the notification bell for more deep dives into the technologies shaping our world.
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This episode is sponsored by Vanta, The security and compliance platform trusted by more than 7,000 customers.With Vanta, you can unify your security program management with a built-in risk register and reporting, and proactively manage security reviews with AI-powered security questionnaires.
Listeners get $1,000 off Vanta at https://vanta.com/eyeonai
(00:00) Preview and Introduction
(02:31) Dr. Panchanathan’s Background and Path to NSF
(05:45) Overview of NSF's Funding and Research Initiatives
(08:17) AI Funding and Allocation Strategy at NSF
(11:57) Importance of AI Institutes and Collaborative Efforts
(14:55) Democratizing AI Access through NAIR
(20:04) NAIR Pilot Projects and Partnerships
(24:23) Accessing Compute Resources via NAIR
(27:43) Scaling NAIR and Future Projections
(30:14) Broader NSF Funding Allocation and Strategic Planning
(33:34) Utilizing AI for NSF Operations
(37:09) International Collaborations and Comparisons
(42:05) Staying Ahead in Global Research Investments
(46:03) Focus on Innovation and Talent Development
(48:40) Regional Innovation Engines and Future Plans for NSF
This episode is sponsored by SysAid.
Get 20% off SysAid Copilot using this link: https://www.sysaid.com/lp/sysaid-copilot-s?utm_source=youtube&utm_medium=cpc&utm_campaign=short-craig
In this episode of the Eye on AI podcast, join us as we delve into the cutting-edge world of AI and high-performance computing with Brian Spears, Director of the AI Innovation Incubator at Lawrence Livermore National Laboratory.
Brian shares his experience in driving AI into national security science and managing the nation’s nuclear stockpile. With a PhD in mechanical engineering, his expertise spans nonlinear dynamical systems and high-dimensional topology, making him uniquely positioned to lead groundbreaking projects in fusion ignition and AI integration.
Discover how Lawrence Livermore National Laboratory achieved fusion ignition for the first time, harnessing the power of AI to elevate simulation models with precise experimental data. Brian explains how this approach is paving the way for commercially viable fusion energy and advancing stockpile stewardship.
Explore the relationship between high-performance computing and AI as Brian discusses the Department of Energy's FAST initiative. Brian also touches on the importance of public-private partnerships, ethical considerations in AI development, and the future potential of quantum computing.
Tune in to understand how the US is leading the global race in AI and computing technology, setting the stage for unprecedented advancements in science and security.
Don't forget to like, subscribe, and hit the notification bell for more insights into the technologies driving the AI revolution.
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Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview
(01:52) Introducing Brian Spears
(03:14) Fusion Ignition and AI Integration
(06:00) Predictive Models and Experimental Data
(08:05) Challenges in Fusion Energy
(12:03) Inertial Confinement Fusion Explained
(14:12) Future of Fusion Energy
(17:15) US Leadership in AI and Computing
(19:22) Global AI Competition
(22:33) High-Performance Computing Infrastructure
(26:08) DOE’s FAST Initiative
(28:55) Transformational AI Applications
(34:01) AI Ethics and Safety
(36:24) Scientific Models and Large Language Models
(39:30) 3D Molecular Modeling
(42:47) National AI Research Resource (NAR)
(45:18) Recruitment Challenges in AI
(48:09) Comparison with China
(52:30) DOE’s Role and Future Vision
(54:19) Quantum Computing
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
In this episode of the Eye on AI podcast, join us as we sit down with Avi Kedmi, CEO of SysAid, to explore the transformative power of AI in IT service management.
Avi shares his journey from the high-tech industry to leading SysAid, a pioneer in IT service management solutions. With over 20 years of experience, Avi discusses how SysAid is leveraging AI to revolutionize service management through predictive modeling and generative AI.
Discover how SysAid's AI-driven solutions reduce ticket volumes and enhance customer satisfaction by automating IT services. Avi provides an inside look at SysAid's AI Co-Pilot, a comprehensive AI suite designed to optimize IT service delivery and support.
Explore the unique features of SysAid's platform, including its ease of use, no-code interface, and seamless integration with existing IT systems. Avi explains how SysAid's AI capabilities enable real-time data processing and decision-making, improving efficiency and response times.
Learn about the future of AI in IT service management, as Avi delves into the potential for AI-driven automation and the development of smarter IT solutions. He also highlights SysAid's strategic approach to staying competitive in a rapidly evolving industry.
Tune in to understand how SysAid is setting new standards in AI-powered IT service management and what this means for the future of IT support.
Don't forget to like, subscribe, and hit the notification bell for more insights into the technologies driving the AI revolution.
Get 20% off SysAid Copilot using this link: https://www.sysaid.com/lp/sysaid-copilot-s?utm_source=youtube&utm_medium=cpc&utm_campaign=short-craig
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
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(00:00) Preview and Introduction
(02:38) Avi Kedmi's Background
(04:37) SysAid's Role in the ITSM Market
(06:39) SysAid Co-Pilot: AI-Powered IT Solutions
(08:31) Importance of Generative AI in Service Management
(12:23) Conversational Interfaces and Large Language Models
(14:20) AI Applications in IT Service Management
(21:16) Automated Pre-Processing and Document Handling
(25:33) AI's Role in Reducing Ticket Volumes
(28:56) Ensuring Accuracy and Relevance
(30:46) Cross-Channel Accuracy Management
(34:03) SysAid’s Mid-Market Focus and Strategic Positioning
(37:52) Market Segmentation and Competitive Advantage
(39:17) Digitization and Future Market Trends
(43:54) Challenges with Knowledge Base Maintenance
(46:48) Future Developments and Industry Trends
(47:39) SysAid's Vision for AI and IT Service Management
This episode is sponsored by TrialKey.ai, the market leader AI-driven clinical trial design optimization, and predictor that improves trial design and execution. With over 90% accuracy based on precision/recall, TrialKey.ai predicts the success of clinical trials more precisely than any other tool on the market.
Maximize clinical trial success while minimizing costs – book a demo at https://trialkey.ai/ or sign up for free!
In this episode of the Eye on AI podcast, join us as we sit down with Mrinal Manohar, CEO of Casper Labs, to explore the intersection of blockchain technology and AI governance.
Mrinal delves into his journey from Wall Street to founding Casper Labs, a leading enterprise-grade blockchain infrastructure company. With a strong background in computer science and experience in AI governance, Mrinal shares how Casper Labs is setting new standards in AI compliance and security.
Discover how Casper Labs uses blockchain to create tamper-proof, auditable records, ensuring the integrity and security of AI systems. Mrinal explains the innovative use of blockchain for multi-party access and version control, highlighting the company's collaboration with IBM to develop cutting-edge solutions integrated into the Watson X platform.
Explore the implications of upcoming AI legislation, such as the EU AI Act, and how Casper Labs is helping enterprises navigate these regulatory changes. Mrinal provides insights into the challenges and opportunities in AI governance, discussing real-world use cases and the future of secure AI systems.
Learn how Casper Labs is positioning itself ahead of the curve, with technical differentiators and strategic partnerships that set it apart in the industry.
Tune in to understand how Casper Labs is transforming AI compliance and security with blockchain, and what this means for the future of AI.
Don't forget to like, subscribe, and hit the notification bell for more insights into the technologies driving the AI revolution.
Checkout Casper Labs:
Website: https://casperlabs.io/
Twitter/X: https://x.com/Casper_Labs
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(01:37) Overview of Casper Labs
(03:46) Proof of Concept and Collaboration with IBM
(06:58) AI Governance and Compliance Needs
(08:38) Key Components of Blockchain for AI Governance
(10:22) Training Data Integrity and Auditability
(14:22) Challenges in AI Governance
(17:15) Real-World Use Cases and Partnerships
(19:24) Technical Differentiators of Casper Labs
(23:39) Future Vision and Product Launch
(26:23) Scalability and Hybrid Networks
(27:52) Product Integration and User Experience
(31:54) Support and Onboarding for Enterprises
(33:11) Building the Blockchain Network
(36:02) Market Response and Future Prospects
(39:16) Differentiating from Competitors
(41:06) Expansion Plans and Future Vision
(45:43) Global Compliance and Availability
(55:44) Closing Thoughts
This episode of Eye on AI is sponsored by BetterHelp.
If you’re thinking of starting therapy, give BetterHelp a try. It’s entirely online. Designed to be convenient, flexible, and suited to your schedule. Just fill out a brief questionnaire to get matched with a licensed therapist, and switch therapists any time for no additional charge.
Visit https://www.betterhelp.com/eyeonai today to get 10% off your first month.
In this episode of the Eye on AI podcast, join host Craig Smith as he engages with Russell Palmer, CEO & Co-Founder at CyberFilm AI.
Russell delves into the transformative journey of integrating AI with storytelling, emphasizing the role of strong narratives in creating impactful AI films. He shares his extensive background, from his early days at Microsoft and JP Morgan to co-founding a startup with his brother that pioneers AI tools for the film industry.
Explore how their innovative app supports writers and filmmakers by offering structured templates, AI-generated plot ideas, character arcs, and storyboards. Discover the startup's mission to democratize filmmaking, making high-quality tools accessible to film students, hobbyists, and professionals alike.
Russell discusses the future of AI in filmmaking, highlighting the potential for AI to enhance creativity, support diverse storytelling, and bridge the gap between aspiring creators and Hollywood-level productions. Learn about their plans to expand features, including video generation and script analysis, while maintaining ethical AI use and respecting intellectual property.
Join us for an insightful conversation on how AI is shaping the future of storytelling and filmmaking, and gain valuable perspectives on navigating this evolving landscape.
Tune in to learn how AI can empower you to create compelling stories and films.
Don't forget to like, subscribe, and hit the notification bell for more on groundbreaking AI technologies.
Check out CyberFilms’ Latest Product:
Website: https://writeonsaga.com
Social: https://www.tiktok.com/@writeonsaga
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(02:59) Russell's Background and Early Career
(05:07) Importance of Story in Filmmaking
(06:52) Early Reception and Writer Strike Impact
(08:16) Evolution Video Generation AI Tools
(11:10) Democratizing Filmmaking for All
(14:24) AI in Hollywood and Cost Reduction
(17:21) Addressing Predictability in AI-Generated Stories
(20:39) Creativity and Originality in AI
(25:04) Expanding Storytelling to Global and Cultural Narratives
(29:22) Demonstration of the AI Storytelling App- Saga
(35:28) Enhancing Script Writing with AI
(37:59) Integrating Storyboards and Cinematography
(42:05) Opportunities for Aspiring Filmmakers
(45:52) Final Thoughts
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
In this episode of the Eye on AI podcast, join host Craig Smith as he sits down with Itamar Friedman, co-founder and CEO of CodiumAI, a pioneering company in the realm of intelligent coding systems.
Itamar shares the ambitious vision of CodiumAI, where developers can aim for zero bugs and issues in their code. Dive into the innovative solutions CodiumAI offers, including Codiumate and PR Agent, tools designed to assist developers in planning, writing, analyzing, and reviewing code with high integrity.
Explore the concept of flow engineering and how CodiumAI's research project, AlphaCodium, outperforms DeepMind's AlphaCode by using fewer LLM calls and no fine-tuning.
Itamar delves into the future of coding, where AI not only generates code but ensures its quality through robust verification systems.Itamar offers valuable advice for both developers and enterprises on navigating the evolving landscape of AI in software development.
Tune in to gain insights into how CodiumAI is leading the way in creating a future where coding is more efficient, reliable, and free from bugs.
Don't forget to like, subscribe, and hit the notification bell for more on groundbreaking AI technologies.
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Craig Smith Twitter: https://twitter.com/craigss
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This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
In this episode of the Eye on AI podcast, join us as we sit down with Lukas Biewald, CEO & co-founder of Weights & Biases, the AI developer platform with tools for training models, fine-tuning models, and leveraging foundation models.
Lukas takes us through his journey, from his early days at Stanford and his work in natural language processing, to the founding of CrowdFlower and its evolution into a major player in data annotation. He shares the insights that led him to start Weights and Biases, aiming to provide comprehensive tools for the entire machine learning workflow.
Lukas discusses the importance of high-quality data annotation, the shift in AI applications, and the role of reinforcement learning with human feedback (RLHF) in refining large models.
Discover how Weights and Biases helps ML practitioners with data lineage and compliance, ensuring that models are trained on the right data and adhere to regulatory standards. Lukas also highlights the significance of tracking and visualizing experiments, retaining intellectual property, and evolving the company's products to meet industry needs.
Tune in to gain valuable insights into the world of ML Ops, data annotation, and the critical tools that support machine learning practitioners in deploying reliable models.
Don't forget to like, subscribe, and hit the notification bell for more on groundbreaking AI technologies.
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Craig Smith Twitter: https://twitter.com/craigss
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(00:00) Preview and Intro
(01:39) Lukas's Background and Career
(04:09) Founding CrowdFlower and Early Machine Learning
(06:59) Current Trends in Machine Learning
(08:46) Reinforcement Learning with Human Feedback (RLHF)
(12:43) Weights and Biases: Origin and Mission
(16:44) Visualizations and Compliance in AI
(22:43) US vs. EU AI Regulations
(25:20) Importance of Experiment Tracking in ML
(28:47) Evolving Products to Meet Industry Needs
(30:38) Prompt Engineering in Modern AI
(33:34) Challenges in Monitoring AI Models
(37:25) Monitoring Functions of Weights and Biases
(39:33) Future of Weights and Biases
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. NetSuite is offering a one-of-a-kind flexible financing program.
Head to https://netsuite.com/EYEONAI to know more.
In this episode of the Eye on AI podcast, join us as we sit down with Jonathan Gillham, founder of Originality AI, a company specializing in AI detection technology.
Jonathan delves into the origins of Originality AI, born out of the need to distinguish between human and AI-generated content in the content publishing industry.
Discover how Originality AI uses supervised learning to build sophisticated models that accurately predict the presence of AI in written content, addressing the challenges of AI detection and adversarial prompts.Learn about the diverse use cases of Originality AI, from web publishers to academia, and how the technology helps mitigate the risk of AI-generated spam in the eyes of Google.
Understand the ethical considerations and societal impacts of AI-generated content, and why transparency and labeling are crucial in this evolving landscape. Jonathan also shares insights into the company's business model, growth trajectory, and future developments, including automated fact-checking and enhancing mixed-use case detection.
Tune in to gain valuable insights into how AI detection technology is shaping the future of content publishing and ensuring content authenticity.
Don't forget to like, subscribe, and hit the notification bell for more on groundbreaking AI technologies.
This episode is sponsored by Vanta, The security and compliance platform trusted by more than 7,000 customers.With Vanta, you can unify your security program management with a built-in risk register and reporting, and proactively manage security reviews with AI-powered security questionnaires.
Listeners get $1,000 off Vanta at vanta.com/eyeonai
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
In this episode of the Eye on AI podcast, join us as we sit down with Peter Cousins, CTO at WorkFusion, a pioneering company in intelligent automation and digital workers for anti-financial crime solutions.
Peter shares how WorkFusion leverages generative AI and classical AI to combat financial crime and enhance compliance.
Discover how AI technologies are revolutionizing sanction screening, adverse media analysis, and KYC processes, reducing manual effort and focusing on high-risk cases.
Learn about the challenges of implementing generative AI in financial services and how a hybrid approach combining human judgment, classical AI, and generative AI ensures accuracy and reliability.
Understand the importance of explainability in AI decisions and how WorkFusion's solutions meet regulatory standards for global financial institutions.
Peter also shares insights into the ongoing arms race against financial criminals and the future of AI in the financial industry.
Tune in to gain valuable insights into how AI is transforming financial services.
Don't forget to like, subscribe, and hit the notification bell for more on groundbreaking AI technologies.
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This episode is sponsored by TrialKey.ai, the market leader AI-driven clinical trial design optimization, and predictor that improves trial design and execution. With over 90% accuracy based on precision/recall, TrialKey.ai predicts the success of clinical trials more precisely than any other tool on the market.
Maximize clinical trial success while minimizing costs – book a demo at https://trialkey.ai/ or sign up for free!
In this episode of the Eye on AI podcast, join us as we sit down with Rahul Sonwalkar, founder and CEO of Julius AI, a cutting-edge platform revolutionizing data analysis through AI-powered code generation.
Rahul shares his inspiring journey from learning to code in high school to founding Julius AI, a tool that helps users analyze datasets, create visualizations, and gain insights using natural language. With over half a million users in just eight months, Julius AI is transforming the way we approach data science and coding.
Discover the challenges and solutions in AI code generation, as Rahul delves into the complexities of building an AI-native product focused on accuracy. Learn how Julius AI uses a mixture of models and error recovery processes to provide reliable code generation and execution.
Explore real-world use cases of Julius AI, from financial analysis and biostatistics to web scraping and beyond. Rahul also shares the future vision of programming with AI, where everyone can become a programmer using simple English commands.
Tune in to understand how Julius AI is setting itself apart from competitors like Microsoft's Copilot and other AI coding tools by prioritizing user-focused problem-solving and community engagement. Rahul's insights into the future of AI programming and the expansion plans for Julius AI are not to be missed.
Don't forget to like, subscribe, and hit the notification bell for more insights into the groundbreaking technologies driving the AI revolution.
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Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction to Julius AI
(04:18) Rahul's Background and Journey
(10:34) Development and Vision for Julius AI
(14:37) Challenges in AI Code Generation
(17:07) Acquiring Users and Community Building
(19:29) Solving the Code Generation Problem
(23:33) How Julius AI Works
(33:19) Range of Tasks and Use Cases
(36:02) Comparison with Competitors
(39:49) AI Native Products vs. Integrations
(44:03) Julius AI's Business Model
(44:23) Live Demo of Julius AI
(48:14) Success Stories and User Examples
(51:43) Julius AI's Future Plans and New Features
(54:54) Translating Complex Documents with AI
(56:09) Optimism for the Future of AI Programming
This episode is sponsored by Vanta, The security and compliance platform trusted by more than 7,000 customers.With Vanta, you can unify your security program management with a built-in risk register and reporting, and proactively manage security reviews with AI-powered security questionnaires.
Listeners get $1,000 off Vanta at vanta.com/eyeonai
In this episode of the Eye on AI podcast, join us for an insightful conversation with Edward Balassanian, CEO and founder of Aimi, a trailblazer in the realm of generative AI music.
Edward takes us through his fascinating journey from engineering and computer science to pioneering a platform that transforms music into a dynamic, interactive service. Aimi’s innovative approach to AI-generated music is redefining the industry by enabling both amateurs and professionals to create high-quality, customized music.
Discover the technical and legal challenges unique to the AI music space, and how Aimi’s bottom-up approach to music creation sets it apart from other AI music initiatives. Edward delves into the complexities of training models with ethically sourced, high-quality data, and explains the importance of maintaining human elements in generative music.
Explore the vast potential of music as a service and how Aimi is revolutionizing industries like gaming, social media, and content creation by integrating seamless, non-repetitive music into various applications. Edward also shares real-world examples and future plans for Aimi, emphasizing the role of AI in amplifying human creativity.
Tune in to understand the transformative impact of AI on music and how Aimi is leading the charge in this exciting frontier.
Don't forget to like, subscribe, and hit the notification bell for more insights into the cutting-edge technologies driving the AI revolution.
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
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Craig Smith Twitter: https://twitter.com/craigss
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This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
In this episode of the Eye on AI podcast, join us as we dive into the realm of AI quality assurance with Mohamed Elgendy, CEO and co-founder of Kolena.
Discover the intricacies of ensuring robust AI performance as Mohamed shares his journey from a software engineer to leading an AI quality platform. Kolena is setting new standards in AI testing, addressing the non-deterministic nature of machine learning models with a systematic framework for validation.
The conversation navigates the challenges of AI testing, the importance of structured quality assurance, and the collaboration with industry bodies to shape the future of AI standards. Mohamed elaborates on Kolena's innovative approach to both human and automated evaluations, providing comprehensive testing solutions tailored to diverse customer needs.
We also explore real-world use cases and the platform's future plans to make AI testing more accessible and reliable. Mohamed's insights illuminate the path toward achieving high-quality AI systems, ensuring they perform as intended across various applications.
Tune in to understand the advancements propelling AI quality forward and how Kolena is pioneering the way in this crucial aspect of AI development.
Don't forget to like, subscribe, and hit the notification bell for more insights into the technologies driving the AI revolution.
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
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Craig Smith Twitter: https://twitter.com/craigss
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This episode is sponsored by 1Password. 1Password combines industry-leading security with award-winning design to bring private, secure, and user-friendly password management to everyone. Companies lose hours every day just from employees forgetting and resetting passwords. A single data breach costs millions of dollars. 1Password secures every sign-in to save you time and money.
Right now, my listeners get a free 2-week trial at: https://www.1password.com/eyeonai
In this episode of Eye on AI, join us as we explore the cutting-edge world of GPU optimization with Ronen Dar, CTO and co-founder of Run:ai.
Delve into the intricacies of managing and maximizing GPU utilization in an era marked by a severe GPU shortage. Ronen shares his insights on how Run:ai's innovative software is revolutionizing AI infrastructure, making GPU resources more efficient and accessible.
The conversation spans the technical challenges of scaling AI models, the evolution of GPU demands from basic algorithms to complex systems like GPT-4, and the strategic innovations helping enterprises overcome these hurdles. Ronen also reflects on the future of AI development, predicting an exponential increase in demand for computational power and the innovative solutions poised to meet these needs.
Tune in to uncover the technological advancements that are propelling AI capabilities forward and shaping the future of AI deployment across industries.
Don't forget to like, subscribe, and hit the notification bell for more deep dives into the technologies that are transforming our digital landscape.
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(00:00) Preview
(02:46) Introducing Ronen Dar
(04:00) Ronen's background and RunAI's origins
(09:13) The need for efficient GPU utilization in AI
(13:14) RunAI's core value proposition
(15:33 RunAI's deployment model
(18:55) The growing demand for compute power and GPUs
(22:08) Challenges in scaling models beyond 70 billion parameters
(27:52) RunAI's open platform approach
(31:00) Addressing latency and throughput challenges in inference
(34:36) RunAI's integration with AI tools and frameworks
(39:37) Reducing the cost of inference with GPU virtualization
(43:54) Challenges in auto-scaling for large language models
(47:06) The future of the GPU market and demand
(50:49) NVIDIA's dominance and the role of competitors like Cerebras
(54:20) RunAI's global customer base and demand patterns
(57:52) NVIDIA's vision and the evolution of GPU architectures
(01:01:25) Compute requirements for the metaverse and future AI applications
(01:03:56) Concerns about power consumption and carbon footprint
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
Unlock the secrets of clinical trial predictions with Saurabh Jain and Damon Rasheed from Opyl & TrialKey.ai on this episode of Eye on AI.
In today’s discussion, delve into how TrialKey's pioneering AI model can predict the success of clinical trials with astonishing accuracy—about 90%. Learn about the innovative use of over 400,000 past trials to enhance the precision and efficiency of new pharmaceutical trials. Saurabh and Damon share how their technology not only predicts outcomes but also optimizes trial design, saving substantial time and resources in the drug development process.
The episode also covers the sophisticated data processing techniques employed by TrialKey, including natural language processing to extract vital variables from complex datasets, and the strategic use of these insights to improve trial designs. Discover the implications of poorly designed trials and how AI can revolutionize their structure for better success rates.
Tune in to gain a deeper understanding of how AI and machine learning are transforming the pharmaceutical landscape, making clinical trials more predictive and efficient. Saurabh and Damon’s expertise offers a glimpse into the future of medical research and investment, emphasizing the role of AI in enhancing decision-making and resource allocation in healthcare.
Remember to like, subscribe, and hit the notification bell to keep up with the latest innovations and discussions reshaping the future of artificial intelligence and healthcare.
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Dive into the cutting-edge realm of neuromorphic computing with André van Schaik, a professor of electrical engineering at the Western Sydney University, and director of the International Centre for Neuromorphic Systems, in Penrith, New South Wales, Australia
In this episode of Eye on AI, André unveils the capabilities of DeepSouth, an innovative brain-scaled neuromorphic computing system designed to simulate up to 100 billion neurons in real time. Discover how DeepSouth leverages spiking neurons and synapses to process information more efficiently than traditional AI models, and how this technology could transform our understanding of brain computation and unlock new AI architectures.
The conversation explores the unique hardware setup of DeepSouth, utilizing FPGAs (Field-Programmable Gate Arrays) for a flexible, reconfigurable approach that mimics the asynchronous and spiking communication of biological neurons.
André discusses the initial testing phase focusing on balanced excitation-inhibition networks, reflecting common neural activities in the human cortex, and outlines the system's potential to facilitate large-scale simulations previously unachievable due to computational constraints.
André's insights are invaluable for anyone interested in the intersection of neuroscience, artificial intelligence, and computational technology.
Don't forget to like, subscribe, and hit the notification bell to stay updated on the latest breakthroughs and discussions in the world of artificial intelligence.
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
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(00:00) Preview and Introduction
(02:19) André van Schaik's background
(03:39) What is neuromorphic computing?
(05:45) Differences between Von Neumann and neuromorphic architectures
(09:27) How DeepSouth simulates neurons
(12:20) What are FPGAs?
(16:42) Current status of DeepSouth
(19:04) Running neural network architectures on DeepSouth
(22:33) DeepSouth as an open source, commercial hardware
(24:40) Potential for cheaper model training
(28:35) Number of neurons and connections in DeepSouth
(30:01) Power consumption comparison
(34:21) Mimicking brain structures in DeepSouth
(35:42) André van Schaik's background in neuroscience
(39:12) Goals of understanding brain activity vs solving problems
(41:44) Interest from AI research community
(43:03) Summary of DeepSouth's goals
This episode is sponsored by 1Password. 1Password combines industry-leading security with award-winning design to bring private, secure, and user-friendly password management to everyone. Companies lose hours every day just from employees forgetting and resetting passwords. A single data breach costs millions of dollars. 1Password secures every sign-in to save you time and money.
Right now, my listeners get a free 2-week trial at: www.1password.com/eyeonai
Explore the world of AI development with Will Falcon, creator of PyTorch Lightning and founder of Lightning AI.
In this episode of Eye on AI, Will takes us through the groundbreaking journey of Lightning Studio, a revolutionary cloud-based platform that's reshaping how AI tools and frameworks are integrated and scaled. From his unique start in the US military to leading AI innovation, Will offers a comprehensive look at the evolution of machine learning technologies that simplify and accelerate the deployment of AI models.
The discussion delves into the creation of PyTorch Lightning, highlighting its role in democratizing AI development by structuring code and enabling scalability across thousands of machines. Will also outlines the pivotal shift from traditional coding practices to a streamlined, cloud-based environment, making advanced AI tools accessible to a global community of developers.
Tune in as we uncover the layers of technology that drive AI forward and discuss the future of AI development platforms.
Will's insights are crucial for anyone interested in the intersection of AI, software engineering, and cloud infrastructure.
Make sure to hit the like button and subscribe for more insights into the technologies shaping our world.
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
This episode is sponsored by 1Password. 1Password combines industry-leading security with award-winning design to bring private, secure, and user-friendly password management to everyone. Companies lose hours every day just from employees forgetting and resetting passwords. A single data breach costs millions of dollars. 1Password secures every sign-in to save you time and money.
Right now, my listeners get a free 2-week trial at: www.1password.com/eyeonai
Dive into the world of autonomous driving with Dragomir Anguelov, Vice President, Head of Research at Waymo, in this captivating episode of Eye on AI.
Drago offers a profound exploration into the technical and operational advancements driving the future of autonomous vehicles. With his rich background at Google and now at Waymo, Drago provides an insider’s view on the evolution of machine learning technologies and their pivotal role in developing self-driving cars that are not only intelligent but also safe and reliable.
This conversation spans the inception of large neural networks for image understanding to the intricate deployment of robotaxis in urban environments. Drago details the challenges of scaling these complex systems across different cities and the breakthroughs that have made autonomous driving a tangible reality in places like Phoenix and San Francisco.
Drago’s insights are invaluable for anyone interested in the convergence of AI, robotics, and transportation.
If you are fascinated by the advancements being made in the autonomous driving space and how they could transform our daily lives, make sure to hit the like button and subscribe for more deep dives into the technologies shaping our future.
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This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
NetSuite is offering a one-of-a-kind flexible financing program. Head to https://netsuite.com/EYEONAI to know more.
Venture into the future of AI with Nick Bostrom, a philosopher at the University of Oxford known for his work on existential risk, the anthropic principle, human enhancement ethics, whole brain emulation, superintelligence risks, and the reversal test.
On episode #181 of Eye on AI, Nick Bostrom, explores the existential and societal implications of AI reaching and surpassing human capabilities. As we contemplate a world where all tasks are performed by AI, Nick discusses the potential for a 'technologically solved' society and its impact on human purpose and motivation.
Join us as Nick provides insights into his latest book, "Deep Utopia," where he questions how humans will find meaning when artificial intelligence handles every aspect of labor and creativity. He elaborates on the risks, ethical considerations, and philosophical dilemmas we face as AI continues to evolve at an unprecedented pace.
This episode is an essential exploration of the shifts AI may bring to our societal structures, labour markets, and individual lives.
If you find yourself intrigued by the philosophical journey into AI's potential to redefine humanity, hit the like button and subscribe for more thoughtful discussions on the future landscapes shaped by artificial intelligence.
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(00:00) Introduction and the Concept of a 'Solved World'
(03:05) Nick Bostrom's Background
(06:06) Exploring the Anthropomorphism in Modern AI
(08:02) Predictions and the 'Hockey Stick' Graph
(10:13) AI Safety and Public Perception
(12:58) Deep Utopia and the Search for Meaning
(15:46) Life in a Technologically Mature World
(18:17) Existential Malaise in Modern Society
(20:43) The Potential of Technological Maturity
(23:51) Philosophical Implications of a Solved World
(28:20) Engineering Happiness and Neurological Adjustments
(32:18) Remaining Human Tasks and Cultural Values
(35:45) The Future of Humanity
(47:03) Closing Remarks and Sponsor Message
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
Explore the journey of AI within the technology industry with Thomas Lah in episode #180 of Eye on AI.
This dialogue features Thomas Lah, Executive Director of the Technology and Services Industry Association (TSIA), as he delves into the influence of AI on technology companies and their operating models.
In this episode, Thomas offers a compelling narrative on how AI is being integrated into the fabric of technology businesses, altering the landscape of innovation and competition. Discover the intricacies of AI adoption strategies, the challenges of data management, and the evolution of business models in response to AI advancements. From Microsoft to Salesforce, uncover how leading tech giants are harnessing AI to redefine efficiency, creativity, and growth.
Dive deep into the core of TSIA's research, unveiling the pivotal role of benchmarking and operational research in navigating the AI revolution. Thomas sheds light on the actionable insights and best practices that are guiding technology companies through this era of rapid technological change.
Whether you're intrigued by the operational shifts AI is catalyzing in the tech sector, or you're keen on understanding the future directions of AI-driven business models, this episode is a treasure trove of knowledge.
Remember to give us a thumbs up on YouTube if this deep dive into the AI transformation within tech companies enriches your understanding.
Subscribe for more insights into how AI is sculpting the technological landscapes of tomorrow.
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(00:00) Preview and Introduction (01:19) AI’s Impact on Tech Companies' Internal Processes (04:22) Thomas Lah’s Background and Contributions to Tech Services (07:49) Future Trends: AI Agents and Physical World Actions (10:12) Real-World AI Use Cases and ROI in Tech Companies (13:44) The Rapid Maturation of AI Tools and Its Impact (16:48) The Right Timing for AI Adoption and Investment (20:09) AI Advantaged vs. Severely Lagged Tech Companies (25:31) Addressing the Consumption Gap with AI in Education (32:17) AI in Operations (38:35) The Evolution of AI Agents and Co-Pilots in Tech Services (45:12) Centralizing and Rationalizing Data for AI Readiness (48:31) Cultural and Technical Shifts Required for AI Integration (51:06) AI's Impact on Business Models and Headcount Reductions
Dive into the heart of the AI race between the US and China with Craig Smith in episode #179 of Eye on AI.
This discussion features Ylli Bajraktari, the President and CEO of the Special Competitive Studies Project, as he unveils the strategic maneuvers and policies shaping the future of artificial intelligence on a global scale.
In this episode, Ylli provides an in-depth analysis of the current state of AI development and competition, illuminating the actions taken by both superpowers to secure their position at the forefront of technological advancement. From the pivotal CHIPS Act to the formation of national AI champions, learn how these initiatives are influencing the global AI landscape.
Uncover the essence of the Special Competitive Studies Project and its mission to ensure the US retains its edge in AI through a comprehensive, nation-wide approach. Ylli discusses the critical importance of AI in national security, the transformative potential of the OffsetX strategy, and the implications of the National Plan for Microelectronics.
Whether you're fascinated by the strategic dynamics of international technology competition or passionate about the impact of AI on society and security, this episode offers invaluable insights into the challenges and opportunities ahead.
Don't forget to rate us on Apple Podcast and Spotify if you're inspired by the strategic discourse on AI's role in shaping the future.
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview
(00:46) Introducing Ylli Bajraktari
(04:21) Origins of the Special Competitive Studies Project
(09:14) Influence of National Security Commission on AI
(14:05) What is the OffsetX Strategy
(15:42) US vs. China: The AI Competition Landscape
(19:00) Post-Gen AI Period and Its Impact
(21:03) The Future of AI Research
(24:41) Reorganizing Government Institutions for the AI Era
(32:48) Understanding Lethal Autonomous Weapon Systems
(35:05) The Concept of Counter-Autonomy
(39:04) Addressing the Threat from China’s Semiconductor Strategy
(44:54) Preview of the Special Competitive Studies Project's AI Expo
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
Join host Craig Smith in episode #178 of Eye on AI for an enlightening conversation with Terry Sejnowski, President of the NeurIPS Foundation and is the Francis Crick Professor at the Salk Institute for Biological Studies where he directs the Computational Neurobiology Laboratory
In this episode, Terry shares his unique insights into the evolution of neural networks, the monumental impact of models like GPT-4, and the intricate relationship between AI technologies and societal norms. Learn about the future trajectory of AI development, as Terry highlights the importance of integrating human brain development aspects into AI to foster models that better understand and integrate into human culture.
Discover Terry's perspective on the role of reinforcement learning in AI, the challenges of aligning AI with ethical considerations, and the potential of neuromorphic engineering to revolutionize energy-efficient computing. This discussion also touches on the implications of AI in reshaping industries, science, and the global workforce.
An essential listen for those fascinated by the ethical dimensions of AI, the potential of neuroscience to inform AI development, and the broader societal impacts of technological advancement.
If you're drawn to the complexities of AI and its potential to redefine our future, don't forget to rate us on Apple Podcast and Spotify.
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(00:00) Introduction to Terry Sejnowski
(01:54) Bridging Computational Neuroscience with AI Development
(05:24) Biological Principles in AI: Learning and Adaptation
(07:07) The Crucial Role of Reinforcement Learning in AI
(10:12) Breakthroughs in AI: Scaling Models and Language Processing
(13:38) The Rapid Pace of AI Evolution: Implications and "AI Time"
(16:58) Ethical Considerations and AI Alignment Challenges
(20:23) Neuromorphic Engineering and Energy Efficiency
(25:42) Real-world Applications: AI's Expanding Role in Society
(29:04) The Developmental Approach: Training AI with Human Nuances
(33:32) The Impact of AI on Science and Discovery
(40:19) AI Education and Lifelong Learning: Overcoming Barriers
(43:20) MOOCs and the Democratization of Learning in the AI Era
(47:08) Balancing Innovation and Safety in the Accelerating AI Landscape
Join host Craig Smith on episode #177 of Eye on AI as he explores the cutting-edge world of generative models in artificial intelligence with Björn Ommer, a visionary AI researcher and Head of Computer Vision & Learning Group at Ludwig Maximilian University of Munic.
In this episode, Björn delves into the fascinating inner workings of diffusion models, shedding light on the pivotal role these models play in advancing technology and society. Discover the groundbreaking development of stable diffusion, a key innovation by Bjorn's team that is setting new standards in the democratization of AI technology.
Learn about the challenges and solutions in making AI accessible on consumer hardware, ensuring that the power of generative AI is not confined to well-funded organizations but available to all. Bjorn shares his expert insights on the balance between open-source innovation and proprietary development, emphasizing the societal implications of generative AI.
This episode is an essential listen for anyone intrigued by the potential of AI to transform our understanding of the visual world, the importance of accessibility in technology, and the future of AI development.
If you're captivated by the evolution of AI and the profound impact of generative models like stable diffusion, don't forget to rate us on Apple Podcast and Spotify.
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(00:00) Preview and Introduction
(01:38) Bjorn Omer's Journey into AI
(03:03) The Evolution of AI Before Deep Learning
(06:38) Democratizing AI with Stable Diffusion
(09:45) Explaining Diffusion Models
(13:40) Challenges of AI on Consumer Hardware
(17:05) The Binding Problem in Vision Research
(22:27) Mechanisms in Stable Diffusion: Attention and Diffusion Processes
(26:09) Open Source vs. Proprietary AI Models
(30:16) Making Compute Resources More Accessible
(34:30) Reducing Compute Requirements in AI Models
(38:52) The Concept of World Models in AI Research
(41:50) The Future of AI and the Fallacy of Scaling
Join host Craig Smith on episode #176 of Eye on AI as he dives deep into the realm of robotic artificial intelligence with Sergey Levine, associate professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley.
In this episode, Sergey unveils the latest advancements in AI control of robots, exploring the implications of reinforcement learning and the concept of embodied AI.
Discover how Sergey's research is pushing the boundaries of AI, enabling robots to learn manipulation skills and generalize across diverse tasks, transforming the potential of home robots and beyond.
Sergey also shares insights into the RTX project, an ambitious collaboration designed to achieve remarkable generalization across different robot morphologies, enhancing robots' ability to perform language-conditioned manipulation tasks.
If you're fascinated by the intersection of AI, robotics, and the quest for creating adaptable, generalizable machines that promise to revolutionize our interaction with technology, this episode is a must-listen.
Remember to rate us on Apple Podcast and Spotify if this episode ignites your interest in the dynamic field of robotic AI and the visionary work of Sergey Levine.
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(00:00) Preview and Introduction to Home Robots and AI in Robotics
(01:43) World Models and Language Models in Robotics
(04:01) The Challenge of Learning-Based Control and Data Utilization
(06:05) RTX Project: Generalizing Controllers Across Different Robots
(10:09) Uniformity in Model Architecture Across Labs
(13:50) Introduction of RT1 and RT2 Models for Robot Control
(16:06) The Future of Robotic Control Research and Architecture
(18:49) The Impact of Hardware Development on Robotics
(22:15) Advances in Controller and AI Model Development
(26:21) Planning and Acting with Vision Language Models
(31:38) The Proprietary vs. Open-Source Debate in Robotics
(36:23) The Future of Commercial and Open Source Robotics Applications
(40:59) The State of Robotics Research in China
Join host Craig Smith on episode #175 of Eye on AI as he engages in an enlightening conversation with Aravind Srinivas, co-founder and CEO of Perplexity AI.
In this episode, Aravind delves into the intricacies of Perplexity AI, a groundbreaking conversational answer engine designed to redefine the landscape of online search.
Discover how Perplexity AI aims to challenge the status quo of search engines by providing direct answers grounded in factual sources, contrasting with the traditional method of sifting through links.
Learn about the challenges and breakthroughs in developing a search engine that combines the reliability of verified information with the intuitive interaction of conversational AI.
Dive into the technical and philosophical nuances of building a search platform that stands to transform how we access information online. Explore the intersection of AI, entrepreneurship, and the relentless pursuit of innovation that drives the team at Perplexity AI.
Remember to rate us on Apple Podcast and Spotify if this episode piques your curiosity about the evolving interface of AI and information retrieval!"
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(00:00) Introduction to Perplexity AI with Aravind Srinivas
(02:26) Aravind Srinivas's Background
(04:17) Early Influences and The Shift to Generative AI
(06:30) Ideation and Entrepreneurial Leap to Start Perplexity AI
(09:44) Challenges of Building a New AI-Powered Search Engine
(13:53) The Journey from Idea to Market with Perplexity AI
(17:34) Overcoming Technical and Market Challenges
(23:44) Disrupting Traditional Search with AI Innovation
(30:08) Building Perplexity's AI and Indexing Technology
(37:13) The Future of Web Indexing and AI's Role
(41:29) Navigating Legal and Ethical Aspects of AI Search
(52:39) Concluding Thoughts and The Road Ahead for Perplexity AI
Join host Craig Smith on episode #174 of Eye on AI as he sits down with Tianmin Shu, Assistant Professor at Johns Hopkins University in both the Computer Science and Cognitive Science departments.
In this episode, Tianmin unravels the fascinating concept of world models and their intersection with artificial and human intelligence. Discover how these models, rooted in cognitive science, offer a blueprint for understanding our environment and enhancing AI's ability to interpret, predict, and interact within it.
Explore the intricate dance between AI and cognitive science as Tianmin shares insights from his rich academic journey from UCLA to MIT, leading to his innovative work on social aspects of AI and the development of agents capable of human-level cooperation and understanding.
Dive deep into the discussion on the integration of world models with large language models, and how this synergy could revolutionize AI's predictive capabilities and reasoning, paving the way for more intuitive and interactive systems across various domains, especially in household environments.
Don't miss this riveting exploration of the next frontier in artificial intelligence research and its potential to transform our interaction with technology.
Remember to rate us on Apple Podcast and Spotify if you're intrigued by the insights shared in this episode!
This episode is sponsored by 1Password. 1Password combines industry-leading security with award-winning design to bring private, secure, and user-friendly password management to everyone. Companies lose hours every day just from employees forgetting and resetting passwords. A single data breach costs millions of dollars. 1Password secures every sign-in to save you time and money. Right now, my listeners get a free 2-week trial at: 1password.com/eyeonai
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Join host Craig Smith for episode #173 of Eye on AI, featuring a groundbreaking discussion with Vincent Vanhoucke, distinguished Scientist, and Senior Director for Robotics at Google DeepMind.
In this episode, Vincent dives into the cutting-edge world of robotic control with RT2, DeepMind's innovative robotic transformer system. Learn how RT2's integration of visual perception, natural language understanding, and action planning is pushing the boundaries of robotics, enabling machines to reason and act with unprecedented flexibility and intelligence.
Discover the challenges, technological marvels, and future prospects of robotics as we explore how DeepMind is shaping the future of AI-driven automation.
Tune in to uncover the potential of RT2 in transforming robotic capabilities and the implications for diverse applications across industries.
Don't forget to rate us on Apple Podcast and Spotify if you find the episode insightful!
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
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(00:00) Preview and Introduction (04:15) Vincent's Background and DeepMind's Robotics (06:04) RT2 Architecture Overview (09:06) Semantic Planning in Robotics (12:33) Reinforcement Learning and Mitigating Model Hallucinations (15:47) World Models and Planning (19:29) Integrating Sensory Data for Planning (24:08) The Future of Robotic Control and RT2 (27:35) RT2 Open Source and Hardware Integration
Join host Craig Smith on episode #172 of Eye on AI as he sits down with Cris Valenzuela, co-founder and CEO of Runway, an applied AI research company shaping the next era of art, entertainment and human creativity
Cris shares insights into the origins of Runway, highlighting how the company supports creators across various domains, from filmmaking to music production, by leveraging the power of AI.
We dive deep into the fascinating world of generative models like stable diffusion, discussing their development, applications, and the future of creative expression through AI.Discover how Runway's AI tools are breaking new ground in image and video generation, transforming artistic workflows, and opening up unprecedented opportunities for creativity.
We'll also explore the broader implications of AI in art and media, discussing the balance between technological innovation and the preservation of artistic integrity.
Tune in and don't forget to rate us on Apple Podcast and Spotify if you enjoy the episode!
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
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(00:00) Preview and Introduction
(01:56) Cris Valenzuela: Background and Runway's Genesis
(05:48) Understanding Diffusion Models
(08:01) Discussion on Mid Journey and Other Models
(10:19) Open Source vs Proprietary Models
(13:07) Exploring Video Generation Technology
(17:52) Achieving Consistency in Generated Videos
(21:22) Compute Requirements for Training Models
(25:07) Scale and Parameters of Runway's Models
(29:49) Customizing Models for Specific Needs
(33:51) Applicability to AR and VR
(37:32) Runway's User Community and Impact
(40:21) Runway’s Best Work
Join host Craig Smith on episode #171 of Eye on AI, for an enlightening conversation with Anna Marie Wagner, SVP, Head of AI at Ginkgo Bioworks, renowned for their work in synthetic biology and its integration with artificial intelligence.
In this episode, we explore groundbreaking projects like engineering self-fertilizing corn, pioneering RNA therapeutics, and developing sustainable materials.
Discover how Ginkgo leverages its genomic library and AI to design custom proteins, pushing scientific boundaries and paving the way for revolutionary industry applications. We'll also tackle the vital topics of biosecurity and ethical considerations in biotech, highlighting the balance between innovation and responsibility.
Anna Marie Wagner's insights provide a glimpse into the transformative potential at the crossroads of biology and technology, making this episode a must-listen for anyone intrigued by the future of scientific advancements.
Tune in to Eye on AI for this enlightening discussion, and don't forget to rate us on Apple Podcast and Spotify if you enjoy the episode.
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(00:00) Preview and Introduction
(01:37) Anna 's Role at Ginkgo and Her Journey in AI and Biotech
(02:25) Ginkgo Bioworks: History, Founders, and Philosophy
(08:05) Who Can Use Ginkgo's Services?
(10:30) Small Molecules, Biologics, and the Scope of Ginkgo's Work
(12:48) The Role of AI in Biotechnology
(16:46) Enzyme Engineering and ML-Guided Searches
(19:11) Ginkgo's Unique Approach to AI and Biotech
(24:33) The Corn Nitrogen Fixation Project with Bayer
(27:20) Genetic Mechanisms for Nitrogen Fixation
(33:19) Addressing Biosafety and Biosecurity Concerns
(36:47) Exploring New Materials and Environmental Concerns
(40:27) Innovations in Biotech
(42:01) Increasing Biotech Awareness
(46:46) Collaboration with Google
(48:06) Building Foundation Models on Google's Infrastructure
(53:20) The Potential of AI in Biology
Join host Craig Smith on episode #170 of Eye on AI, for a riveting conversation with Richard Sutton, currently serving as a professor of computing science at the University of Alberta and a research scientist at Keen Technologies.
Sutton is considered one of the founders of modern computational reinforcement learning, having several significant contributions to the field, including temporal difference learning and policy gradient methods.
In this episode, we go through the Alberta Plan for AI development, the transformative potential of reinforcement learning, and the future of AI in augmenting human intelligence.
Richard Sutton shares insights on the importance of computational power, the impact of large language models, and the vision for AI that interacts with the world through goals and learning from its environment.
We also explore the challenges and opportunities in making AI more embodied and goal-oriented, and how this approach could revolutionize our interaction with technology.
A must-listen for anyone interested in the cutting-edge advancements in AI and its societal implications.
Don't forget to rate us on Apple Podcast and Spotify if you enjoyed this episode!
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
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(00:00) Preview and Introduction
(02:15) AI’s Evolution: Insights from Richard Sutton
(07:08) Breaking Down AI: From Algorithms to AGI
(10:50) The Alberta Experiment: A New Approach to AI Learning
(18:27) The Horde Architecture Explained
(21:23) Power Collaboration: Carmack, Keen, and the Future of AI
(25:04) Expanding AI's Learning Capabilities
(31:34) Is AI the Future of Technology?
(35:29) The Next Step in AI: Experiential Learning and Embodiment
(40:00) AI's Building Blocks: Algorithms for a Smarter Tomorrow
(45:59) The Strategy of AI: Planning and Representation
(49:27) Learning Methods Face-Off: Reinforcement vs. Supervised
(52:53) The 2030 Vision: Aiming for True AI Intelligence?
Join host Craig Smith on episode #169 of Eye on AI as we sit down with Guillermo Rauch, CEO of Vercel, a company that optimizes frontend deployment, making web projects faster to execute and easier to scale.
In this episode, we explore the intersection of AI and web development, showcasing how Vercel is pioneering the integration of generative AI technologies to revolutionize web experiences.
Guillermo Rauch shares his vision on the future of web development, emphasizing the significance of JavaScript, the evolution of the web, and the critical role of Vercel in facilitating developers to seamlessly deploy AI-driven applications.
We delve into the architectural innovations at Vercel, the democratization of AI, and the synergy of combining diverse AI models for superior functionalities as well. Guillermo's perspectives provide a glimpse into the future of interactive web experiences, powered by AI.
This episode is a must-listen for developers, entrepreneurs, and anyone interested in the cutting-edge of AI and web development.
Don't forget to rate us on Apple Podcast and Spotify if you enjoyed this episode!
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
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(00:00) Preview and Introduction
(03:01) Guillermo's Background and Next.js Creation
(08:19) Vercel's Operation on AWS and Alternative Solutions
(13:12) Combining Different AI Models for Enhanced Outputs
(17:25) The Evolution of AI and Focus on User Experience
(22:46) Introduction to Copilot and AI Integration in Coding
(26:33) The Future of AI Technologies
(31:41) Generative AI Applications and Vercel's Role
(33:14) Flexibility and Framework Support on Vercel
(38:11) Vercel's Architectural Approach
(41:02) Trends in Generative AI and App Development
(47:54) Supporting Applications with World Models
(50:54) Vercel's Growth and Expansion in Serving AI Companies
(55:20) Flexibility in Model Integration and Future Directions
(57:28) Closing Remarks and Oracle Cloud Infrastructure Promo
Join host Craig Smith on episode #168 of Eye on AI as we sit down with Ian Bremmer, the founder and president of the Eurasia Group, a leading global political risk research and consulting firm.
In this episode, we delve into the complex world of AI governance and the geopolitical challenges of regulating transformative technology.
Ian Bremmer shares his expert insights into the rapidly evolving landscape of AI development and its implications for global politics, security, and economy. We discuss the necessity of international cooperation and regulatory frameworks to manage the risks and harness the potential of AI technologies.
Bremmer also draws parallels between AI governance and other regulatory challenges, such as climate change, highlighting the importance of strategic foresight and adaptive policies in addressing the multifaceted issues presented by AI.
Whether you're interested in the geopolitical dynamics of technology, the intricacies of AI regulation, or the future of global governance, this episode offers valuable perspectives from one of the leading thinkers in the field.
Make sure you rate us on Apple Podcast and Spotify if you enjoyed this episode!
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at https://netsuite.com/EYEONAI
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(00:00) Introduction to AI Governance
(00:59) Craig Smith's Introduction
(03:00) Ian Bremmer's Background
(04:19) AI Regulation Discussion
(11:17) Limiting AI Compute Power
(19:21) The Role of AGI and AI Regulation
(26:23) EU's Approach to AI Regulation
(29:24) Hybrid Regulation Models
(32:08) Comparing AI Governance with Other Industries
(35:19) US-China Competition in AI
(42:32) The Role of Open Source in AI Governance
(45:17) Ian Bremmer's Thoughts on AI's Future
This episode is sponsored by ISS, a leading global provider of video intelligence and data awareness solutions. Founded in 1996 and headquartered in Woodbridge, N.J., ISS offers a robust portfolio of AI-powered, high-trust video analytics for streamlining security, safety and business operations within a wide range of vertical markets.
So, what do you want to know about your environment? To learn more about our video intelligence solutions, visit issivs.com Join host Craig Smith on episode #167 of Eye on AI as we sit down with Matt Powell, Managing Director at ISSVSS, a company that offers a comprehensive suite of AI powered video intelligence solutions to address security, safety, and business challenges across a diverse range of vertical markets.
In this episode, we explore the fascinating evolution of video analytics technology, focusing on its impactful applications across various industries, from urban planning and traffic engineering to healthcare and sports venues.
Discover the unique challenges and breakthroughs in video analytics, the intricate development process,and the unique analytic modules designed for diverse tasks like crowd management and safety monitoring.
Matt shares how these advancements are not only transforming business operations but also paving the way for more accessible and consumer-centric applications, particularly in sectors like elder care.
If you're intrigued by the intersection of AI technology and its real-world applications, this conversation is a must-watch.
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at https://netsuite.com/EYEONAI
Stay Updated:
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(00:00) Preview
(00:33) AI’s Role in Various Industries
(02:47) ISS's Evolution and Global Presence
(05:01) On-Premise vs. Cloud Analytics
(09:14) Understanding Video Analytics and AI Modules
(22:16) The Versatility of AI Tasks and Modules
(25:48) Future Trends in AI and Video Analytics
(31:59) Diverse Applications of Video Analytics
(37:00) Accessibility and Cost of Video Analytics
(40:04) Applications in Elder Care and Security
(46:48) Facial Recognition Technology and Privacy
(48:18) Intelligent Transportation and City Planning
(53:48) Advanced Analytics in Public Safety
(58:24) Global Adoption and Future of AI
(1:00:11) Closing Remarks on AI's Impact
Join host Craig Smith on episode #166 of Eye on AI as we sit down with Itamar Arel, CEO of Tenyx, a company that uses proprietary neuroscience-inspired AI technology to build the next generation of voice-based conversational agents.
Itamar shares his journey that started with academic research to becoming a leading tech entrepreneur with Tenyx. We explore the evolution of voice AI in customer service and the unique challenges and advancements in understanding and responding to human speech.
We dig deeper into Tenyx’s unique approach to AI-driven customer service while exploring the production and design considerations when developing cutting-edge AI technology.
Make sure you watch till the end as Itamar shares his vision on how AI is going to reshape industries and help advance modern day businesses.
Enjoyed this conversation? Make sure you like, comment and share for more fascinating discussions in the world of AI.
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
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(00:00) Preview and Introduction
(03:35) Itamar Arel's Career and Introduction to Voice AI Development
(07:39) Key Differences in Current and Past Technology Solutions
(09:10) Advancements in Voice AI and Large Language Models
(11:00) The Inception and Evolution of Tenyx
(13:29) Challenges in Developing Voice AI
(18:27) Innovative Approaches in Voice AI Development
(21:05) Data Handling and Fine-Tuning in Model Development
(25;41) How To Standout In The Crowded AI Market
(29:44) The Future of Voice AI and Generative Models
(37:14) Testing and Evaluation of Voice AI Systems
(40:10) Where Will AI Be in 5 Years?
(43:42) Closing Remarks and A Word From Our Sponsors
This episode is sponsored by Babbel. Babbel is conversation-based learning built with science-backed cognitive tools like spaced repetition and interactive lessons created by real language teachers and voiced by real native speakers.
Get 55% off your Babbel subscription 👉 https://babbel.com/eyeonai
Unveil the transformative power of AI in business and society.
Join us on #165 of the Eye on AI podcast as we sit down with Andy Hock, VP of Product at Cerebras Systems, an AI hardware startup out to accelerate deep learning and change computing forever.
Focusing on the intersection of AI and business, Andy discusses how advanced technologies are reshaping corporate strategies and operations. He offers insights into integrating AI into traditional business models, emphasizing the transformative role of technology in innovation and growth.
We also explore the societal implications of AI. Andy delves into the ethical considerations and challenges posed by AI, including privacy and responsible deployment. He sheds light on the latest trends in AI research, particularly in areas like natural language processing and machine learning, and their diverse applications across industries.
Andy concludes with advice for businesses and individuals navigating the AI landscape, underscoring the importance of adaptability and continuous learning in this rapidly evolving field. Make sure you watch till the end!
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(00:00) Preview and Introduction
(01:09) Decoding Cerebras Systems' Technology.
(03:25) The Power of the Wafer Scale Engine
(05:24) Training and Inference Capabilities
(10:44) Accessibility for Students and Researchers
(12:08) GPU Equivalents and Wafer Scale Engine’s Efficiency
(13:53) Utilization and Power of the Chip
(19:02) Understanding Wafer and Circuitry
(23:27) Computing Power of the Wafer Scale Engine
(28:59) Challenges in Cooling the Wafer Scale Engine
(32:31) Utilization of Silicon Waste
(36:21) Cost Comparison with Other Technologies
(40:01) Customer Usage Patterns – Cloud vs On-Premise
(45:22) Training Models for Edge Devices
(47:30) Collaborations with OpenAI
(49:26) Addressing GPU Shortages and Enterprise Needs
(51:01) Inference Capabilities and Future Developments
(57:46) AI as a National Compute Resource
(01:03:41) Closing Remarks
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at https://netsuite.com/EYEONAI
Explore the frontiers of AI with Hrant Khachatrian and discover how Armenia is carving its niche in the global AI landscape on Eye on AI.
In this episode Hrant shares his journey from industry to academia, detailing the establishment of YerevaNN at a time when machine learning was scarcely present in Armenia.
The discussion revolves around the challenges and breakthroughs in AI research, particularly in areas like natural language processing and clinical time series. Hrant also delves into his lab's efforts in developing deep learning algorithms for a wide array of applications, from electronic health records to image segmentation.
His insights provide a unique perspective on the growth of AI research in Armenia and its global implications, so make sure you watch till the end.
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(02:03) Sponsorship: Netsuite by Oracle Evolution
(04:40) Hrant's Journey: From Computer Science to Founding Yerevann ML Research Lab
(06:15) What Are The Goals of Yerevann ML Research Lab?
(11:33) Career Pathways in AI: Industry vs Academia
(14:22) AI Development in Armenia: Challenges and Opportunities
(21:41) Leveraging Compute Resources for AI Research
(25:46) Drug Discovery and Aerial Navigation in AI
(33:54) Exploring New Avenues of AI Research
(41:15) Building a Global Research Community from Armenia
(49:53) Future of AI Research: Potential Areas and Strategies
(57:10) Closing Remarks
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at https://netsuite.com/EYEONAI
Discover the heart of Armenia’s tech revolution with the latest guest of the Eye on AI podcast, Rem Darbinyan. Discover how this small nation is sprinting towards becoming a powerhouse of innovation, with education systems racing to nurture the next wave of AI mavens.
Rem walks us through his personal journey, from Armenia to Russia and the US, only to return with a mission: to escalate Armenia from an outsourcing hub to a global startup contender.
Learn what it means to dream big, as we unveil the intricacies of pioneering the new era of startups. Step into a world where geographical borders dissolve in the face of unrelenting creativity and flexibility.
(00:00) Preview and Introduction (02:09) The background of Rem Darbinyan (04:49) Sponsorship: Nesuite by Oracle (07:00) How Rem discovered artificial intelligence (09:50) How Armenia and artificial intelligence are growing (13:55) Startup culture and universities for AI/ML (17:45) Was Armenia an outsourced partner for many countries? (22:00) Why do people outsource to India and Armenia? (24:25) How Armenia build products for global markets (30:00) How Rem reaches western markets with products (36:00) How Rem builds influencer platforms (40:00) Building lean and validating each step
Stay Updated:
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This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at https://netsuite.com/EYEONAI
On episode #162 of Eye on AI, Craig Smith sits down with Vasi Philomin, Vice President of Generative AI at Amazon Web Services.
Vasi shares his journey in AI and ML, detailing his contributions to Amazon's extensive array of AI capabilities. He delves into the development and impact of revolutionary services like Lex, Poly, Code Whisperer, and Amazon Q, highlighting Amazon's approach to AI integration and its customer-centric innovations.
This episode offers a glimpse into the transformative potential of generative AI across industries and the future of enterprise AI solutions.
Join us to understand Amazon's unique perspective on AI development and its global influence.
Don't forget to leave a 5-star rating on Spotify and a review on Apple Podcasts!
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(00:00) Preview and Introduction
(03:41)Vasi Philomin's Background and Role at Amazon
(04:13) Generative AI at Amazon: Development and Impac
(08:10) Amazon's AI Strategy and Foundation Models
(15:57) Diverse AI Models and Enterprise Solutions.
(22:01) The Future of AI Agents and Work Automation
(29:22) The Evolution and Impact of AI Agents
(36:32) Closing Remarks and Netsuite by Oracle
This episode is sponsored by Babbel. Babbel is conversation-based learning built with science-backed cognitive tools like spaced repetition and interactive lessons created by real language teachers and voiced by real native speakers.
Get 55% off your Babbel subscription 👉 babbel.com/eyeonai
On episode #161 of Eye on AI, join Craig Smith as he sits down with Harut Martirosyan, CTO of Intent.ai.
In this episode, we explore Harut's journey in AI, highlighting his role in shaping ad targeting technology and fostering Armenia's tech ecosystem.
Harut shares insights about Armenia's technological heritage, the influence of major tech companies in the region, and the evolving landscape of AI and machine learning. We also cover the integration of AI in business and its global impact.
Don't forget to rate us on Spotify and leave a review on Apple Podcasts!
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(00:00) Preview and Introduction to Harut Martirosyan
(05:14) Harut's Background in AI and Privacy Focus
(07:16) Evolution of Tech Education in Armenia
(10:47) Intent AI's Product and Machine Learning Challenges
(15:09) Exploring Armenia’s Growing Tech Ecosystem
(21:57) Political Landscape and Tech's Societal Impact
(30:20) Armenia’s Startup Ecosystem and Market Dynamics
(35:42) Identifying and Capitalizing on Emerging Tech Niches
(39:19) Future Prospects in Armenian Tech
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
On episode #160 of Eye on AI, join Craig Smith as he sits down with Atul Deo, General Manager for Amazon Bedrock.
This episode delves into Atul's journey in the tech world, from his beginnings in computer science and business to spearheading major AI-powered projects at Amazon.
Atul shares his insights on the development and impact of Amazon Bedrock, a platform designed to democratize access to advanced AI models. He discusses the evolution of machine learning, the integration of AI in customer care through Amazon Connect, and the emergence of generative AI technologies like Amazon Code Whisperer.
Learn about the challenges and breakthroughs in creating AI applications, the significance of large language models, and Atul's vision for the future of AI at Amazon.
Don't forget to leave a 5-star rating on Spotify and a review on Apple Podcasts!
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Craig Smith Twitter: https://twitter.com/craigss
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(00:00) Preview and Introduction
(03:30) Exploring Bedrock and Atul’s Professional Journey
(07:14) Diving Deep into Code Whisperer and AI-Powered Coding
(10:54) The Future of AI in Code Generation and Review
(13:23) Unveiling Bedrock's API and Its Ecosystem
(16:36) Retrieval Augmented Generation (RAG) in AI
(21:51) The Evolution and Integration of Vector Databases in AI
(25:29) Confronting the GPU Shortage and AI Scalability
(29:32) The Landscape of Foundation Models and AI's Future
(33:27) Broadening the Horizon: From Language to World Models
(38:33) Closing Thoughts and Future of AI
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
In episode #159 of Eye on AI, Craig Smith sits down with Peter Chen, the co-founder and CEO of Covariant, in a deep dive into the world of AI-driven robotics.
Peter shares his journey from his early days in China to his pivotal role in shaping the future of AI at Covariant. He discusses the philosophies that guided his work at OpenAI and how these have influenced Covariant's mission in robotics.
This episode unveils how Covariant is harnessing AI to build foundational models for robotics, discussing the intersection of reinforcement learning, generative models, and the broader implications for the field. Peter elaborates on the challenges and breakthroughs in developing AI agents that can operate in dynamic, real-world environments, providing insights into the future of robotics and AI integration.
Join us for this insightful conversation, where Peter Chen maps out the evolving landscape of AI in robotics, shedding light on how Covariant is pushing the boundaries of what's possible.
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(00:00) Preview and Introduction
(03:10) Peter Chen Journey in AI
(09:53) The Evolution of Generative AI and Transformer Models
(12:21) The Concept of World Models in AI
(14:03) Building Robust Role Models in AI
(20:48) Training AI: From Video Analysis to Real-World Interaction
(23:10) The Three Pillars of Building a Robotic Foundation Model
(27:36) Architectural Insights of Covariant's Foundation Model
(33:20) Adapting AI Models to Diverse Hardware
(35:01) The Future of Robotics: Progress and Potential
(38:55) Real-World Application and Future of AI-Controlled Robots
(42:11) Envisioning the Future of Automated Warehouses
(45:51) The Evolution of Robotics: Current Trends and Future Prospects
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at NetSuite.com/EYEONAI
On episode 158 of Eye on AI, host Craig Smith dives deep into the world of AI safety, governance, and open-source dilemmas with Connor Leahy, CEO of Conjecture, an AI company specializing in AI safety.
Connor, known for his pioneering work in open-source large language models, shares his views on the monopolization of AI technology and the risks of keeping such powerful technology in the hands of a few.
The episode starts with a discussion on the dangers of centralizing AI power, reflecting on OpenAI's situation and the broader implications for AI governance. Connor draws parallels with historical examples, emphasizing the need for widespread governance and responsible AI development. He highlights the importance of creating AI architectures that are understandable and controllable, discussing the challenges in ensuring AI safety in a rapidly evolving field.
We also explore the complexities of AI ethics, touching upon the necessity of policy and regulation in shaping AI's future. We discuss the potential of AI systems, the importance of public understanding and involvement in AI governance, and the role of governments in regulating AI development.
The episode concludes with a thought-provoking reflection on the future of AI and its impact on society, economy, and politics. Connor urges the need for careful consideration and action in the face of AI's unprecedented capabilities, advocating for a more cautious approach to AI development.
Remember to leave a 5-star rating on Spotify and a review on Apple Podcasts if you enjoyed this podcast.
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(00:00) Preview
(00:25) Netsuite by Oracle
(02:42) Introducing Connor Leahy
(06:35) The Mayak Facility: A Historical Parallel
(13:39) Open Source AI: Safety and Risks
(19:31) Flaws of Self-Regulation in AI
(24:30) Connor’s Policy Proposals for AI
(31:02) Implementing a Kill Switch in AI Systems
(33:39) The Role of Public Opinion and Policy in AI
(41:00) AI Agents and the Risk of Disinformation
(49:26) Survivorship Bias and AI Risks
(52:43) A Hopeful Outlook on AI and Society
(57:08) Closing Remarks and A word From Our Sponsors
This episode is sponsored by ISS, a leading global provider of video intelligence and data awareness solutions. ISS offers a robust portfolio of AI-powered, high-trust video analytics for streamlining security, safety and business operations within a wide range of vertical markets. So, what do you want to know about your environment?
To learn more about our video intelligence solutions, visit https://issivs.com/
On episode #155 of Eye on AI, Craig Smith sits down with Karen Hao, who is currently a contributing writer for The Atlantic with an impressive background as a foreign correspondent for The Wall Street Journal in Hong Kong and as a senior artificial intelligence editor at MIT Technology Review.
Known for her incisive coverage of AI, including its ethical and societal implications, Hao brings a wealth of knowledge from her experiences in journalism and data science.
In this episode, Karen delves into the recent controversies surrounding OpenAI, shedding light on the power struggles, ethical dilemmas, and corporate alliances shaping the future of artificial intelligence. Her unique perspective, gained from her experience as a foreign correspondent and senior AI editor, offers a deep understanding of the complexities that exist in the AI world.
We explore the intricate narrative constructed by OpenAI, its relationship with giants like Microsoft, and the broader implications of these partnerships on AI development and ethics. Karen's critical analysis provides an insightful look into the often opaque world of AI and its global impact.
If you find this discussion as enlightening as we did, please consider leaving a 5-star rating on Spotify and a review on Apple Podcasts.
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(02:28) Karen Hao's Background and Entry into Tech Journalism
(09:14) OpenAI's GPT-2 Controversy and Company Evolution
(11:35) Nonprofit and For-Profit Structure of OpenAI
(15:26) OpenAI Board Dynamics and Power Struggles
(18:07) Transparency and Open Source in AI Development
(21:27) Future of OpenAI and Tech Industry Speculations
(26:22) Microsoft's Investment and Partnership with OpenAI
(31:28) Sam Altman's Potential Chip Company Endeavor
(33:20) AGI Speculations and Existential Risks
(34:38) AGI Definitions and Real-World AI Limitations
This episode is sponsored by Celonis, the global leader in process mining. AI has landed and enterprises are adapting. To give customers’ slick experiences and teams the technology to deliver. The road is long, but you’re closer than you think. Your business processes run through systems. Creating data at every step. Celonis reconstructs this data to generate Process Intelligence. A common business language. So AI knows how your business flows. Across every department, every system and every process. With AI solutions powered by Celonis enterprises get faster, more accurate insights. A new level of automation potential. And a step change in productivity, performance and customer satisfaction Process Intelligence is the missing piece in the AI Enabled tech stack.
Go to https://celonis.com/eyeonai to find out more.
On episode #156 of Eye on AI, Craig Smith sits down with Gordon Crovitz, co-founder of NewsGuard and former publisher of the Wall Street Journal, to unravel the complexities of AI-generated misinformation.
In this episode, Crovitz delves into the challenges posed by AI in the spread of fake news, emphasizing the growing issue of AI-enhanced misinformation websites. He discusses the significant role of NewsGuard in countering this trend through human-analyzed databases and the importance of 'trust data' to improve the reliability of AI models. The conversation also touches upon the responsibility of social media platforms and search engines in this battle against digital deception.
Tune in for an enlightening discussion that navigates the intersection of AI, journalism, and truth in today's digital landscape.
Stay updated:
Craig Smith's Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview
(00:19) Celonis
(01:26) Introducing Gordon Crovitz
(02:24) What is NewsGuard’s Mission?
(05:58) Challenges in Detecting AI-Generated Content
(08:36) The Impact of AI-Generated Misinformation
(14:19) Future of AI Agents and Their Role in Content Generation
(17:35) Use Purpose of NewsGuard's Databases
(22:34) How Do You Tackle Misinformation Effectively?
(29:38) Government and Regulatory Responses to Misinformation
(32:36) What Role Does Social Media Play in Misinformation?
(39:22) Impact of AI on News
(42:32) The Role of Search Companies in Combating Misinformation
(44:13) Regulatory Measures to Stop Misinformation
This episode is sponsored by Celonis, the global leader in process mining. AI has landed and enterprises are adapting. To give customers’ slick experiences and teams the technology to deliver. The road is long, but you’re closer than you think. Your business processes run through systems. Creating data at every step. Celonis reconstructs this data to generate Process Intelligence. A common business language. So AI knows how your business flows. Across every department, every system and every process. With AI solutions powered by Celonis enterprises get faster, more accurate insights. A new level of automation potential. And a step change in productivity, performance and customer satisfaction Process Intelligence is the missing piece in the AI Enabled tech stack.
Go to https://celonis.com/eyeonai to find out more.
Explore the world of scent detection and creation with our special guest, Alex Wiltschko, Founder and CEO of Osmo. Alex is giving computers a sense of smell to improve the health and happiness of human life.
From discussing the complexities of mapping smell using artificial intelligence to the lexicon used by perfumers to standardize their work, Alex takes us on a scented journey that’s bound to whet your olfactory appetite. You’ll be intrigued by how olfactory sensory neurons express 350 distinct channels of information and how AI can predict smells based on the molecular structure.
Alex shares his insights about a unique project they’ve been working on with the Gates Foundation to create molecules that smell good to humans but repel insects. We dive into the prospect of finding safe, affordable, and great smelling molecules via AI, and how this can have a profound impact on products we use every day.
Finally, we shift the conversation to the use of large language models in creating natural language interfaces. Alex shares how Osmo is using AI to ‘open the window of computation to smells’ and how this technology can potentially make us healthier and happier.
Craig Smith's Twitter: https://twitter.com/craigss
(00:00) Preview (00:30) Celonis Sponsorship & introduction (03:30) Alex's Interest in Neuroscience and Scents (05:20) The Neuroscience of Wine Tasting (14:25) Mapping Smell With Artificial Intelligence (18:05) How AI Integrates with Smell & Molecules (21:43) Perfumers' Language Dictionary and Taxonomy (25:20) Completing the Double Blind Test For Scent (34:05) Discovering Safe and Effective Fragrance Molecules (44:23) The Future of Fragrance Technology (54:48) Large Language Models in Natural Language Interfaces
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
Join us on episode #154 of Eye on AI as Craig Smith sits down with Sal Khan, the founder of Khan Academy, a non-profit educational organization that provides free online courses, lessons, and practice exercises across a wide range of subjects to learners worldwide.
In this episode, Sal shares the journey of Khan Academy's growth from a small tutoring project to a global educational platform. He discusses the challenges and successes in integrating AI into educational systems, emphasizing its efficacy in enhancing student engagement and learning outcomes. Sal also sheds light on the potential of generative AI in language learning, illustrating how it bridges cultural and linguistic gaps, especially for students navigating between their native language and English.
The conversation further delves into the impact of AI-powered education in resource-limited settings, exemplifying its potential as a game-changer in global education. We touch upon the skepticism towards free educational resources, a hurdle especially prevalent in poorer regions of the world. Sal Khan addresses this irony, sharing strategies to overcome these barriers and increase awareness and adoption of such resources.
If you found this episode insightful, please support us by leaving a 5-star rating on Spotify and a review on Apple Podcasts.
Stay updated:
Craig Smith's Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Intro (03:02) Sal Khan's Background and the Origins of Khan Academy (08:18) AI Integration in Khan Academy's Learning Platform (11:54) Khanmigo: The AI Tutor from Khan Academy (17:43) Khan Academy's Business Model (23:32) Future of AI Tutors and Engaging Learning Experiences (28:16) Khan Academy's Global Reach and Accessibility (34:17) How is Sal Expanding Khan Academy's AI Capabilities? (38:50) Addressing Skepticism and Misuse of AI in Education (41:19) Sal Khan's Message on the Future of AI in Education
This episode is sponsored by Celonis ,the global leader in process mining. AI has landed and enterprises are adapting. To give customers slick experiences and teams the technology to deliver. The road is long, but you’re closer than you think. Your business processes run through systems. Creating data at every step. Celonis reconstructs this data to generate Process Intelligence. A common business language. So AI knows how your business flows. Across every department, every system and every process. With AI solutions powered by Celonis enterprises get faster, more accurate insights. A new level of automation potential. And a step change in productivity, performance and customer satisfaction Process Intelligence is the missing piece in the AI Enabled tech stack.
Go to https://celonis.com/eyeonai to find out more.
In episode #153 of Eye on AI, Craig Smith sits down with Ed Anuff, Chief Product Office at DataStax.
We take a deep dive into the world of vector databases and their integration with AI. Ed sheds light on the innovative ways AI is being incorporated into database technologies, with a special focus on the advancements and applications of Cassandra in this realm.
Ed elaborates on the challenges and opportunities in melding AI with database management systems. He talks about the evolving landscape of data storage and retrieval in the age of AI, and how these advancements are reshaping businesses and data strategies.
We also explore the broader implications of AI in database technology, including scalability, efficiency, and the future of AI-driven data solutions. Ed shares his insights on how companies like DataStax are at the forefront of this technological convergence, driving innovation and transformation in the industry.
If you find this episode insightful, please support us by leaving a 5-star rating on Spotify and a review on Apple Podcasts.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview, Celonis and Introduction (02:19) Ed Anuff's Background and Journey to DataStax (03:33) The Role of Cassandra in DataStax (05:06) Understanding Cassandra: A NoSQL Database (07:50) Impact of ChatGPT and Vector Databases in AI (11:58) DataStax's Introduction of Vector Databases (17:26) Addressing Data Accumulation and Usage (22:18) Managing Data Expiration in DataStax (29:24) Introducing AstraDB: DataStax's Cloud Product (36:42) Business Growth and AI Integrations in DataStax (42:18) Rate Limits, AI Experiments, and Enterprise Integration (49:47) The Future of AI in Databases (55:20) Evaluating Databases: Performance and Relevancy
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at NetSuite.com/EYEONAI
On episode #152 of Eye on AI, Craig Smith sits down with Alex Kendall, founder and CEO of Wavye, a company building autonomous vehicle technology using AI.
In this episode, Alex provides an inside look at Wavye's approach to autonomous driving, which leverages world models and reinforcement learning to create an AI "driver" that can understand complex urban environments. Alex explains how world models allow an AI system to imagine multiple futures before acting, enabling safer decision-making, and shares Wavye's progress on deploying autonomous delivery vehicles with partners in the UK.
We also dive into the differences between world models and large language models, the unique data challenges of perception-based AI, and Wave's ambitions to expand this AI technology to new applications like humanoid robotics.
If you enjoyed this podcast, please consider leaving a 5-star rating on Spotify and a review on Apple Podcasts.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview, Introduction and Netsuite
(03:45) The Advantages of World Models
(10:12) Developing Autonomous Driving Technology
(16:35) Partnership with Microsoft and Training Challenges
(21:10) Decoding the Concept of Generalization in Autonomous Driving
(27:08) Compute Requirements and Infrastructure
(32:45) The Role of Azure in Training
(37:12) What Is Tokenization of Data
(41:47) Addressing Compute Constraints
(46:12) Future Applications of World Models and Open Source
This episode is sponsored by Celonis ,the global leader in process mining. AI has landed and enterprises are adapting. To give customers slick experiences and teams the technology to deliver. The road is long, but you’re closer than you think. Your business processes run through systems. Creating data at every step. Celonis reconstructs this data to generate Process Intelligence. A common business language. So AI knows how your business flows. Across every department, every system and every process. With AI solutions powered by Celonis enterprises get faster, more accurate insights. A new level of automation potential. And a step change in productivity, performance and customer satisfaction Process Intelligence is the missing piece in the AI Enabled tech stack.
Go to https://celonis.com/eyeonai to find out more.
Welcome to episode 151 of the ‘Eye on AI’ podcast. In this episode, host Craig Smith sits down with Asa Cooper, a postdoctoral researcher at NYU, who is at the forefront of language model safety.
This episode takes us on a journey through the complexities of AI situational awareness, the potential for consciousness in language models, and the future of AI safety research.
Craig and Asa delve into the nuances of AI situational awareness and its distinction from sentience. Asa, with his rich background in NLP and AI safety from Edinburgh University, shares insights from his post-doc work at NYU, discussing collaborative efforts on a paper that has garnered attention for its take on situational awareness in large language models (LLMs).
We explore the economic drivers behind creating AI with such capabilities and the role of scaling versus algorithmic innovation in achieving this milestone. We also delve into the concept of agency in LLMs, the challenges of post-deployment monitoring, and the effectiveness of current measures in detecting situational awareness.
To wrap things off, we break down the importance of source trustworthiness and the model's ability to discern reliable information, a critical aspect of AI safety and functionality, so make sure to watch till the end.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(02:30) Asa's NLP Expertise and the Safety of Language Models
(06:05) Breaking Down AI's Situational Awareness
(13:44) Evolution of AI: Predictive Models to AI Coworkers
(20:29) New Frontier in AI Development?
(27:14) Measuring AI's Awareness
(33:49) Innovative Experiments with LLMs
(40:51) The Consequences of Detecting Situational Awareness in AI
(44:07) How To Train AI On Trusted Sources
(49:52) What Is The Future of AI Training?
(56:35) AI Safety: Public Concerns and the Path Forward**
This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai
Welcome to episode 150 of the ‘Eye on AI’ podcast. In this episode, host Craig Smith sits down with Yann LeCun, a Turing Award winner who has been instrumental in advancing convolutional neural networks and whose work spans machine learning, computer vision, and more.
Tune is as Craig and Yann explore the intricacies of AI, world models, and the challenges of continuous learning.
In this episode, Yann delves deep into the concept of a "world model" - systems that can predict the world's future states, allowing agents to make informed decisions. The discussion transitions to the challenges of training these models, particularly when dealing with diverse data like text and images. We then discuss the computational demands of modern AI models, with Yann highlighting the nuances between generative models for videos and language.
He also touches upon the idea of the "Embodied Turing Tests" and how augmented language models can bridge the gap between human-like behavior and computational efficiency.The spotlight then shifts to pressing concerns surrounding the open-source nature of AI models, with Yann articulating the legal ramifications and the future of open-source AI. Drawing from global perspectives, including China's stance on open-source, Yann underscores the imperative for a collaborative approach in the AI space, ensuring it's reflective of diverse global needs.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview, Oracle and Introduction
(02:42) Decoding The World Model and Gaia 1
(07:43) Energy and Computational Demands of AI
(08:06) Video vs. Text Processing & True AI Capabilities
(11:17) Embodied Turing Test & Augmented LLMs
(15:38) Is AI a Threat To Society?
(25:04) Where is AI Development Headed?
(31:06) Interplay of Neuroscience and AI**
(33:33) Yann's Vision, JEPA, and Learning Challenges
(39:05) Yann's Career, AI Progress, and Challenges
(44:47) The Open Source Debate in AI
(55:30) Oracle Cloud Infrastructure
This episode is sponsored by Digimarc, the leader in digital watermarking. Digimarc digital watermarks invisibly guard your digital assets to protect against misuse, prove copyright ownership, and verify authenticity. In an era of artificial intelligence, don’t leave your images and other digital content exposed. Demand superior content protection and maintain trust in your brand with Digimarc.
Checkout Digimarc - https://www.digimarc.com/
This episode is sponsored by Celonis ,the global leader in process mining. AI has landed and enterprises are adapting. To give customers slick experiences and teams the technology to deliver. The road is long, but you’re closer than you think. Your business processes run through systems. Creating data at every step. Celonis recontrusts this data to generate Process Intelligence. A common business language. So AI knows how your business flows. Across every department, every system and every process. With AI solutions powered by Celonis enterprises get faster, more accurate insights. A new level of automation potential. And a step change in productivity, performance and customer satisfaction Process Intelligence is the missing piece in the AI Enabled tech stack.
Visit Celonis- https://celonis.com/eyeonai
Welcome to episode 149 of the ‘Eye on AI’ podcast. In this episode, host Craig Smith sits down with Alex Klein, the Cofounder & CEO of STEM and Kano Computing, who boasts an illustrious academic background from Cambridge and Yale.
Alex recalls his transition from journalism to creating STEM kits for children and unveils the inception story of the STEM player, a pioneering music product co-developed with Kanye West. As the conversation progresses, Alex delves deep into his academic experiences, focusing on his economic research at Cambridge, and his venture into the tech world. Emphasizing hands-on tech experiences, Alex discusses the manufacturing processes, and the origin story of KANO - designed to make Raspberry Pi more user-friendly.
Alex describes his unexpected encounter with Kanye West at the Consumer Electronics Show (CES) and their subsequent collaborations. The nuances of their flagship product, the STEM player, giving listeners an insight into how it revolutionizes music listening. Alex also gives us a sneak peek into their upcoming product, STEM 2, and sheds light on the company's future trajectory, emphasizing their commitment to redefining the music and audio space over the next three years.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
00:00 Preview, Celonis and Digimarc Ad
02:11 Origins of Kano & Alex's Stint with Journalism
04:47 The Evolution of Stem Player
12:55 Alex’ Educational & Philosophical Foundations
15:13 Kanye Collaboration
21:24 Deep Dive into Audio & STEM’s Technology
27:26 Future of Stem Player
37 02 Revolutionizing Music & Audio Experience Through Hardware
43:22 Innovations in AI & its Use Case Horizons
This epsiode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere.
If you want to do more and spend less like Uber and Cohere - take a free test drive of OCI at oracle.com/eyeonai
Welcome to episode 148 of the ‘Eye on AI’ podcast. In this episode, host Craig Smith sits down with Ahmed Imtiaz, a PhD student from Rice University working on deep learning theory and generative modeling. Ahmed is currently spearheading his research at Google, exploring the dynamics of text-to-image generative models.
In this episode, Ahmed sheds light on the concept of synthetic data, emphasizing the delicate equilibrium between real and algorithmically generated data. We navigate the complexities of model autophagy disorder (MAD) in generative AI,highlighting the potential pitfalls that models can fall into when overly reliant on their own generated data.
We also go through AI capabilities in lesser-explored languages, with Ahmed passionately sharing about his initiative "Bengali AI" aimed at advancing AI proficiency in the Bengali language. Ahmed introduces pioneering strategies to differentiate and manage synthetic data.
As we wrap up, Ahmed and I deliberate on the merits and challenges of open-sourcing formidable AI models. We grapple with the age-old debate of transparency versus performance, juxtaposed against the backdrop of potential risks.
Dive into the world of AI, synthetic data, and deep learning and join the discussion with Ahmed Imtiaz, as we tackle some of the most pressing issues the AI community is facing today.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Oracle ad
(02:56) Ahmed's Academic Journey
(04:14) The Challenge of Non-English AI
(06:34) Model Autophagy Disorder Explained
(14:40) Internet Content: AI's Growing Involvement
(21:08) The New Age of Data Collection
(26:28) AI’s Role in Protecting Digital Assets
(38:51) Open-Source vs Proprietary Model Debate
This episode is sponsored by Crusoe. Crusoe Cloud is a scalable, clean, high-performance cloud, optimized for AI and HPC workloads, and powered by wasted, stranded or clean energy. Crusoe offers virtualized compute and storage solutions for a range of applications - including generative AI, computational biology, and rendering.
Visit https://crusoecloud.com/ to see what climate-aligned computing can do for your business
This episode is sponsored by Celonis ,the global leader in process mining. AI has landed and enterprises are adapting. To give customers slick experiences and teams the technology to deliver. The road is long, but you’re closer than you think. Your business processes run through systems. Creating data at every step. Celonis recontrusts this data to generate Process Intelligence. A common business language. So AI knows how your business flows. Across every department, every system and every process.
Go to https:/celonis.com/eyeonai/ to find out more.
Welcome to episode 147 of the Eye on AI podcast. In this episode, host Craig Smith sits down with Yilna Du, a final year PhD student at MIT EECS with a background in research at leading institutions like OpenAI, FAIR, and Google Deepmind.
Yilun's extensive expertise spans generative models, decision making, robot learning, and embodied agents, making him a valuable voice in the AI domain.
Our conversation kicks off with a brief on Yilun's academic journey, leading into a deep dive into Reinforcement Learning with AI feedback (RLHF) - its history, inception, and challenges. We then touch upon the effectiveness of RLHF, the intriguing concept of multi-agent debate, and the PAPES procedure.
Craig and Yilun further explore the vast realm of AI, debating the gaps between open-source and proprietary models, the need for more compute resources, and the future of robotics interlaced with AI. Yilun provides a glimpse into his vision of decentralized AI systems, contrasting the industry's commercial trajectory with academia.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview, Celonis and Crusoe Ad
(04:06) Yilun's Academic Background
(05:52) Origin and Applications of RLHF
(12:16) ROHF and the Multi-Agent Debate Method
(17:32) AI Model Interaction without Human Intervention?
(20:41) Applicability and Inconsistency Detection
(28:43) The Future of AI Training
(45:26) Robotics and Decentralized AI Systems
This episode is sponsored by Celonis ,the global leader in process mining. AI has landed and enterprises are adapting. To give customers slick experiences and teams the technology to deliver. The road is long, but you’re closer than you think. Your business processes run through systems. Creating data at every step. Celonis recontrusts this data to generate Process Intelligence. A common business language. So AI knows how your business flows. Across every department, every system and every process. With AI solutions powered by Celonis enterprises get faster, more accurate insights. A new level of automation potential. And a step change in productivity, performance and customer satisfaction Process Intelligence is the missing piece in the AI Enabled tech stack.
Go to https:/celonis.com/eyeonai to find out more. Welcome to episode 146 of the Eye on AI podcast. In this episode, host Craig Smith sits down with Viren Jain, a leading Research Scientist at Google in Mountain View, California. Viren, at the helm of the Connectomics team, has pioneered breakthroughs in synapse-resolution brain mapping in collaboration with esteemed institutions such as HHMI, Max Planck, and Harvard.
The conversation kicks off with Jain introducing his academic journey and the evolution of connectomics – the comprehensive study of neural connections in the brain. The duo delves deep into the challenges and advancements in imaging technologies, comparing their progression to genome sequencing. Craig probes further, inquiring about shared principles across organisms, the dynamic behavior of the brain, and the role of electron microscopes in understanding neural structures.
The dialogue also touches upon Google's role in the research, Jain's collaborative ventures, and the potential future of AI and connectomics. Viren also shares his insights into neuron tracing, the significance of combining algorithm predictions, the zebra finch bird's song-learning mechanism, and the broader goal of enhancing human health and medicine.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview, Introduction and Celonis
(06:45) Viren’s Academic and Professional Journey
(13:17) AI’s Technological Progress and Challenges
(22:20) Deep Dive into Connectomics
(39:20) Google's Role in AI
(44:16) Natural Learning vs. AI Algorithms
(57:32) Brain Mapping: Present and Future
(01:00:33) Brain Studies for Medical Advancement
(01:06:05) Final Reflections and Celonis ad
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
On episode #145 of Eye on AI, Craig Smith sits down with Riley McCormack, President and CEO of Digimarc, pioneers in digital watermarking and cloud-based product data.
In this episode, we explore the critical role of digital watermarking in securing our digital assets, especially amidst the surging influence of AI. Riley guides us through the potential risks and benefits this technology brings to the forefront as AI continues to transform our digital world.
We then navigate the intricate territories of NFTs and distributed ledger technology, understanding how digital watermarking is reshaping these fields by ensuring trust and authenticity. Our discussion also delves into the Digital Millennium Copyright Act of 1997, highlighting its relevance in upholding copyrights and fostering trust within the digital stratosphere.
We conclude with a look at how digital watermarking impacts content creation and its role in shaping a secure and sustainable digital future, from collaborations with central banks to innovative products like Digimarc Recycle.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
00:00 Preview, Introduction and Shopify
03:05 Introduction to Digital Watermarking
07:01 Evolution of Digital Watermarking
14:21 Digimarc's Role in Digital Watermarking
21:13 Exploring the Protection Of Digital Content
28:56 Key Characteristics of Digital Watermarking
35:12 Application and Implementation of Digital Watermarking
42:46 Watermarking in Blockchain
49:11 What is Digimarc Validate?
01:03:01 Outro and Shopify
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at NetSuite.com/EYEONAI
On episode #144 of Eye on AI, Craig Smith sits down with Matt Hicks, President and CEO of Red Hat, a leading provider of enterprise open source software solutions.
In this episode, Matt takes us through the evolution of Linux and the rise of the open source models. We explore how Red Hat's long-term support and predictable life cycles have empowered companies to embrace Linux. Additionally, we delve into the transformative potential of deploying open source software alongside proprietary solutions and examine the challenges and opportunities that lie ahead for open source in the realm of generative AI.
To wrap things up,as we discuss the importance of efficiency, cost constraints, and specialized models for businesses, all while navigating the ongoing debate on general-purpose AI and the risks and rewards it brings.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview,Introduction & Netsuite
(03:11) The Role of OS in Tech
(08:06) Red Hat, Open Source, and Generative AI
(16:12) Large Language Models and Building Foundations
(24:18) AI: Commoditization, Frontier, & Hardware Predictions
(32:24) Open Source AI a Dual-Edged Sword?
(40:30) Regulatory Aspects & Red Hat's Future Directions
(48:36) IBM's Acquisition of Red Hat
(55:21) Outro & Netsuite by Oracle
This episode is sponsored by Crusoe. Crusoe Cloud is a scalable, clean, high-performance cloud, optimized for AI and HPC workloads, and powered by wasted, stranded or clean energy. Crusoe offers virtualized compute and storage solutions for a range of applications - including generative AI, computational biology, and rendering.
Visit crusoecloud.com to see what climate-aligned computing can do for your business.
On episode #143 of Eye on AI, Craig Smith sits down with Scott Aaronson, Schlumberger Centennial Chair of Computer Science at The University of Texas and director of its Quantum Information Center.
In this episode, we cut through the quantum computing hype and explore its profound implications for AI. We reveal the practicality of quantum computing, examining how companies are leveraging it to solve intricate problems, like vehicle routing, using D-Wave systems. Scott and I delve into the distinctions between quantum annealing and Grover-type speedups, shedding light on the potential of hybrid solutions that blend classical and quantum elements.
Shifting gears, we delve into the synergy between quantum computing and AI safety. Scott shares insights from his work at OpenAI, particularly a project aimed at fine-tuning language models like GPT for detecting AI-generated text, highlighting the implications of such advanced AI technology's potential misuse.
If you enjoyed this podcast, please consider leaving a 5-star rating on Spotify and a review on Apple Podcasts.
Craig Smith's Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(04:13) Demystifying Quantum Computing
(16:04) Leveraging Quantum Computers for Optimization
(31:01) What is Quantum Computing?
(42:40) Advancements and Challenges in Quantum Computing
(54:57) Machine Learning and AI Safety
This episode is sponsored by Celonis, the global leader in process mining. AI has landed and enterprises are adapting. To give customers slick experiences and teams the technology to deliver. The road is long, but you’re closer than you think.
Your business processes run through systems. Creating data at every step. Celonis recontrusts this data to generate Process Intelligence. A common business language. So AI knows how your business flows. Across every department, every system and every process. With AI solutions powered by Celonis enterprises get faster, more accurate insights. A new level of automation potential. And a step change in productivity, performance and customer satisfaction Process Intelligence is the missing piece in the AI Enabled tech stack.
Go to https:/celonis.com/eyeonai to find out more. On episode #141 of Eye on AI, Craig Smith sits down with Arjun Subramonian, a PhD student hailing from UCLA, with a focus on AI fairness and ethics. Arjun's work encompasses the intricate intersections of machine learning, algorithmic fairness, social justice, and ethics, all while ensuring inclusivity and equity in the realm of technology.
In this episode, we embark on a journey through the power of technology, exploring the potential biases in tech development. Arjun shares his personal journey from Silicon Valley to academia, shedding light on the challenges faced as a transgender researcher.
Arjun guides us through the ways technology can have a positive impact, from using neo-pronouns to fostering inclusive environments for the queer community. We also venture into the complexities of democratizing AI research, the risks of AI misuse, and the limitations of the scientific method.
Our conversation wraps up by emphasizing the importance of inclusivity and equity in the global context, underlining the need for cross-globe communication in building a more inclusive, equitable technology landscape.
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
00:00 Preview and Celonis Ad
03:12 Promoting LGBTQ+ Inclusion in AI
15:29 Decentralized Organizations
22:29 Pitfalls of AI and Academia
30:59 AI Evolution and Challenges of Inclusion
38:26 Intersectionality and Inclusivity in AI
45:20 Celonis
This episode is sponsored by DataStax, the real-time AI company. With DataStax, any enterprise can mobilize real-time data and quickly build smart, high-growth applications at unlimited scale, on any cloud. Companies building real-time generative AI apps can leverage the DataStax vector search capabilities to build LLM, AI assistant, and more. Sign up now at https://bit.ly/3sHUdGx On episode #141 of Eye on AI, Craig Smith sits down with Peter Voss, founder, CEO, and Chief Scientist of Aigo.ai. Join us as we take a deep dive into the world of artificial general intelligence (AGI)
In this episode we embark on Peter's remarkable journey, from his roots as an electronics engineer to his significant role in the pursuit of AGI. Discover how his vision differs from mainstream AI approaches, leaning on cognitive architectures and graph knowledge bases.
Ever wondered about the immense potential of real-time learning in AGI? We unearth the secrets behind teaching a system general knowledge and enhancing its cognitive abilities. Dive into the concept of life logging and personalized AI assistants, gaining fresh insights into how AI can adapt and learn on the fly.
We wrap things up with a discussion on the challenges of funding AGI projects and explore the competitive landscape in the realm of chatbots and large language models. Get an inside look at Aigo.ai’s customer base and pricing strategy.
Peter Voss’s LinkedIn: https://www.linkedin.com/in/vosspeter/
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
00:00 Preview and Data Stax
02:19 Starting an AI Company
07:26 What are Cognitive Architectures?
12:19 Knowledge Graphs in Aigo.ai
15:20 AI Personal Assistants
21:47 The Future of AGI
28:01 Challenges and Limitations of Current AI Models
36:55 Approaches to AGI Development
46:11 Development and Progress Toward AGI
58:08 The Importance of AGI and Collaboration
This episode is sponsored by MindStudio by YouAi. MindStudio is the best way to build an AI business. Start driving some serious revenue before everyone else. Mind Studio allows you to use conversational language to program incredibly powerful AI tools. No coding knowledge is needed to start your AI business.
Sign up now- https://bit.ly/MindStudioEyeonAI
On episode #139 of Eye on AI , Craig Smith sits down with Isabelle Guyon, a pioneer in the world of machine learning and pattern recognition, and Chair Professor at the University of Paris-Saclay. Isabelle Guyon, renowned for her groundbreaking work with Vladimir Vapnik and Bernhard Boser, has made significant contributions to support-vector machines (SVMs), artificial neural networks, and bioinformatics.
In this episode, we delve into SVMs, a technique that efficiently classifies data by maximizing margins, with applications spanning image classification, text classification, and bioinformatics.
We also explore maximum margin classifiers in the biomedical field, uncovering their unique approach to category distinction. Learn about weighted sum usage and their adaptability based on available data. Discover how maximum margin classifiers apply to labeled and unlabeled data, for both classification and regression tasks.
We wrap things up by discussing the promising prospects of chatbots and language models. Isabelle Guyon shares valuable insights on data preprocessing, bias adjustment methods, and the fusion of SVMs with deep learning to address contemporary challenges.
Isabelle Guyon’s LinkedIn: https://www.linkedin.com/in/isabelle-guyon-aa371170
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview (00:52) Introduction and MindStudio by YouAi (04:55) Machine Learning Techniques (15:15) Classification Methods in Biomedical Applications (22:40) Support Vector Machines and Kernel Methods (36:45) Future of Chatbots and Language Models (41:08) Unsupervised Learning in Deep Learning Importance (45:53) Outro and MindStudio by YouAi
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. It’s the leading commerce platform designed for a business of any size. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at http://shopify.com/eyeonai
On episode #139 of Eye on AI , Craig Smith sits down with Dmitry Shapiro, Founder of YouAi and CEO of GoMeta. Dmitry Shapiro is no stranger to the tech industry. With an impressive track record, he has made significant contributions to companies like Google, MySpace, and now, he's leading the charge at YouAi.
We start by exploring the groundbreaking concept behind YouAi, a company poised to revolutionize how we interact with artificial intelligence.
Education and content generation are domains where AI's potential can be unleashed in a transformative way. Dmitri reveals how AI could serve as a personal 'mind reader', bridging knowledge gaps and personalizing education like never before.
The spotlight then turns to Mind Studio, YouAi's ingenious tool that empowers users to create AI models without coding. Dmitry also unveils AI tools that simplify parenting.
As we near the end of our conversation, we revisit the concept of mind indexing and explore AI assistants, recommendation systems, and the power of asking questions to decode ambiguity.
Dmitry Shapiro LinkedIn: https://www.linkedin.com/in/dmitry-shapiro-a2b1
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(02:00) Shopify
(04:11) Dmitry Shapiro’s Early Career
(11:29) AI in Education?
(18:20) AI’s Role in Content Creation
(25:24) Customizing AI Applications
(36:26) Leveraging The Right LLMs
(44:54) AI Assistants Explained
(53:22) What is Mind Indexing?
(56:19) Shopify
This episode is sponsored by MindStudio by YouAi. MindStudio is the best way to build an AI business. Start driving some serious revenue before everyone else. Mind Studio allows you to use conversational language to program incredibly powerful AI tools. No coding knowledge is needed to start your AI business.
Sign up now- https://youai.ai/mindstudio
On episode #138 of Eye on AI. Craig Smith sits down with Dan O'Connell, the Chief AI and Strategy Officer at Dialpad and a seasoned expert in the world of AI-driven business communications.
Check out Dialpad- https://www.dialpad.com/
Currently serving as a member of Dialpad's Board of Directors, Dan's impressive career includes leadership roles at TalkIQ, AdRoll, and an 8-year stint at Google in key sales positions.
During our conversation, Dan takes us through Dialpad's AI-driven transformation of business communication. We explore the power of natural language processing, speech recognition, and large language models, enabling real-time transcription, call summaries, sentiment analysis, and virtual agents.
We also delve into the significance of sentiment analysis and the role of context, alongside debates on third-party APIs versus proprietary models, AI's unpredictability, and domain-specific model economics.
Our exploration continues with AI's impact on CRM, generative AI's insights, chatbot evolution, and cost-effective AI management.
Tune in to explore AIs impact on modern day business communication.
Dan O’Connell’s LinkedIn: https://www.linkedin.com/in/droconnell/
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(01:33) Mind Studio by YouAI
(03:46) Artificial Intelligence in Business Communications
(10:54) Building Sentiment Analysis and Custom Models
(19:35) Managing Costs and using AI in Business
(23:47) AI Disrupts CRM Market?
(30:56) Mind Studio by YouAI
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.
Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free at NetSuite.com/EYEONAI
On Episode #137 of Eye on AI, we dive deep into the world of data storage and its connection to AI. Join host Craig Smith as we unravel valuable insights shared by Raul Martynek, CEO of Data Bank, and explore the evolving landscape of data centers and their pivotal role in powering AI-driven innovations.
In this episode we discuss the history and significance of data centers, from their humble beginnings to their crucial role in today's data-driven world. Uncover how AI is driving the surging demand for data center capacity and the challenges the industry faces, including the impact of inflation and supply chain disruptions.
We talk about China's ambitious plans to bolster its semiconductor industry and its implications for data center growth. We also delve into the critical issue of power consumption driven by AI and its effects on global power grids
Join us for a thought-provoking discussion on the future of data centers and its synergy with AI.
Raul Martynek's LinkedIn: https://www.linkedin.com/in/raulmartynek
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(01:43) Netsuite by Oracle
(06:10) Growing Demands for Data Centers
(12:35) Data Centres Before AI
(24:08) Industry Challenges and Market Trends
(29:20) AI’s Impact on Power Consumption
(36:00) Future of Databank
(40:20) AIs Impact on Data Centers
(44:34) Podcast Wrap-Up and Netsuite by Oracle
This episode is sponsored by MindStudio by YouAi. MindStudio is the best way to build an AI business. Start driving some serious revenue before everyone else. Mind Studio allows you to use conversational language to program incredibly powerful AI tools. No coding knowledge is needed to start your AI business.
Sign up - YOUAI.AI/mindstudio
On episode #135 of the Eye on AI podcast, Craig Smith sits down with Diaa El All, founder and CEO of Soundful, an AI tool that generates royalty free background music at the click of a button for your videos, streams, podcasts and more.
From its integration with natural language processing to major industry partnerships, Soundful is paving the way for creators to not just produce, but also to monetize their content without worrying about being copyright striked.
As we venture into the future of music production and licensing, we question the impact of AI on the music industry and what it means on the business side as well. We breakdown how AI can enable musicians to boost their creativity by drawing inspiration from generative AI music.
Finally, we delve into the debate surrounding the role of imperfections in crafting a successful song. Imperfections have long been considered an integral part of what makes music human and relatable. Is perfection still the goal, or is there room for quirks and idiosyncrasies in AI-generated music?
Tune in as we unravel the transformative power of AI in reshaping the music industry and propelling its evolution.
Diaa El All LinkedIn: https://www.linkedin.com/in/diaaelall/
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Preview and Introduction
(01:36) MindStudio by YouAI
(03:53) Soundful’s Origin Story
(06:25) Can Creators Benefit From AI Music?
(16:24) Who uses Soundful?
(25:50) Future of Music Production and Licensing
(33:16) How AI Creates Music
(37:15) MindStudio by YouAI
This episode is sponsored by Shopify. Shopify is a commerce platform that allows anyone to set up an online store and sell their products. It’s the leading commerce platform designed for a business of any size. Whether you’re selling online, on social media, or in person, Shopify has you covered on every base. With Shopify you can sell physical and digital products. You can sell services, memberships, ticketed events, rentals and even classes and lessons.
Sign up for a $1 per month trial period at shopify.com/eyeonai On episode #134 of the Eye on AI podcast, Craig Smith sits down with Alex Zhavoronkov, founder and CEO of Insilico Medicine. Being at the forefront of cutting-edge drug discovery and longevity, Alex leverages the power of AI to develop novel drugs that could potentially extend our lifespan.In this episode we explore the unique tools Insilico Medicine uses to hypothesize protein targets and their links to diseases. Alex also gives us a peek into their automated robotic lab in Suzhou, China, which is expected to revolutionize drug development.
We delve deep into the world of drug discovery, with a special focus on Insilico Medicine’s tools, Pandomics, and Chemistry42, that are reshaping the field. Yet beyond the science, we also discuss the broader implications of tackling aging - from overpopulation to the strain on healthcare and social security systems.
Finally, we tackle the elephant in the room - the challenges in the pharmaceutical industry. Can AI expedite the drug discovery process? Alex certainly thinks so. We explore how AI can help identify partners quickly, streamline processes, and ultimately accelerate the development of drugs.
Join us as we unravel these mysteries and take you through the fascinating world of biotech, AI, and pharmaceutical research.
(0:00) Preview
(01:36) Shopify
(04:26) AI's Revolutionizing Drug Discovery
(06:11) Inside AI Pharmaceutical Research
(12:23) Use of AI tools in Medicine
(19:56) Biotech Synergy: Collaborative Exploration and Target Discovery
(37:17) Decoding Aging with AI
(46:52) Aging, Overpopulation, and Drug Breakthroughs
(1:07:33) Pharmaceutical Industry Challenges
(1:20:42) How AI is Advancing Longevity through Medicine
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. Download NetSuite’s popular KPI Checklist, designed to give you consistently excellent performance - absolutely free, at NetSuite.com/EYEONAI.
On episode #133 of the Eye on AI podcast, Craig Smith sits down with Michael Jordan. A revered scientist and distinguished professor at the University of California, Berkeley, Michael’s expertise spans machine learning, statistics, and artificial intelligence.
In this episode we explore the intricate landscape of deep learning, its statistical bedrock, and the myriad applications of machine learning methods. We dig deeper into the cloud computing revolution, ignited by deep learning, which has empowered behemoths like Amazon to streamline their logistics and commerce data.
The dialogue continues as we uncover the trends in deep learning, its role in the grand scheme of AI, and the persisting challenges in the domain.
We conclude by contemplating the repercussions of AI and optimization in complex systems. We examine its historical roots in the mid-20th century, its potential to replace jobs, and its application in various sectors such as financial markets, healthcare, and education.
(00:00) Preview
(01:00) Introduction
(01:36) NetSuite by Oracle
(03:53) Deep Learning Advancements in AI
(12:56) AI Optimization in Complex Systems
(28:53) Future of Machine Learning in Healthcare
(39:45) Privacy and Value in Multi-Agent Learning
(54:48) Learning Systems, Avatars, and Music Business
(1:02:20) Single Source of Truth for Business Owners
(1:04:28) NetSuite by Oracle
Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
On episode #132 of the Eye on AI podcast, Craig Smith sits down with Scott Downes, Chief Technology Officer at Invisible Technologies. We crack open the fascinating world of large language models (LLMs). What are the unique ways LLMs can revolutionize text cleanup, product classification, and more? Scott unpacks the power of technology like Reinforcement Learning for Human Feedback (RLHF) that expands the horizons of data collection. This podcast is a thorough analysis of the world of language and meaning. How does language encode meaning? Can RLHF be the panacea for complex conundrums? Scott breaks down his vision about using RLHF to redefine problem-solving. We dive into the vexing concept of teaching a language model through reinforcement learning without a world model. We discuss the future of the human workforce in AI, hear Scott’s insights on the potential shift from labellers to RLHF workers. What implications does this shift hold? Can AI elevate people to work on more complicated tasks? From exploring the economic pressure companies face to the potential for increased productivity from AI, we break down the future of work. (00:00) Preview and introduction (01:33) Generative AI’s Dirty Little Secret (17:33) Large Language Models in Problem Solving (23:24) Large Language Models and RLHF Challenges (30:07) Teaching Language Models Through RLHF(35:35) Language Models’ Power and Potential(53:00) Future of Human Workforce in AI(1:03:10) AI Changing Your World Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to episode #131 of the Eye on AI podcast with Andrew Ng. Get ready to challenge your perspectives as we sit down with Andrew Ng. We navigate the widely disputed topic of AI as a potential existential threat, with Andrew assuring us that, with time and global cooperation, safety measures can be built to prevent disaster. He offers insight into the debates surrounding the harm AI might cause, including the notions of AI as a bio-weapon and the notorious ‘paper clip argument’. Listen as Andrew debunks these theories, delivering an interesting argument for why he believes the associated risks are minimal.Onwards, we venture into the intriguing realm of AI’s capability to understand the world, setting the stage for a conversation on how we can objectively assess their comprehension. We explore the safety measures of AI, drawing parallels with the rigour of the aviation industry, and contemplate on the consensus within the research community regarding the danger posed by AI. (00:00) Preview (01:08) Introduction (02:15) Existential risk of artificial intelligence (05:50) Aviation analogy with artificial intelligence (10:00) The threat of AI & deep learning (13:15) Lack of consensus in AI dangers (18:00) How AI can solve climate change (24:00) Landing AI and Andrew Ng (27:30) Visual prompting for images Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Our sponsor for this episode is Masterworks, an art investing platform. They buy the art outright, from contemporary masters like Picasso and Banksy, then qualify it with the SEC, and offer it as an investment. Net proceeds from its sale are distributed to its investors. Since their inception, they have sold over $45 million dollars worth of artwork And so far, each of Masterworks’ exits have returned positive net returns to their investors.
Masterworks has over 750,000 users, and their art offerings usually sell out in hours, which is why they’ve had to make a waitlist.
But Eye on AI viewers can skip the line and get priority access right now by clicking this link: https://www.masterworks.art/eyeonai
Purchase shares in great masterpieces from artists like Pablo Picasso, Banksy, Andy Warhol, and more. See important Masterworks disclosures: https://www.masterworks.com/cd “Net Return" refers to the annualized internal rate of return net of all fees and costs, calculated from the offering closing date to the date the sale is consummated. IRR may not be indicative of Masterworks paintings not yet sold and past performance is not indicative of future results. Returns shown are 4 examples of midrange returns selected to demonstrate Masterworks performance history. Returns may be higher or lower. Investing involves risk, including loss of principal.
Welcome to episode #130 of Eye on AI with Mathew Lodge. In this episode, we explore the world of reinforcement learning and code generation. Mathew Lodge, the CEO of Diffblue, shares insights into how reinforcement learning fuels generative AI. As we explore the intricacies of reinforcement learning, we uncover its potential in game playing and guiding us towards solutions. We shed light on the products that it powers, such as AlphaGo and AlphaDev. However, we also address the challenges of large language models and explain why they may not be the ultimate solution for code generation. In the last part of our conversation, we delve into the future of language models and intelligence. Mathew shares valuable insights on merging no-code and low-code solutions. We confront the skepticism of software developers towards AI for code products and the task of articulating program outcomes. Wrapping up, we reflect on the evolution of programming languages and the impact of abstraction on machine learning.
(00:00) Preview & sponsorship (01:51) Reinforcement Learning and Code Generation (04:39) Reinforcement Learning and Improving Algorithms (15:32) The Challenges of Large Language Models(23:58) Future of Language Models and Intelligence (35:50) Challenges and Potential of AI-generated Code (48:32) Programming Language Evolution and Higher-Level Languages
Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to episode #129 of Eye on AI with Alexandra Geese. Navigating the complex waters of the European Union’s AI Act is no simple task. Yet, that’s exactly what Alexandra Geese, a member of the European Parliament, and I venture to do in this conversation. Alexandra’s insights into the AI Act, its four defined categories of AI applications, and its current negotiation phase with the European Council and the European Commission are illuminating. We delve into the Act’s essential mission: ensuring AI serves humanity, while also exploring the influence of powerful players in the AI industry on the EU’s legislation. As our journey deepens, we tackle a range of crucial issues underpinning the Act. Alexandra and navigate through potential economic implications for those who rely on copyright legislation, and the risk of Europe falling behind in AI implementation if the Act is too restrictive. We also touch on the involvement of major American AI firms in the Act’s finalization process, and implications for copyrighted material. We dive into the ongoing debates shaping the legislation and the enforcement of the law, once passed. Alexandra shares her thoughts on potential fines for violations, different AI zones, and the possibility of the US following Europe’s lead in AI legislation. We wrap up with a deep reflection on the environmental impact of AI, the power held by few companies, and our collective responsibility as AI reshapes the world.
(00:00) Preview
(00:52) Introduction
(03:10) Alexandra Geese background in digital legislation
(04:00) The AI act: the explanation and details
(08:00) The foundations of corporations for AI regulation
(13:00) Copyright regulation and impacts of creativity
(17:00) We need AI that serves humanity
(21:30) Are foundation models high risk to society?
(25:00) Should people be worried about investing in AI?
(30:45) What is dynamic AI regulation?
(36:10) What is the timeline for AI regulation?
(38:50) What penalties will be applied to AI regulation?
(44:30) Will US & EU merge on AI regulation?
(50:30) How to solve AI hallucinations
Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Found is a show about founders and company-building that features the change-makers and innovators who are actually doing the work. Each week, TechCrunch Plus reporters, Becca Szkutak and Dom-Madori Davis talk with a founder about what it’s really like to build and run a company—from ideation to launch. They talk to founders across many industries and their conversations often lead back to AI as many startups start to implement AI into what they do. New episodes of Found are published every Tuesday and you can find them wherever you listen to podcasts.
Found podcast: https://podlink.com/found
Yoshua Bengio, the legendary AI expert, will join us for Episode 128 of Eye on AI podcast. In this episode, we delve into the unnerving question: Could the rise of a superhuman AI signal the downfall of humanity as we know it? Join us as we embark on an exploration of the existential threat posed by superhuman AI, leaving no stone unturned. We dissect the Future of Life Institute’s role in overseeing large language model development. As well as the sobering warnings issued by the Centre for AI Safety regarding artificial general intelligence. The stakes have never been higher, and we uncover the pressing need for action. Prepare to confront the disconcerting notion of society’s gradual disempowerment and an ever-increasing dependency on AI. We shed light on the challenges of extricating ourselves from this intricate web, where pulling the plug on AI seems almost impossible. Brace yourself for a thought-provoking discussion on the potential psychological effects of realizing that our relentless pursuit of AI advancement may inadvertently jeopardize humanity itself. In this episode, we dare to imagine a future where deep learning amplifies system-2 capabilities, forcing us to develop countermeasures and regulations to mitigate associated risks. We grapple with the possibility of leveraging AI to combat climate change, while treading carefully to prevent catastrophic outcomes. But that’s not all. We confront the notion of AI systems acting autonomously, highlighting the critical importance of stringent regulation surrounding their access and usage.
(00:00) Preview
(00:42) Introduction
(03:30) Yoshua Bengio's essay on AI extinction
(09:45) Use cases for dangerous uses of AI
(12:00) Why are AI risks only happening now?
(17:50) Extinction threat and fear with AI & climate change
(21:10) Super intelligence and the concerns for humanity
(15:02) Yoshua Bengio research in AI safety
(29:50) Are corporations a form of artificial intelligence?
(31:15) Extinction scenarios by Yoshua Bengio
(37:00) AI agency and AI regulation
(40:15) Who controls AI for the general public?
(45:11) The AI debate in the world
Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to Episode 127 of the Eye on AI podcast with host Craig Smith and guest Clemens Mewald. In this episode, we dive into the world of AI and its transformative impact on industries. Join us as we explore Instabase, the cutting-edge company led by our guest, a seasoned engineer with an impressive background at Google Brain, Databricks, and now Instabase. Discover how Instabase is revolutionizing automation and content capture across various organizations using AI-driven methods. Uncover the mission behind Instabase and delve into the intricate details of AI Hub, a groundbreaking marketplace for AI models and products. We explore the limitations of model repositories and marketplaces, particularly in large-scale applications. As we compare AI Hub with the AWS Marketplace, we touch upon the abundance of low-code app development solutions in the market, highlighting Accio’s rich SaaS offerings and generative AI apps as an industry benchmark. No discussion about AI would be complete without delving into the potential of GPT-4, a powerful language model capable of accurately predicting task outcomes. Join us on this ride as we uncover the heart of AI, its revolutionary applications, and its transformative power across industries. (00:00) Preview (00:38) Introduction (01:22) Clemens background and Google Brain (02:44) Instabase and solving unstructured data problems (07:40) How Instabase works and different use cases (13:20) The long term vision of the AI Hub (17:12) Blockchain based marketplace for AI models (21:50) AWS Marketplace compared to Instabase (24:05) Generative AI and no code web apps (31:05) Biggest concerns of using Open AI for security (35:40) Considerations of use cases of GPT4 (40:00) LLMs acting as knowledge and reasoning engines (46:40) Using different AI models based on different tasks (51:00) Leveraging other AI models for compatibility (54:14) How to get people to start using Instabase
Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to episode #126 of Eye on AI with Craig Smith and Noam Chomsky. Are neural nets the key to understanding the human brain and language acquisition? In this conversation with renowned linguist and cognitive scientist Noam Chomsky, we delve into the limitations of large language models and the ongoing quest to uncover the mysteries of the human mind. Together, we explore the historical development of research in this field, from Minsky’s thesis to Jeff Hinton’s goals for understanding the brain. We also discuss the potential harms and benefits of large language models, comparing them to the internal combustion engine and its differences from a gazelle running. We tackle the difficult task of studying the neurophysiology of human cognition and the ethical implications of invasive experiments. As we consider language as a natural object, we discuss the works of notable figures such as Albert Einstein, Galileo, Leibniz, and Turing, and the similarities between language and biology. We even entertain the possibility of extraterrestrial language and communication. Join us on this thought-provoking journey as we explore the intricacies of language, the brain, and our place in the cosmos. (00:00) Preview
(00:43) Introduction
(01:54) Noam Chomsky’s neural net ideology & criticisms
(6:58) Jeff Hinton & Noam Chomsky’s: How the brain works
(10:05) Correlation between neural nets and the brain
(11:11) Noam Chomsky’s reaction to Chat-GPT & LLMs
(15:21) Exploring the mechanisms of the brain
(19:00) What do we learn from chatbots?
(22:30) What are impossible languages?
(26:45) Generative AI doesn’t show true intelligence?
(28:40) Is there a danger of AI becoming too intelligent?
(31:30) Can AI language models become sentient?
(36:40) Turing machine and neural nets experimentations
(42:40) Non-evasive procedures for understanding the brain
(45:54) Does Noam Chomsky still work on understanding the brain?
(49:33) Is Noam Chomsky excited about the future of neural nets?
(55:30) Albert Einstein and Galileo’s principles
(55:40) Is there an extraterrestrial language model?
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to episode 125 of Eye on AI, where we embark on a journey into the realm of Generative AI. In this episode, we have the pleasure of chatting with Pascal Weinberger, co-founder and CEO of Bardeen AI, who takes us through the evolution of AI and its incredible potential for creativity and professional endeavors. Join us as we venture behind the scenes of Telefonica’s Moonshot Lab, where AI projects in healthcare, energy, and city planning are explored. Discover the fascinating ideas and initiatives that have emerged, including the birth of a mental health company, as we uncover the immense impact of Generative AI. During our conversation, we’ll delve into the nuances of Generative AI technology, exploring how industry giants like Microsoft and Google are harnessing its power to enhance their products. We’ll also discuss the strategies and challenges faced by companies in the competitive Generative AI market, with a strong focus on meeting the needs of end users. We’ll also tackle the ongoing debates surrounding the risks and benefits of AI technology, ensuring you stay ahead of the curve in this ever-evolving world of Generative AI. Tune in and join us as we unravel the secrets of Generative AI, paving the way for a future where creativity and productivity reach new heights.
(00:00) Preview (00:24) Pascal's Weinberger background in Telefonica (08:28) Machine learning & AI with Pascal's Weinberger (10:28) How Pascal's Weinberger founded Bardeen AI (13:25) Generate AI MVP for Bardeen AI (17:21) Generative AI applications and OpenAI competition (22:24) Competition in the AI space (25:24) Big tech companies vs. startups in AI (31:46) The future of AI and transformer algorithm (32:41) Bardeen AI features and functionality (46:24) AutoGPT problems and considerations (50:54) Risk of AI & misuse of commands
Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to episode #124 of the Eye on AI podcast, where we bring you the latest insights into the fascinating world of artificial intelligence. In this episode, Craig Smith is joined by Sina Kian, General Counsel and COO at Aleo, as they dive deep into the revolutionary realm of zero-knowledge proofs. Join us as we explore the incredible potential of zero-knowledge proofs in safeguarding sensitive data while leveraging it for machine learning and AI applications. Sina Kian provides shares how this innovative technology can reshape privacy, digital identity, and even social media authentication. During this conversation, we delve into the power of privacy-preserving blockchain technology and its far-reaching impact across industries. Discover how Aleo is at the forefront of making digital identity more secure and how it can be seamlessly integrated across platforms without compromising sensitive information. We examine the future of machine learning and AI, unraveling the role that digital identity plays in accessing products and content based on location. As we venture into the depths of the social media landscape, we also explore the risks and rewards associated with user data and privacy. Gain insights into how privacy-preserving technology can shield user information and authenticate data and content without compromising privacy. This conversation will discusses the potential of zero-knowledge proofs and privacy-preserving technology, offering a glimpse into how they will shape the future of machine learning and AI. (00:00) Preview
(00:41) Introduction
(02:28) Sina Kian's background in Aleo & blockchain
(05:49) Blockchain's integration with AI & machine learning
(11:48) How data is protected in blockchain technology
(12:25) Use cases of encryption with Aleo
(18:53) How Aleo works with an open source protocol
(24:13) Aleo's progress in developing its open source project
(31:13) Why social media platforms capture your data
(34:16) How can you find widespread adoption?
(35:43) How the government are getting involved in digital identity
(41:53) How data privacy integrates to Web 3.0
(45:15) Blockchain's implementation in the real world
(48:43) Next steps from Aleo
(53:53) Social media interaction with privacy
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to Eye on AI, the podcast that keeps you informed about the latest trends, obstacles, and possibilities in the realm of artificial intelligence. In this episode, we have the privilege of engaging in a thought-provoking discussion with Aidan Gomez, an exceptional AI developer and co-founder of Cohere. Aidan’s passion lies in enhancing the efficiency of massive neural networks and effectively deploying them in the real world. Drawing from his vast experience, which includes leading a team of researchers at For.ai and conducting groundbreaking research at Google Brain, Aidan provides us with unique insights and anecdotes that shed light on the AI landscape. During our conversation, Aidan explains his collaboration with the legendary Geoffrey Hinton and their remarkable project at Google Brain. We delve into the intricate architecture of AI systems, demystifying the construction of the transformative transformer algorithm. Aidan generously shares his knowledge on the creation of attention within these models and the complexities of scaling such systems. As we explore the fascinating domain of language models, Aidan discusses their learning process, bridging the gap between code and data. We uncover the immense potential of these models to suggest other large-scale counterparts. We gain invaluable insights into Aidan’s journey as a co-founder of Cohere, an innovative platform revolutionizing the utilization of language technology. Tune in to Eye on AI now to immerse yourself in a captivating conversation that will expand your understanding of this ever-develop field. (00:00) Preview (00:33) Introduction & sponsorship (02:00) Aidan's background with machine learning & AI (05:10) Geoffrey Hinton & Aidan Gomez working together (07:55) Aidan Gomez & Google Brain's project (12:53) Aidan's role in building AI architecture (15:25) How the transformer algorithm is built (18:25) How do you create attention? (20:40) How do you scale the model? (25:10) How language models learn from code and data (29:55) Did you know the potential of the project? (34:15) Can LLMs suggest other large models? (36:45) How Aidan Gomez started Cohere (41:10) How do people use Cohere? (46:50) Examples of language technology models (48:40) How Cohere handles hallucinations (52:53) The dangers of AI Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to Eye on AI, the podcast that explores the latest developments, challenges, and opportunities in the world of artificial intelligence. In this episode, we sit down with Connor Leahy, an AI researcher and co-founder of EleutherAI, to discuss the darker side of AI. Connor shares his insights on the current negative trajectory of AI, the challenges of keeping superintelligence in a sandbox, and the potential negative implications of large language models such as GPT4. He also discusses the problem of releasing AI to the public and the need for regulatory intervention to ensure alignment with human values. Throughout the podcast, Connor highlights the work of Conjecture, a project focused on advancing alignment in AI, and shares his perspectives on the stages of research and development of this critical issue. If you’re interested in understanding the ethical and social implications of AI and the efforts to ensure alignment with human values, this podcast is for you. So join us as we delve into the darker side of AI with Connor Leahy on Eye on AI. (00:00) Preview
(00:48) Connor Leahy’s background with EleutherAI & Conjecture
(03:05) Large language models applications with EleutherAI
(06:51) The current negative trajectory of AI
(08:46) How difficult is keeping super intelligence in a sandbox?
(12:35) How AutoGPT uses ChatGPT to run autonomously
(15:15) How GPT4 can be used out of context & negatively
(19:30) How OpenAI gives access to nefarious activities
(26:39) The problem with the race for AGI
(28:51) The goal of Conjecture and advancing alignment
(31:04) The problem with releasing AI to the public
(33:35) FTC complaint & government intervention in AI
(38:13) Technical implementation to fix the alignment issue
(44:34) How CoEm is fixing the alignment issue
(53:30) Stages of research and development of Conjecture
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
In this podcast, we sit down with Danny Tobey, an attorney with the global law firm DLA Piper, to discuss the changing legal dynamics surrounding artificial intelligence. As one of the leading experts in the field, Danny provides valuable insights into the current state of legislation and regulation, the efforts of regulatory bodies like the Federal Trade Commission in tackling issues related to AI, and how the law firm of the future will look as AI continues to transform the economy. With the growing impact of AI on all aspects of our lives, the legal profession is facing unique challenges and opportunities. Danny brings a wealth of knowledge and experience to the conversation, having worked with clients in industries ranging from healthcare to financial services to consumer products. Throughout the podcast, Danny explores the ethical and legal implications of AI, as well as the ways in which AI is already reshaping the legal industry. He provides thoughtful perspectives on how the legal profession can adapt and evolve to meet the demands of an AI-driven economy, and the role that lawyers and regulatory bodies will play in shaping the future of this transformative technology. Whether you're a legal professional looking to stay on top of the latest developments in AI, or simply interested in the ways that AI is changing the legal landscape, this podcast is sure to offer valuable insights and food for thought. So join us as we dive deep into the intersection of law and artificial intelligence with Danny Tobey. Craig Smith Twitter: https://twitter.com/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI
In this episode of the Eye on A.I. podcast, host Craig Smith interviews Yoshua Bengio, one of the founding fathers of deep learning and a Turing Award winner. Bengio shares his insights on the famous pause letter, which he signed along with other prominent A.I. researchers, calling for a more responsible approach to the development of A.I. technologies. He discusses the potential risks associated with increasingly powerful A.I. models and the importance of ensuring that models are developed in a way that aligns with our ethical values. Bengio also talks about his latest research on world models and inference machines, which aim to provide A.I. systems with the ability to reason for reality and make more informed decisions. He explains how these models are built and how they could be used in a variety of applications, such as autonomous vehicles and robotics. Throughout the podcast, Bengio emphasises the need for interdisciplinary collaboration and the importance of addressing the ethical implications of A.I. technologies. Don’t miss this insightful conversation with one of the most influential figures in A.I. on Eye on A.I. podcast! Craig Smith Twitter: https://twitter.com/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI
Welcome to the latest episode of our podcast featuring Edo Liberty, an AI expert and former creator of SageMaker at Amazon’s AI labs. In this episode, Edo discusses how his team at Pinecone.io is tackling the problem of hallucinations in large language models like ChatGPT. Edo’s approach involves using vector embeddings to create a long-term memory database for large language models. By converting authoritative and trusted information into vectors, and loading them into the database, the system provides a reliable source of information for large language models to draw from, reducing the likelihood of inaccurate responses. Throughout the episode, Edo explains the technical details of his approach and shares some of the potential applications for this technology, including AI systems that rely on language processing. Edo also discusses the future of AI and how this technology could revolutionise the way we interact with computers and machines. With his insights and expertise in the field, this episode is a must-listen for anyone interested in the latest developments in AI and language processing. We have a new sponsor this week: NetSuite by Oracle, a cloud-based enterprise resource planning software to help businesses of any size manage their financials, operations, and customer relationships in a single platform. They've just rolled out a terrific offer: you can defer payments for a full NetSuite implementation for six months. That's no payment and no interest for six months, and you can take advantage of this special financing offer today at netsuite.com/EYEONAI Craig Smith Twitter: https://twitter.com/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI
In this podcast episode, Ilya Sutskever, the co-founder and chief scientist at OpenAI, discusses his vision for the future of artificial intelligence (AI), including large language models like GPT-4. Sutskever starts by explaining the importance of AI research and how OpenAI is working to advance the field. He shares his views on the ethical considerations of AI development and the potential impact of AI on society. The conversation then moves on to large language models and their capabilities. Sutskever talks about the challenges of developing GPT-4 and the limitations of current models. He discusses the potential for large language models to generate a text that is indistinguishable from human writing and how this technology could be used in the future. Sutskever also shares his views on AI-aided democracy and how AI could help solve global problems such as climate change and poverty. He emphasises the importance of building AI systems that are transparent, ethical, and aligned with human values. Throughout the conversation, Sutskever provides insights into the current state of AI research, the challenges facing the field, and his vision for the future of AI. This podcast episode is a must-listen for anyone interested in the intersection of AI, language, and society. Timestamps: (00:04) Introduction of Craig Smith and Ilya Sutskever. (01:00) Sutskever's AI and consciousness interests. (02:30) Sutskever's start in machine learning with Hinton. (03:45) Realization about training large neural networks. (06:33) Convolutional neural network breakthroughs and imagenet. (08:36) Predicting the next thing for unsupervised learning. (10:24) Development of GPT-3 and scaling in deep learning. (11:42) Specific scaling in deep learning and potential discovery. (13:01) Small changes can have big impact. (13:46) Limits of large language models and lack of understanding. (14:32) Difficulty in discussing limits of language models. (15:13) Statistical regularities lead to better understanding of world. (16:33) Limitations of language models and hope for reinforcement learning. (17:52) Teaching neural nets through interaction with humans. (21:44) Multimodal understanding not necessary for language models. (25:28) Autoregressive transformers and high-dimensional distributions. (26:02) Autoregressive transformers work well on images. (27:09) Pixels represented like a string of text. (29:40) Large generative models learn compressed representations of real-world processes. (31:31) Human teachers needed to guide reinforcement learning process. (35:10) Opportunity to teach AI models more skills with less data. (39:57) Desirable to have democratic process for providing information. (41:15) Impossible to understand everything in complicated situations. Craig Smith Twitter: https://twitter.com/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI
In this episode, Ben Sorscher, a PhD student at Stanford, sheds light on the challenges posed by the ever-increasing size of data sets used to train machine learning models, specifically large language models. The sheer size of these data sets has been pushing the limits of scaling, as the cost of training and the environmental impact of the electricity they consume becomes increasingly enormous. As a solution, Ben discusses the concept of “data pruning” - a method of reducing the size of data sets without sacrificing model performance. Data pruning involves selecting the most important or representative data points and removing the rest, resulting in a smaller, more efficient data set that still produces accurate results. Throughout the podcast, Ben delves into the intricacies of data pruning, including the benefits and drawbacks of the technique, the practical considerations for implementing it in machine learning models, and the potential impact it could have on the field of artificial intelligence. Craig Smith Twitter: https://twitter.com/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI
In this episode, Yann LeCun, a renowned computer scientist and AI researcher, shares his insights on the limitations of large language models and how his new joint embedding predictive architecture could help bridge the gap. While large language models have made remarkable strides in natural language processing and understanding, they are still far from perfect. Yann LeCun points out that these models often cannot capture the nuances and complexities of language, leading to inaccuracies and errors. To address this gap, Yann LeCun introduces his new joint embedding predictive architecture - a novel approach to language modelling that combines techniques from computer vision and natural language processing. This approach involves jointly embedding text and images, allowing for more accurate predictions and a better understanding of the relationships between original concepts and objects. Craig Smith Twitter: https://twitter.com/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI
In this episode, Terry Sejnowski, an AI pioneer, chairman of the NeurIPS Foundation, and co-creator of Boltzmann Machines, delves into the latest developments in deep learning and their potential impact on our understanding of the human brain. Terry Sejnowski begins by discussing the NeurIPS conference - one of the most significant events in the field of artificial intelligence - and its role in advancing research and innovation in deep learning. He shares insights into the latest breakthroughs in the field, including the repurposing of the sleep-wake cycle of Boltzmann Machines in Geoff Hinton's new Forward-Forward algorithm. Throughout the episode, Terry Sejnowski shares his expertise on the intersection of artificial intelligence and neuroscience, exploring how advances in deep learning may help us better understand the complexities of the human brain. He discusses how researchers are using AI techniques to study brain activity and the potential implications for fields such as medicine and psychology. Overall, this episode will be of particular interest to those interested in the latest developments in artificial intelligence and their potential applications in neuroscience and related fields. Craig Smith Twitter: https://twitter.com/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI
In this episode, Geoffrey Hinton, a renowned computer scientist and a leading expert in deep learning, provides an in-depth exploration of his groundbreaking new learning algorithm - the forward-forward algorithm. Hinton argues this algorithm provides a more plausible model for how the cerebral cortex might learn, and could be the key to unlocking new possibilities in artificial intelligence. Throughout the episode, Hinton discusses the mechanics of the forward-forward algorithm, including how it differs from traditional deep learning models and what makes it more effective. He also provides insights into the potential applications of this new algorithm, such as enabling machines to perform tasks that were previously thought to be exclusive to human cognition. Hinton shares his thoughts on the current state of deep learning and its future prospects, particularly in neuroscience. He explores how advances in deep learning may help us gain a better understanding of our own brains and how we can use this knowledge to create more intelligent machines. Overall, this podcast provides a fascinating glimpse into the latest developments in artificial intelligence and the cutting-edge research being conducted by one of its leading pioneers. Craig Smith Twitter: https://twitter.com/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI
To set the stage for some terrific conversations I have coming to you in the new year, in this episode we go back to some earlier conversations that talk about how we got to where we are in deep learning and how those early threads continue to lead innovation.
This week I talk to Bob Rogers, a Harvard trained astrophysicist who once built digital twins of black holes to better understand them, and now builds digital twins of supply chains to help make them more efficient and resilient.
Jonathon Reilly, co-founder of Akkio, a no-code AI platform, talks about how users with a web browser and an idea have the power to bring AI to life themselves without having to write code.
Moses Guttmann, founded ClearML, talks about the evolution of the MLOps industry over the past few years and ClearML's contribution to it.
Bratin Saha, head of Amazon's machine learning services, talks about Amazon's growing dominance in model building and deploying AI, about the company's SageMaker platform, and whether anyone can compete with the behemoth.
Peter Schrammel, one of the founders of Diffblue, an automated unit-test writing software company, speaks about the increasing automatic generation of code and how he sees such automation increasing the productivity of developers.
Michael Kearns, a computer scientist professor at the University of Pennsylvania and an Amazon scholar talks about differential privacy, how Amazon's research approach differs from its peers, and how AI will eventually permeate all aspects of our lives.
Jacki Morie, a senior XPRIZE advisor, talks about the ANA Avatar XPRIZE, a competition focused on creating a physical avatar system that will seamlessly transport human skills and experience to distant locations. The four-year competition is in its final stretch.
Aaron Patzer, founder of the personal finance app MINT and more recently founder of the AI-based healthcare company Vital, talks about keeping customer data private and the promise, giving emergency room patients information with AI and finding friendly solutions to anxiety-producing problems.
Rohit Prasad, Amazon's Senior Vice President and Head Scientist for Alexa, speaks about the development of conversational AI and virtual assistants and the merging of IoT sensor data into ambient intelligence - AI that is always present and immediately accessible.
Ken Washington, who leads Amazon's consumer robotics team, talks about the company's compact wheeled robot called Astro. Ken talked about Astro's evolution, it's popular and possible use cases, and what might be in store in the future.
Almammon Rasool Abdali, a machine-learning engineer and PhD student in Baghdad, is one of the more prominent members of Iraq's small but growing deep learning community. We talked about his work, which involves vision systems to detect violence, and about the state of artificial intelligence research and teaching in the country generally.
Oriol Vinyals, who leads DeepMind’s deep learning team, talks about AlphaCode, his group’s code-writing language model, and DeepMind’s winding road toward artificial general intelligence.
Andrew Ng, founder of Google Brain, Coursera and Landing AI, talks about his vision of data-centric AI, MLOps and the future of supervised vs unsupervised learning. The Eye on AI podcast is sponsored by ClearML.
Tom Siebel, founder and CEO of C3.ai talks about AI projects including military target acquisition and precision healthcare while musing about the dark side of our technological future. The Eye on AI podcast is sponsored by Clear.ML
Max Bileschi, a software engineer at Google Research, talks about his team’s application of convolutional neural networks to predict the function of amino acid sequences in a protein. Eye on AI is sponsored by Clear.ML.
Connor Leahy, one of the minds behind Eleuther AI and its open-source large language model, GPT-J, talks about the building such models and their implications for the future.
Robert O. Work, former Deputy Secretary of Defense and recently co-chairman of the National Security Commission on AI, talks about competition between the US and China to integrate AI into their military capabilities.
Stephen DeAngelis, head of Enterra Solutions, reminds us that so-called Old-Fashioned AI continues to be a powerful tool. He talked about leveraging knowledge bases, inference engines and symbolic logic to make decisions about large dynamic systems.
Andrew Feldman, one of the founders and CEO of Cerebras Systems, talks about the company's wafer-scale computer chip optimized for machine learning and about the network of chips that company has built that has as much computing power as a human brain.
Adobe’s head of research, Gavin Miller, talks about AI-enhanced creativity, guarding against manipulation of visual media and his own AI-enabled robot snakes.
Seth Dobrin, chief AI officer at IBM, talks about the company's tools to increase the trustworthiness, fairness and explainability of AI models.
This week, I talk to Ron Schmelzer and Kathleen Walch, founders of Cognilytica, a research, advisory, and education firm focused on artificial Intelligence. We talked about the rise of MLOps, data labeling, unsupervised learning and what it will take to get us to human-level artificial general intelligence.
This week I talk to the inimitable Ben Goertzel, about his non-profit foundation, SingularityNET, his work with the robotic head, Sophia, his talking Philip K. Dick avatar, his work in medical AI, his frustration over Big Tech's dominance of AI research and his own quest for AGI.
AI commentator and investor Kaifu Lee talks about his book AI 2041 in which he considers possible futures for humanity if deep learning applications develop as planned.
NSCAI staff Justin Lynch, Ryan Carpenter and Lance Lantier talk about how the 1986 Goldwater Nichols Act that reorganized the US military inspired the commission’s recommendations to reorganize the Department of Defense to drive adoption of emerging and disruptive technology capabilities.
NSCAI staff Christie Lawrence and Rama Elleru talk about how intellectual property protections play an unexpected role in guiding US innovation and contribute to the global competition with China for dominance in AI.
NSCAI staff Tess Deblanc-Knowles and Mike Garris talk about the steps the US government needs to take to foster AI innovation in the years ahead.
NSCAI staff Paul Leka and Christie Lawrence talk about forming an international emerging technology coalition to strengthen and coordinate the use of emerging technology for democratic ends.
NSCAI staff Mike Garris and Mike Jackson spoke about what needs to be done to lay the foundations for an AI-infused national security going forward.
NSCAI staff Aristotle Vainikos and Parker Wild spoke about the commission’s recommendations for establishing public-private innovation hubs around the country that can encourage and tap the entrepreneurial potential between the coasts and expand the participation of private enterprise in national security.
NSCAI staff Mike Jackson and Darren Wright talk about the commission’s recommendations for bringing the intelligence community up to speed with AI. They spoke about the organizational changes needed and the culture shift required to ensure that the intelligence community is integrating AI in its work.
NSCAI staff David Kumashiro and Courtney Barno talked about the commission’s recommendations on democratizing AI for the warfighter and enabling bottom-up AI innovation.
NSCAI staff Kevin McGuinness and Raina Davis talked about the commission’s recommendations for increasing public visibility about the government’s AI needs and lowering the barrier to entry for companies that want to help meet those needs.
NSCAI staff Chris Rice and Courtney Barno talk about what the US has to do to get up to speed on its AI military capabilities by 2025 in order to outpace our competitors, particularly China.
NSCAI staff Justin Lynch, Lance Lantier and Shaantam Chawla, talked about educating the warfighter for the AI era. They spoke about what kind of training warfighters need to effectively integrate AI, from commanders to infantry men and women and how that integration will change the nature of warfare and the military’s perception of itself in the years ahead.
Ylli Bajraktari, executive director of the National Security Commission on AI, talked about what he considers the most important recommendations in the commission’s final report and about the need for Congress and the White House to act swiftly to counter China’s concerted efforts to beat the US in deploying this critical technology around the world.
This week, I talk to Cade Metz, the New York Times' lead reporter on artificial intelligence, about his new book, “Genius Makers, the Mavericks Who Brought AI to Google Facebook and the World." The book focuses on some of the personalities and companies responsible for the current wave of AI innovation and touches on some of the controversies swirling around the new technology today.
Kent Walker, who oversees the Google's AI ethics and responsible AI innovation, talks about how Google reviews AI systems for trust and safety and the outlook for safe AI going forward.
Director of the Pentagon’s Joint AI Center, Lieutenant General Michael S. Groen talks about improving war fighting and the challenge of China.
David Yi and Yohan Lee from Riiid Labs, the leading startup applying machine-learning to education, talk about making personalized instruction available to anyone in the world with an internet-connected device. They spoke about the family of algorithms behind their system and the recently concluded Riiid AIEd Challenge, a Kaggle competition that engaged more than 3,400 teams across the world in developing knowledge tracing algorithms.
Turing award winner Yoshua Bengio and his colleague Julian Serban, co-founder of Korbit, an AI ed-tech startup with the aim of democratizing education, talk about enhancing education through the application of deep learning systems that can track student behavior predict their performance and deliver strategies to both improve performance and prevent students from losing interest.
Geoff Hinton has lived at the outer reaches of machine learning research since an aborted attempt at a carpentry career a half century ago. He spoke to me about his work In 2020 and what he sees on the horizon for AI.
Eric Horvitz, chief research scientist at Microsoft and a commissioner on the National Security Commission on AI, talks about ensuring interoperability of AI systems with US allies and working to make all AI systems reliable.
An open-source compiler called TVM helps data scientists optimize their model’s performance on specific hardware.
NSCAI commissioner Steve Chien, technical supervisor of the artificial intelligence group at NASA's Jet Propulsion Laboratory, talks about the growing demand for AI solutions in space, from coordinating an increasing number of earth-orbiting objects to protecting critical communication satellites from attack.
Jason Matheny, a commissioner at the National Security Commission on AI and head of Georgetown University’s Center for Security and Emerging Technology, talks about coordinating AI developments with NATO and making India the focus of the US's Indo-Pacific AI strategy to counter China.
Alex Ratner, an assistant professor at the University of Washington and a cofounder and CEO of Snorkel AI, talks about programmatically labeling training data for supervised learning models.
In the second episode of a series on the machine-learning pipeline, Joe Hellerstein, a professor at UC Berkeley, talks about data wrangling.
Turing Award winner David Patterson talks about the end of Moore's law and the evolution of computer chips from general purpose CPUs to GPUs to the recent Cambrian explosion of specialized AI chips, including Google's TPU, in the first episode of five about the machine-learning model-development pipeline with Ameet Talwalkar, co-founder of Determined AI, an open-source platform for ML model development.
NSCAI commissioner Gilman Louie talks about great power competition in the digital age and the US need for a more technologically literate diplomatic core to counter China's increasing diplomatic efforts on the technology front.
Ken Ford, an NSCAI commissioner, talks about turning AI from a tool to a teammate and unshackling research and implementation of AI from government bureaucracy in order to compete with nimbler countries such as China.
Katharina McFarland, an NSCAI commissioner, talks about the commission’s recommendations on inserting AI into the National Defense Strategy and how war games should integrate AI enabled applications in order to inform US military doctrine
Eric Horvitz, Chief Scientific Officer at Microsoft and a commissioner with the National Security Commission on AI, talks about the commission’s recommendations that responsible and ethical uses be a primary consideration in any AI system for national security.
Jason Matheny, an NSCAI commissioner who now leads a think tank at Georgetown University focused on the intersections of technology, policy and national security, spoke in this week’s episode about the Commission’s recommendations on export controls for sensitive technology and the difficult problem of protecting digital assets like algorithms and data.
Mignon Clyburn, an NSCAI commissioner and longtime regulator at the FCC, talks about the Commission’s recommendations to increase competency in artificial intelligence at the Department of Defense and other government agencies. Ms. Clyburn talked about establishing a National Reserve Digital Corps with a scholarship program modeled after the ROTC and the creation of a United States Digital Service Academy similar to mint a new class of civil servants with deep technical knowledge.
The Alexa Prize Socialbot Grand Challenge is a competition for university students to create a social bot that can converse coherently and engagingly with humans. This year's prize goes to the team from Emory University in Atlanta, Georgia. I speak with Prem Natarajan, vice president of natural understanding in the Alexa AI organization, about the prize, the evolution of conversational AI, its current challenges and its future promise
Qualcomm Technologies is powering the shift to fifth generation wireless communications, known as 5G. In this sponsored episode, I speak to two of the company's product managers leading the company's efforts to use AI to enhance 5G, reduce on-device power consumption, and give developers the tools necessary to make devices smarter and faster.
This week I speak to Stanford professor Fei-Fei Li, one of the people responsible for the current AI revolution. Fei-Fei talked about her early days running a New Jersey dry cleaner to finance her Princeton education, her creation of ImageNet, the world's first large labeled image data set, which allowed the validation of neural networks, and her latest work on ambient intelligence, which promises to transform elder care.
Pietro Perona, a professor at the California Institute of Technology, is one of the brains behind a pair of smartphone apps that help you do just that: eBird and iNaturalist. But simple as the apps are to use in identifying tens of thousands of species, the science behind them is complex. Gathering enough examples for each species to train a neural network is impossible, so much of Prof. Perona’s work has been focused on making machines more efficient learners, requiring less training data.
In this week's episode, the last in a series of six, we talked to Eric Horvitz. Commissioner at the National Security Commission on AI and Chief Research Scientist at Microsoft, about the commission's recommendations to Congress about the need for training, standards and documentation to govern the application of AI in the national security space.
In this week's episode, we talk with NSCAI Commissioner Gilman Louie about line of effort’s recommendations to Congress on how to maintain US leadership in AI hardware and 5G. He spoke about the need for a national microelectronic strategy and policies that would advance spectrum sharing for 5G to create a global alternative to the Chinese telecommunications giant Huawei.
NSCAI Commissioner Jason Matheny talks about his line of effort regarding cooperation on AI with key allies and partners. He spoke about his group's recommendations that the government establish a senior national security point of contact for AI and convene a multilateral working group for AI collaboration and interoperability - as well as the need for AI war games.
In the third episode of six episodes looking at the National Security Commission on AI 's first quarter recommendations to Congress, we speak with Katharina McFarland, a former Assistant Secretary of Defense for Acquisition, about the commission's recommendation that the Department of Defense and the Office of the Director of National Intelligence establish a steering committee on emerging technology to ensure that AI for national security gets top priority in the years ahead.
In this week's episode, we speak to Jose-Marie Griffiths, a commissioner on the National Security Commission on Artificial Intelligence, about the commission’s recommendations on how to strengthen the federal government's AI workforce. The recommendations focused on raising understanding of AI within the government and the need to streamline government hiring practices in order to attract and retain talent.
In April 2020, the National Security Commission on Artificial Intelligence issued its first-quarter recommendations to Congress, covering seven lines of effort, six of which are public and one of which is classified. In the first of a series of podcast episodes about those recommendations, we spoke with Andrew Moore, a professor at Carnegie Mellon University and NSCAI commissioner about the commission’s recommendations on increased AI R&D funding.
COVID-19 continues to sweep through the human population, killing some and damaging the health of others. While this podcast is normally focused on machine-learning, this week I talk to Vittorio Sebastiano, an assistant professor of stem cell biology at Stanford University, about groundbreaking tech that could someday help restore scarred tissue to pre-COVID health. Vittorio talked about his hunt for machine-learning collaborators to understand the process further.
COVID-19 has swept across the world was startling speed, but with equally startling speed, the machine learning community has responded. This week I speak with Irina Rish, a professor at the University of Montreal and a Mila academic member, who is helping head a task force to understand the virus. She talked about where the efforts currently stand and where they expect to go in the weeks and months ahead.
Let me know when it’s live.There has been a debate in the past few years between the symbolists and the connectionists about the future of artificial intelligence. The symbolists say that traditional, explainable, logic-based approaches still hold tremendous promise while the connectionists say that the power of deep learning, for all its current opacity and narrow application, holds the key to more general forms of machine intelligence. This week, I speak with David Cox, IBM Director of the MIT-IBM Watson AI Lab, which is blending the two traditions in what they call neuro-symbolic AI in hopes to move AI forward.
Justin Gottschlich, who founded the machine programming research group at Intel Labs, explains his group's efforts to automate software development. The ambition is to make it possible for anybody to create software simply by describing what they intend the software to do.
This week I talk to Casimir Wierzynski, a senior director in Intel’s AI Products Group, Cas talked about his work in privacy, taking me on a tour of the latest strategies that promise to unlock the data necessary to liberate AI. He talked about hardening encryption against the code-cracking power of quantum computers and about his work in connectomics with salami slicers for the brain that are making it possible to map the neural networks of our minds.
Terry Sejnowski, author of the book Deep Learning Revolution, who together with Geoff Hinton created Boltzmann machines, a deep learning network that has remarkable similarities to learning in the brain, talks about whether machines dream and the algorithms of the brain, whether Marvin Minsky was the devil and how deep learning is shaping the future of education.
We begin 2020 by looking back at some of the highlights from 2019 including conversations with Turing award winners, Yoshua, Bengio and Yann Lecun, as well as with the father of reinforcement learning, Rich Sutton. Our guests consider applying machine learning to the climate crisis; competition between the U S and China for dominance in AI; and the future of machine learning through various kinds of unsupervised learning.
Daphne Koller, formerly at Stanford University and cofounder of the online education company, Coursera, talks this week about using machine-learning to develop new drugs. Her approach is to use machine learning to accuratley identify cellular or genetic targets for treatment. The field is just getting started but promises to speed the development of new and better therapies to treat disease.
My guest this week, Aude Billard from Switzerland’s Learning Algorithms and Systems Laboratory, blends control theory with machine learning to build robotic systems that are both swift and precise but can handle some of the unpredictability of the real world. Her lab famously taught a robot arm to catch a tennis racket looping through the air and is working on ever more precise robots that can even do the work of Switzerland’s famous watchmakers.
Former Google chief executive Eric Schmidt and former Deputy Defense Secretary Bob Work, co-chairs of the U.S. National Security Commission on AI, talk about the challenges the government faces in winning support from a skeptical private sector and in maintaining engagement with China while ensuring that that engagement doesn’t work to America’s detriment.
The secret in much of artificial intelligence today is that it depends on hordes of unskilled workers to label the data used to train supervised learning models. But, in order for data science teams to work with labelers around the world, they need a platform. This week, in the second of a periodic series of sponsored episodes, I talk to Manu Sharma and Brian Rieger, who saw the opportunity to provide that platform and founded Labelbox, the leading labelling software in the space.
A few months ago at the recent international conference on machine learning, a workshop and research paper launched a movement to use machine learning in addressing climate change. The response was huge and has given birth to the bones of an organization climate change.ai. This week I talked to David Rolnick, a postdoc at U Penn and Priya, Donti, a Phd student at Carnegie Mellon, about how the group came together and about how the organization is developing.
Automated machine-learning tools – or tools that automate the creation of machine-learning applications – are increasingly important in the current talent-scarce environment. Expensive ML engineers shouldn't spend their time doing stuff that machines can do quicker and cheaper. This week, we talk to Evan Sparks and Ameet Talwalkar, two of the founders of Determined AI, which builds tools that streamline workflows for machine-learning teams and, the company hopes, will eventually democratize AI.
This week, I talk to Brendan McCord, who wrote the Pentagon’s AI strategy and is now a Special Government Employee at the National Security Commission on AI. Brendan talks about what he believes the US needs to do to stay competitive with China and promote an alternative vision of AI-powered security and prosperity to the world.
This week I talk to John Platt, a Distinguished Scientist at Google, about twin problems: finding cheap zero-carbon energy sources and mitigating global warming. John is a polymath, having discovered asteroids, helped put the touch in computer touchpads and even won an Academy Award for scientific and technical achievements in computer animation. Now, he is part of a growing movement of machine learning researchers tackling climate change.
This week we return to the world of thinking robots with Chelsea Finn, one of the youngest experts in the field, who talks about her journey, about her work in meta-learning and about lifelong learning for robots.
This week, we look at AI in India. With its massive population, fast-growing economy, English-language education and large supply of brilliant researchers and engineers, it should be competing with China and the U.S. for dominance in the space. But it is not. I talk to Partha Talukdar, a professor at the Indian Institute of Science, Bangalore, about the challenges that have kept India from realizing its AI potential.
This week I talk to Trae Stephens and Brian Schimpf from Anduril Industries, an AI defense contractor, about the current state of AI research and deployment for national security, including how the US stacks up against China. We also talked about the resistance among US engineers to work on defense applications and whether that hobbles the US in the global AI arms race.
This week, I talk to Ken Church, a pioneer in Natural Language Processing, whose use of statistical models on part of speech tagging revolutionized the field and is what makes automatic dictation and machine translation so popular today. We talked about his early days at MIT, about explainable AI and about how the Holy See played a role in his probabilistic approach to NLP.
This week, I talk to Sergey Levine, one of the most prolific researchers in robot learning. We talked about developing a robot’s sense of touch and about robot dreams and whether he believes we know what’s happening in the field in Russia and China.
Thinking robots: that’s how much of the world envisions artificial intelligence and if there is one person on the planet who understands the limitations and promise of intelligence in robots, it's Pieter Abbeel, one of the world’s foremost experts on robotic learning systems. In this episode, Pieter talks about robot memories and the prospect of robots with personalities eventually assisting in the home. Listen and learn about your future.
This week I talk to the Bengio brothers, Samy and Yoshua, in their first interview together. Yoshua recently won the Turing Award with Geoff Hinton and Yann Lecun, while Samy leads a team of researchers at Google Brain. The brothers are well known to people who work in machine learning, but few know how intertwined their professional lives have been. They talked about their unconventional parents and their early collaboration on neural network research, as well as what they see as the challenges ahead.
In this week's episode, I talk to Pedro Domingos, author of the bestselling book, The Master Algorithm, which is about the ongoing effort to unify machine-learning paradigms in a single model. But the conversation was much broader than that. Pedro believes strongly that the great powers are engaged in an AI arms race with America's Defense Advanced Research Projects Agency, or Darpa, pitted against China's military and industrial dynamo. We also talked about the future of democracy and authoritarianism in an AI-driven world.
Resurrecting the Tower of Babel with machine learning: In this week’s episode, we talk to Liang Huang, principal scientist at Baidu Research in Silicon Valley about his breakthrough in simultaneous translation technology, which promises to erase language barriers. Baidu’s system can already translate speech to text with as little as a three-second delay. Soon, Liang says, the technology will translate speech to speech, enabling a future in which people from different languages can speak fluidly with each other.
In this episode of Eye on AI, I continue my review of AI research in different regions of the world with a focus on Europe. Europe, with its strong academic tradition, faces unique challenges in scientific research because of the continent's fragmentation and the weakening of the European Union. Given the growing dominance of North America and China, Europe risks being left behind. To understand what Europe is doing to avoid this, I talk to Bernhard Schölkopf and Matthias Bethge, two machine learning researchers from Tübingen, Germany, who have been working to bring machine learning research in Europe under one umbrella. I hope you find Bernhard and Matthias as interesting as I did.
In this episode of Eye on AI, I talk to Ben Rosman, who runs Africa’s largest machine learning lab at the University of Witwatersrand in Johannesburg, South Africa, where he is focused on reinforcement learning. Ben has been instrumental in unifying and upgrading the continent’s machine-learning capabilities in hopes of making Africa a player in the artificial intelligence revolution. If you wanted to know what’s going on with AI in Africa, Ben will fill you in. I hope you find him as interesting as I did.
In this episode of Eye on AI, I talk to Julian Togelius, perhaps the most prolific researcher at the intersection of video games and artificial intelligence. Julian works on AI for games and games for AI. Some of his most significant work is in training deep neural networks to play video games and generalize what they have learned, a critical step toward artificial general intelligence. For those of you who don't understand the importance of video games to artificial intelligence research, Julian will enlighten you. For those of you who do his recent work will surprise you. I hope you find Julian as interesting as I did.
In this episode of Eye on AI, I talk to Miles Brundage, who studies the societal impacts of artificial intelligence and works on the policy team of OpenAI, the nonprofit A.I. research company founded by Elon Musk. When I spoke to Miles, he was a research fellow at the University of Oxford’s Future of Humanity Institute, where he remains an associate. We talked about the policy side of AI security and whether he is optimistic that regulations can steer machine learning applications away from the nightmare scenarios popularly imagined. I hope you find Miles as interesting as I did.
In this episode of Eye on AI, I talk to Kaifu Lee, a thought leader on AI in China. Kaifu just published the book, AI Superpowers: China, Silicon Valley, and the New World Order. We talked about the premise of the book, which is that China has already caught up with the US in the field of AI and is poised to surpass it. While China may lag on basic research, it has the formula to excel in implementation. I hope you find Kaifu as interesting as I did.
In Episode 1 of Eye on AI, I talk to Jack Clark, Strategy and Communications Director at OpenAI, a nonprofit A.I. research company, in a wide-ranging conversation off of things highlighted in Jack’s popular Import AI newsletter. Topics include Google CEO Sundar Pichai’s comment that the advent of artificial intelligence to man’s discovery of fire; the chances that the world’s nation states can create and adhere to international norms governing A.I., preventing the spread of dangerous applications of the powerful technology; whether A.I. is escaping the labs of the tech giants and becoming more democratic; and whether A.I. eventually become a cognitive mirror to our own minds.
En liten tjänst av I'm With Friends. Finns även på engelska.