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Cognilytica’s AI Today podcast focuses on relevant information about what’s going on today in the world of artificial intelligence. Hosts Kathleen Walch and Ron Schmelzer discuss pressing topics around artificial intelligence with easy to digest content, interview guests and experts on the subject, and cut through the hype and noise to identify what is really happening with adoption and implementation of AI.
The podcast AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion is created by AI & Data Today. The podcast and the artwork on this page are embedded on this page using the public podcast feed (RSS).
In our very first podcast we asked the question “Why Does AI Matter?”. So we thought it only fitting as we start our eighth season of AI Today to come back to this topic. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss whether or not the mood is turning against AI.
Continue reading Is the Mood Turning Against AI? [AI Today Podcast] at Cognilytica.
AI continues to impact and enhance every industry. From better nutrition, better sleep, practicing mindfulness and meditation, to improved insights on one’s overall health AI is having a big impact on fitness and wellness. In this episode of AI Today hosts Kathleen Walch and Ron Schemzler share AI’s impact on the fitness and wellness industry.
Continue reading AI Use Case Series: AI in Fitness and Wellness [AI Today Podcast] at Cognilytica.
AI is being used in many industries and sports is no exception. AI is being applied to enhance all areas of sports from the athlete to the fan, the coach to the referee, and even in judging athletic competition. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss how AI is being applied in professional sports.
Adaptability is the ability to adjust to new conditions, environments, or situations effectively and efficiently. It involves being open to change, learning quickly from experiences, and having the flexibility to modify one’s approach in response to shifting circumstances. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer continue with the soft skills series and discuss the soft skill of adaptability.
Continue reading The Need for Adaptability with AI [AI Today Podcast] at Cognilytica.
An AI-First Mindset refers to a proactive and strategic approach to integrating AI into all aspects of your life both personally and professionally. It involves prioritizing and using AI as a key driver for decision-making, innovation, and problem-solving. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss what having an AI-First mindset means.
Continue reading What is an AI-First Mindset? [AI Today Podcast] at Cognilytica.
If you’re ever done a web search you know that getting relevant and appropriate answers on the web can take a lot of effort. Oftentimes, it also requires multiple attempts to get relevant results. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss the changing landscape of AI and search.
How AI is changing search
Already, AI is proving to be a massive enhancement and augmentation to the everyday work and tasks of businesses, enterprises, and organizations of all types.
Continue reading What’s happening with AI and Search? [AI Today Podcast] at Cognilytica.
Data is integral at any organization. However, data on it’s own doesn’t provide much value. If we want to get more from our data and AI systems, and if we truly want to get machines to become more intelligent, we need to bridge that gap with at least some understanding of those patterns. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer interivew Rich Maltzman.
CIOs everywhere are gearing up for increased investments in AI, while facing challenges and overcoming barriers that come with implementing and scaling AI. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer interview Linda Yao. Linda is COO and Head of AI Solutions and Services at Lenovo.
AI’s Impact on CIOs
Recently, Lenovo conducted a global survey of CIOs.
Here’s a hint as to what is separating the AI failures from successes: skip the proof of concept. When it comes to AI projects go right for pilot projects. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss AI Pilots vs. Proof of Concepts.
AI Pilots vs. Proof of Concepts
A proof-of-concept is a project that is a trial or test run to illustrate if something is even possible and to prove your technology works.
Continue reading Skip the AI Proof of Concept [AI Today Podcast] at Cognilytica.
AI and generative AI is proving transformational in every industry. This includes long established industries like insurance. In particular, the growth of generative AI in the insurance and insurtech space in showing tremendous potential. In this episode of AI Today we interview Connor Atchison (CEO) & Itay Mishan (CTO) at Wisedocs.
How is AI used in the insurance industry?
Artificial intelligence has been on the horizon for over seventy years. In fact, the term AI was officially coined in 1956. So, why does it seem so close but also so unattainable? In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss the question: Are we still repeating the same mistakes with AI?
AI projects aren’t dying because of big problems. Rather it’s the small things that are causing projects to fail. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss what iteration really means for AI projects.
Continuous Model Iteration
We always say that AI projects are never set it and forget it.
Continue reading What Iteration Really Means with AI [AI Today Podcast] at Cognilytica.
Move Fast and Break Things worked for high flying Silicon Valley startup megatech companies but it doesn’t work for AI projects. Between 70%-80% of AI projects are failing to meet their objectives. With stats like this, it’s clear that breaking things isn’t leading to success in AI. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer dig into this topic.
One of the most vexing problems in even today’s highly capable intelligence systems is for systems to actually understand what they are generating as output. Repeating a pattern, even a sophisticated pattern, while showing good knowledge of the pattern, doesn’t really help if the system doesn’t really understand what it is generating. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss this DIKUW pyramid and why the “U” understanding level is a critical, but often left out, layer of the pyramid.
Soft skills are increasingly becoming important for AI, and in particular Generative AI. Collaboration can accelerate learning, creativity, and innovation. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss the critical skill of collaboration.
Why Collaboration skills are needed for AI
In this episode we discuss why collaboration skills are important to improve your interaction with AI systems.
AI is being adopted by many organizations and they are seeing dramatic improvement, increased productivity, and cost savings. However, government at all levels, including local governments, are also seeing dramatic improvements when adopting AI. On this episode of AI Today we interview Roxy Ndebumadu. She is the District 4 Councilmember at Bowie, MD City Council.
Effective communication is vital for enhancing both human-to-machine and human-to-human interactions with AI. Clear communication ensures more accurate and optimal outputs from AI systems. Additionally, AI tools can improve our communication skills by helping us better articulate and present our ideas and creative needs. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer continue with the soft skills series and discuss the soft skill of communication.
Continue reading Unlocking the power of Communication with AI [AI Today Podcast] at Cognilytica.
Creativity is a uniquely human trait that allows for the expression of individuality and a range of emotions. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer continue with our soft skills series discussing creativity.
AI, especially generative AI, is transforming personal and professional tasks like writing, report generation, and image creation, making them easier and more accessible.
On May 17, 2024, Governor Jared Polis signed SB24-205, a pioneering law to protect Colorado consumers using AI systems. The legislation mandates transparency and accountability, ensuring AI technologies are developed ethically and fairly. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer interview Rep Manny Rutinel. He is a Colorado State Representative and a Prime Sponsor of the bill in the House.
Generative AI has significantly influenced content creation, data analysis, and interactive communication, but there is a growing need for intelligent systems to perform tasks with minimal human input. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer dicuss the concept of Agentic AI, including what it is, and why it’s becoming popular.
Continue reading The Rise of Agentic AI [AI Today Podcast] at Cognilytica.
Companies of all sizes across the globe in just about every single industry are looking to see how AI can provide them a competitive edge. They want AI to provide efficiencies and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity in the field of AI for project professionals who are CPMAI certified and follow the CPMAI methodology.
The widespread adoption and use of generative AI means that folks no longer need to be an expert in “hard” skills such as statistics & probability, calculus, or linear algebra to get value from using Generative AI. Instead, the need to use soft skills such as communication, curiosity, problem solving, and adaptability is becoming more important.
Continue reading Why Critical Thinking is Crucial for AI [AI Today Podcast] at Cognilytica.
The Four-Part AI-Enabled Vision of the Future
In 2018, when at the time we thought AI hype couldn’t get any more hype-y, we at Cognilytica spent time thinking about what the broad implications of AI would be on our individual lives, our business and work lives, and on society in general. This thinking led us to put together our four-part vision we called the “AI-Enabled Vision of the Future”.
The Four-Part AI-Enabled Vision of the Future
In 2018, when at the time we thought AI hype couldn’t get any more hype-y, we at Cognilytica spent time thinking about what the broad implications of AI would be on our individual lives, our business and work lives, and on society in general. This thinking led us to put together our four-part vision we called the “AI-Enabled Vision of the Future”.
The Four-Part AI-Enabled Vision of the Future
In 2018, when at the time we thought AI hype couldn’t get any more hype-y, we at Cognilytica spent time thinking about what the broad implications of AI would be on our individual lives, our business and work lives, and on society in general. This thinking led us to put together our four-part vision we called the “AI-Enabled Vision of the Future”.
The Four-Part AI-Enabled Vision of the Future
In 2018, when at the time we thought AI hype couldn’t get any more hype-y, we at Cognilytica spent time thinking about what the broad implications of AI would be on our individual lives, our business and work lives, and on society in general. This thinking led us to put together our four-part vision we called the “AI-Enabled Vision of the Future”.
Back in 2018, when at the time we thought AI hype couldn’t get any more hype-y, we at Cognilytica spent time thinking about what the broad implications of AI would be on our individual lives, our business and work lives, and on society in general. This thinking led us to put together our four-part vision we called the “AI-Enabled Vision of the Future”.
Generative AI is one of the most accessible forms of AI currently available. While in the past, you might have used AI without knowing it, you can use Generative AI purposefully in ways that have immediate and dramatic impact on your daily life. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss what soft skills are necessary to get what we want out of Generative AI.
Continue reading Prompt Engineering Best Practices: Soft Skills [AI Today Podcast] at Cognilytica.
AI, and in particular generative AI, is having a profound impact on just about every industry. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer interview Saby Waraich to discuss AI’s impact on Project Management. Saby is CIO at Clackamas Community College and and speaking at the PMI Austin, TX Professional Development Day May 2, 2024.
Effective communication is an important skill to have. And, in this AI-era it’s more important than ever. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer interview Patti DeNucci. She is an author, speaker, workshop facilitator, consultant and keynoting the PMI Austin, TX Professional Development Day May 2, 2024.
How does AI impact communication?
Experimenting, testing, and refining your prompts are essential. The journey to crafting the perfect prompt often involves trying various strategies to discover what works best for your specific needs. A best practice is to constantly experiment, practice, and try new things using an approach called “hack and track”. This is where you use a spreadsheet or other method to track what prompts work well as you experiment.
Plugins for Large Language Models (LLMs) are additional tools or extensions that enhance the LLM’s capabilities beyond its base functions. In this episode hosts Kathleen Walch and Ron Schmelzer discuss this topic in greater detail.
Can I use plugins with ChatGPT?
Plugins can access external databases, perform specific computations, or interact with other software and APIs to fetch real-time data, execute code, and more.
Continue reading Prompt Engineering Best Practices: Using Plugins [AI Today Podcast] at Cognilytica.
As folks continue to use LLMs, best practices are emerging to help users get the most out of LLMs. OpenAI’s ChatGPT allows users to tailor responses to match their tone and desired output goals. Many have reported that using custom instructions results in much more accurate, precise, consistent, and predictable results. But why would you want to do this and why does it matter?
Companies of all sizes in every industry are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can provide them a competitive edge. They want to provide efficiencies and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity in the field of AI for professionals who are CPMAI certified and follow the CPMAI methodology.
To improve the reliability and performance of LLMs, sometimes you need to break large tasks/prompts into sub-tasks. Prompt chaining is when a task is split into sub-tasks with the idea to create a chain of prompt operations. Prompt chaining is useful if the LLM is struggling to complete your larger complex task in one step.
LLMs are basically big “text predictors” that try to generate outputs based on what it expects is the most likely desired output based on what the user provides as the text-based input, the prompt. Prompts are natural language instructions for an LLM provided by a human so that it will deliver the desired results you’re looking for.
AI is helping to re-imagine experiences of all sorts, including air travel. At the 2024 SXSW Conference and Festivals Bernadette Berger, who is Director of Innovation at Alaska Airlines presents on “The Sky’s the Limit: How AI will Re-imagine Airports”. In this episode of the AI Today podcast hosts and AI thought leaders Kathleen Walch and Ron Schmelzer have the opportunity to interview Bernadette.
AI is having an impact on every industry, including healthcare. AI’s impact in the practice of medicine is helping to reshape the practice of medicine both now, and in the future. In this episode of the AI Today podcast we interview Dr. Jag Singh. He is a Professor of Medicine at Harvard Medical School, focusing on the application of AI in the practice of medicine.
During the SXSW 2024 event, Wei Li presented on AI Everywhere with Software and Hardware. In this episode of the AI Today podcast we interview Wei Li. He is VP/GM of the AI Software Engineering Team at Intel.
He shares with what insights from that talk and what he means by AI being everywhere in both hardware and software.
As organizations continue to adopt AI the idea of innovation and sustainability are becoming important conversations. Intel wants to accelerate AI adoption by lowering barriers to entry for customers. In this episode of the AI Today podcast we interview Nuri Cankaya. He is the VP of AI Marketing at Intel.
Nuri sheds light on the myriad challenges faced by companies as they navigate the integration of AI with real-world data.
AI is having an impact on just about every industry and healthcare is no exception. In this episode of the AI Today podcast Cognilytica AI thought leaders Kathleen Walch and Ron Schmelzer interview Dr. Jesse Ehrenfeld. He is President of the American Medical Association (AMA). He also recently spoke at the 2024 SXSW Conference and Festivals.
The people side of AI is changing. Generative AI is reshaping how teams brainstorm, collaborate, and embrace the future. In this episode of the AI Today podcast we interview Ian Beacraft who is CEO at Signal and Cipher, and also CPMAI certified.
Is AI helping or hurting society?
In recent years the idea of responsible, ethical, and trustworthy AI has gained a lot of attention.
The Explainable AI Layer of the Cognilytica Trustworthy AI Framework addresses the technical methods that go into understanding system behavior and make black boxes less so. In this episode of the AI Today podcast Cognilytica AI experts Ron Schmelzer and Kathleen Walch discuss the interpretable and explainable AI layer.
The Explainable AI Layer
Separate from the notion of transparency of AI systems is the concept of AI algorithms being able to explain how they arrived at particular decisions.
Continue reading Explainable AI Concepts [AI Today Podcast] at Cognilytica.
Anyone looking to use and/or develop AI systems need ways that maintain trust, provide visibility and transparency, and utilize processes and methods that can provide greater oversight and accountability for potent AI systems that need to address – the layers of trustworthy AI. In this episode of the AI Today podcast Cognilytica thought leaders Kathleen Walch and Ron Schmelzer go over the Governed AI layer of the Cognilytica Trustworthy AI Framework.
Continue reading Governed AI Concepts [AI Today Podcast] at Cognilytica.
What are you really spending on in an AI Project? This is a question we often get asked. So, we wanted to spend some time on this podcast to discuss how to determine AI project costs.
First, it’s important to remember that it all comes down to scope. Our motto: Think Big. Start Small.
Continue reading Determining AI Project Costs [AI Today Podcast] at Cognilytica.
AI system transparency is about how we manage and run our AI systems. Transparency needs to address how you plan to provide visibility or transparency into how AI systems are created or applied. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss the transparent layer of AI as part of Cognilytica’s Trustworthy AI Framework.
Continue reading Transparent AI Concepts [AI Today Podcast] at Cognilytica.
The best practice for any high risk, emerging technology project with ill-defined goals is: Think Big. Start Small. Iterate Often. But, what does that really mean? How do you think big? And how do you start small? What does iteration look like? And how does this connect to project scope? In this episode of the AI Today podcast we discuss what it means to think big when it comes to AI.
Continue reading Properly Scoping AI Projects [AI Today Podcast] at Cognilytica.
In the context of technology adoption, “crossing the chasm” refers to the pivotal moment when an emerging technology moves beyond the early adopters and innovators phase to reach the early majority of users. This concept, popularized by Geoffrey A. Moore in his book “Crossing the Chasm,” highlights the gap or “chasm” that exists between the initial acceptance of a technology by enthusiasts and visionaries and its broader acceptance by a more pragmatic, mainstream market.
Continue reading Has AI Crossed the Chasm? [AI Today Podcast] at Cognilytica.
What is pseudo AI?
While AI is all about machines that have the intelligence like people, Pseudo AI or “AI washing” is when a company or product claims that AI is being used for a specific task or feature, but in reality, it’s people doing that task. In the startup world, “faking it until you make it”, is a common practice.
Continue reading Pseudo AI: Still a Thing, Still a Problem [AI Today Podcast] at Cognilytica.
What is Data Debt?
Organizations are awash with data. And data has been growing at organizations for decades. Data is accumulating across many different systems, processes, and as organizations evolve, merge, and change. What comes out of this is the idea of data debt, which is the accumulation of data-related problems over time as a result of the accumulation of data systems.
Continue reading AI Education Series: Data Debt [AI Today Podcast] at Cognilytica.
What is a responsible AI?
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum that addresses various aspects relating to societal, systemic, and technical areas.
Continue reading Trustworthy AI Series: Responsible AI Concepts [AI Today Podcast] at Cognilytica.
What can possibly go wrong when you embed someone else’s AI models in your systems? This episode of the AI Today podcast aims to answer this question. And, provide alternative options to Open Source AI. Despite the increasingly walled garden that is becoming the Large Language Models (LLMs) such as OpenAI’s ChatGPT, organizations are creating and embedding AI solutions powered by third-party models they have little visibility and control into.
What are the 5 ethics in artificial intelligence?
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly.
Continue reading Trustworthy AI Series: Ethical AI Concepts [AI Today Podcast] at Cognilytica.
What is a Chief AI Officer (CAIO)?
There has been a lot of talk lately, including a new executive order in the US, about the need for a Chief AI Officer. But, what is this role? And, is it really needed? We wanted to spend some time in today’s podcast revisiting a topic we first wrote about in 2019.
Continue reading Do you need a Chief AI Officer? [AI Today Podcast] at Cognilytica.
In an era where Artificial Intelligence is revolutionizing various industries, professionals equipped with the right skills and certifications are in high demand. The Certified Project Management for AI (CPMAI) certification is a game-changer for those seeking to excel in planning, managing, and executing AI and ML projects. And for those looking to grow critical AI and data skills.
How can AI be trustworthy?
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough for organizations. You need to know how to build, use, and interact with these systems ethically and responsibly.
Continue reading The Layers of Trustworthy AI Revisited [AI Today Podcast] at Cognilytica.
It’s hard to have a conversation about AI these days without the topics of Generative AI and Large Language Models (LLMs) coming up. And, Large Language Models (LLMs) have been proving useful for a variety of things such as helping write text, write code, generate images, and help augment human workers. However, as people are using LLMs, they are demanding even greater accuracy and relevance to their specific industry and/or topic area.
In today’s fast paced landscape, AI has emerged as a transformative technology. It’s being used as an augmented intelligence tool to help people do their job and tasks better. AI is also being used to help people create content and art. It’s being used to make decisions, both big and small. Loan decisions, product recommendations, movie recommendations, and so much more.
How many categories of AI are there?
Artificial Intelligence and machine learning is maturing considerably. You can now find AI projects in every industry. At Cognilytica, we spend a considerable amount of time on use cases and how different industries are using AI. As we analyze hundreds of different use cases, interact with many customers, deliver our AI and ML training courses, and write dozens of articles we find that there are seven common patterns that seem to continuously show up in all these use cases.
Continue reading Revisiting the Seven Patterns of AI in 2024 [AI Today Podcast] at Cognilytica.
Companies of all sizes in just about every single industry across the globe are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity in the field of AI for professionals who are CPMAI certified and follow the CPMAI methodology.
Facial recognition falls under the recognition pattern of AI. On it’s own the technology is neutral. However, it’s the application and use (or misuse) of this technology that can have severe consequences. Rite Aid is one of the most recent companies to come under fire for their use of facial recognition. In this episode of the AI Today podcast we explore what happened that that caused the FTC to give retailer Rite Aid fa facial recognition ban for 5 years.
Hyperpersonalization is focused on machine learning approaches that can develop a profile of an individual that can evolve over time rather than categorizing or “bucketing” an individual into a pre-defined category. One of the seven patterns of AI, the goal is to treat each individual as an individual. As you can imagine, this is a marketers dream.
AI projects are really data-centric projects. After all, data is the heart of AI. So it should come as no surprise that project managers who are managing AI projects need to move beyond just general project management skills. These provide a good foundation for managing schedules, resources, and the people needed to meet organizational goals.
In this episode of the AI Today podcast we want to look at some of the biggest trends in AI, including where AI is headed in 2024 and what this means for you.
Generative AI Gets Embedded in Everything
The ease and availability of Generative AI makes it easy to embed in everything.
Continue reading AI Today Podcast: Looking ahead at AI (and AI Today) in 2024 at Cognilytica.
In this episode of the AI Today podcast we want to take a look back at some of the highlights in AI, including headline-making AI news. 2023 was the year for generative AI. It was also the year for Trustworthy AI.
Generative AI all day, every day
Despite a pullback in other areas, Venture Capital investment in AI continues to be hot in 2023.
Continue reading AI Today Podcast: Looking back at AI in 2023 at Cognilytica.
The EU AI Act is a groundbreaking law that is the first ever law that will regulate AI. It’s the world’s first comprehensive AI law. It’s the first major regulatory framework for AI at a continental level, and the world’s first rules on AI. One of the goals of the AI Act is to provide a comprehensive set of rules for trustworthy AI.
Continue reading AI Today Podcast: The EU AI Act – What does it mean for you? at Cognilytica.
AI continues to have an impact on just about every single industry. Companies are on their AI journey to see how it can help with hypersonalization, improve efficiencies, and help them gain a competitive edge. The Consumer Packaged Goods (CPG) industry is embracing AI in number of ways. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Nandini Nandakumar.
Depending on the type of AI project that you do, it can have different lengths to see ROI. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss the different lengths of time to ROI for different types of AI projects.
Augmented Intelligence is where machines and humans work together to help assist the human to be better at tasks.
We often get asked what projects are appropriate for AI versus other forms of technology. So, we thought it was a great topic for a podcast. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer go over when to do automation versus AI.
Automation is using technology to perform repetitive tasks.
Continue reading AI Today Podcast: When to do Automation Versus AI at Cognilytica.
AI is impacting very about every single industry and pharma is no exception. AI has tremendous potential in streamlining processes, optimizing drug discovery, and enhancing patient care in ways we’ve never seen before. In this episode of the AI Today podcast we have an insightful conversation with Xiong (Sean) Liu. He is the Director of Data Science and AI at Novartis.
You may have heard the terms proof-of-concept, pilot, and production thrown around relating to various projects at your organization. But, do you know the difference between all of them?
And when running and AI project should you start with a proof-of-concept or pilot project?
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Proof-of-Concept, Pilot, and Production.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Anonymization, General Data Protection Regulation (GDPR), Uncanny Valley, explain how these terms relate to AI and why it’s important to know about them.
If you’re not familiar with the General Data Protection Regulation (GDPR) is a European Union regulation focused on data protection and privacy first published in 2016.
Hadoop and MapReduce changed the world of big data. And data is the heart of AI, so it should come as no surprise that talk about big data in the context of AI. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Hadoop, MapReduce, explain how these terms relate to AI and why it’s important to know about them.
Continue reading AI Today Podcast: AI Glossary Series – Hadoop, MapReduce at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Algorithmic Discrimination, Governance, Pseudo AI. Why are these terms vital in the AI landscape? And what do they mean?
Algorithmic discrimination
If you’re unfamiliar with the term algorithmic discrimination, it’s when bias in data used to train the algorithm can result in unfair decisions and results.
With the use of malicious AI on the rise, it’s hard to believe anything you read, hear, or see these days. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Malicious AI, Adversarial Attack, DeepFake, explain how these terms relate to AI and why it’s important to know about them.
Companies of all sizes in just about every single industry across the globe are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity in the field of AI and for professionals who are CPMAI certified.
Generative AI continues to be a hot topic discussion. People are using generative AI to help with many things, but just like with any technology it’s important to understand it’s a tool. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss how to actually put Generative AI into the apps and products that you use including how to use it in production.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Methodology, Waterfall, Agile, CRISP-DM, Cognitive Project Management for AI (CPMAI).
In this episde we explain how these terms relate to AI and why it’s important to know about them. Just about every single industry is using AI in some shape or form to help streamline and improve processes, increase productivity, gain a competitive edge, and stand out from others.
Conversation is a natural form of communication for humans. Therefore, it should come as no surprise that the future will be AI-Native. But what does an “AI-native future” mean? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Gi Jung Kim who is the CEO and co-founder of Coxwave.
It’s hard to have a conversation about AI these days without the topic of Generative AI coming up. People are using gen AI to help with many things from text creation, image creation, and more. But, just like with any technology, there can be a downside as well.
However, what happens when we become too reliant on technology?
Companies of all sizes in just about every single industry from healthcare to finance to construction are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can provide a competitive edge. They want to be able to have technology provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity for people looking to manage these types of projects.
AI systems have the potential to provide great value. But also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum that addresses various aspects relating to societal, systemic, and technical areas.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Black Box, Explainable AI (XAI), Interpretable AI, explain how these terms relate to AI and why it’s important to know about them.
📖 Learn about Black Box Technology 📦: Kathleen and Ron will unravel the mystery behind Black Box technology, explaining its connection to deep learning in the realm of artificial intelligence.
Companies of all sizes in just about every single industry are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can be used. They want to see how AI can provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity for people looking to manage these types of projects.
It’s hard to have a conversation about AI these days without the topic of Generative AI coming up. People are using gen AI to help with many things such as generating content and images. However, just like with any technology there can be a downside as well. In this podcast episode hosts Kathleen Walch and Ron Schmelzer take a deeper look at ge AI.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define terms related to data. Because, data is the heart of AI. So it’s important to understand the role data plays in AI and ML projects. In this episode we go over the terms data engineer, data engineering, and data pipeline.
AI systems have the potential to provide great value. But, also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum.
Continue reading AI Today Podcast: Trustworthy AI Series: Governed AI at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer delve into the diverse roles and concepts within the data universe: Data Science, Data Scientist, Citizen Data Scientist/Citizen Developer, and Data Custodian.
Data Science isn’t just a buzzword; it’s the art of transforming raw data into meaningful insights. And Data Scientists may be the sexiest job of the 21st Century, but do you know what they do?
It’s hard to have a conversation about AI these days without the topic of Generative AI coming up. People are using generative AI and LLMs to help with many things. But what do these technologies mean at an organizational level? And how do you apply this technology for your organization?
In this podcast episode hosts Kathleen Walch and Ron Schmelzer take a deeper look at generative AI.
Analytics are statistical and other methods to gain informational insight from data. Since data is the heart of AI, it makes sense analytics should be understood. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Analytics, Data Visualization, Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, Proscriptive / Projective Analytics.
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum that addresses various aspects relating to societal, systemic, and technical areas.
Continue reading AI Today Podcast: Trustworthy AI Series: AI System Transparency at Cognilytica.
Companies of all sizes in just about every single industry are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity for people looking to manage these types of projects and there is a significant and growing demand for skilled AI project managers across the whole range of AI capabilities.
It’s hard to have a conversation about AI these days without the topic of Generative AI coming up. People are using generative AI to help with many things, including creating images. But what do these technologies mean at an organizational level? And how do you apply this technology for your organization? In this podcast episode hosts Kathleen Walch and Ron Schmelzer take a deeper look at generative AI for images, in particular Diffusion Models and Image Generation.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data, Dataset, Big Data, DIKUW Pyramid, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum that addresses various aspects relating to societal, systemic, and technical areas.
Continue reading AI Today Podcast: Trustworthy AI Series: Responsible AI at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data, Dataset, Big Data, DIKUW Pyramid, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
It’s hard to have a conversation about AI these days without the topics of Generative AI and Large Language Models (LLMs) coming up. But what do these technologies mean at an organizational level? And how do you apply this technology for your organization? In this podcast episode hosts Kathleen Walch and Ron Schmelzer take a deeper look at what generative AI, Transformer Models, and LLMs are.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms V’s of Big Data, Data Volume, Exabyte / Petabyte / Yottabyte / Zettabyte, Data Variety, Data Velocity, Data Veracity, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum that addresses various aspects relating to societal, systemic, and technical areas.
Continue reading AI Today Podcast: Trustworthy AI Series: Ethical AI at Cognilytica.
Data is the heart of AI. So, of course we need to have a podcast about data! In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data, Dataset, Big Data, DIKUW Pyramid.
Data is the basic unit of discrete values that convey meaning, facts, quantities, or other units that computers operate on for further processing, interpretation, and analysis.
It’s one thing for us to talk about the Cognitive Project Management for AI (CPMAI) Methodology and the benefits it can bring to managers running AI and advanced data projects, but hearing directly how individuals are learning from and are applying the CPMAI Methodology can be incredibly valuable. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Chuck LaBarre, who is Chief Information Officer at ENI and is also CPMAI certified.
Data is critical to making AI and machine learning work. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data Augmentation, Data Labeling, Bounding box, Sensor fusion.
Data Augmentation are the techniques used to enhance existing data through the use of additional data, manipulations on existing data, or combinations of data in various ways.
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. Additionally you need to understand that Trustworthy AI is a spectrum that addresses various aspects relating to societal, systemic, and technical areas.
Data is the heart of AI. So, therefore doing things associated with your data is going to be critical for AI projects. This includes Data Preparation, Data Cleaning, Data Splitting, Data Multiplication, and Data Transformation.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms above and explain why they are important for AI projects.
For anyone who has used or interacted with an AI system you know that trust is required for AI systems if you want them to deliver any meaningful benefit. And once trust is lost, it’s almost impossible to gain back. Therefore, making Trustworthy, ethical & responsible AI a reality is not just a policy statement or a press release.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Robotic Process Automation (RPA), Attended bots, Unattended bots, Low Code, No Code, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Automation, Robot, Robotics, Collaborative Robot (Cobot), explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
AI is proving transformational in every industry, including long established industries, and insurance is no exception. AI is able to optimize underwriting processes, enable more personalized insurance offerings, enhance the overall customer experience, as well as help with process improvements.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Connor Atchison who is the CEO of Wisedocs, a medical record review machine learning software for insurance carriers, healthcare providers, laws firms, and TPAs.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data Science Notebooks, Jupyter, Colab, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
Many organizations want to do AI, but the technical skills needed can present a challenge. Not all organizations have data scientists on hand. Yet, many organizations still want to benefits of AI. In recent years there have been tools and platforms created to help automate many of the aspects of building and developing ML models that previously required very specialized skills and talent.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Machine Learning Tools: Keras, PyTorch, Scikit Learn, TensorFlow, Apache Spark, Kaggle, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Machine Learning Development Languages: Python, R, Julia, Scala, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms DevOps, Machine Learning Operations (ML Ops), explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
Data is the heart of AI. Which is why having good, clean data is so critical. But what happens when your data changes of over? What does that do to your models? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss the terms Data Drift, Model Drift, and Model Retraining.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Cloud ML, On-Premise, Edge Device, Machine Learning -as-a-Service (MLaaS), explain how these terms relates to AI and why it’s important to know about them.
Show Notes:
This episode is sponsored by Algolia:
Algolia Powers Discovery.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Batch Prediction, Microservice, Real-time Prediction, Stream Learning, Cold-Path Analytics, and Hot-Path Analytics, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
This episode is sponsored by Algolia:
Algolia Powers Discovery.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Operationalization, explain how this term relates to AI and why it’s important to know about them.
Show Notes:
This episode is sponsored by Algolia:
Algolia Powers Discovery.
Continue reading AI Today Podcast: AI Glossary Series – Operationalization at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Digital Transformation, Return on Investment (ROI), and Key Performance Indicator (KPI), explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
This episode is sponsored by Algolia:
Algolia Powers Discovery.
In this episode of the AI Today Podcast hosts Kathleen Walch and Ron Schmelzer get to talk to Sean Mullaney who is the Chief Technology Officer (CTO) at Algolia. We discuss how AI is revolutionizing e-commerce. Sean shares how vectorization is being used to enhance the relevance and personalization of search results for e-commerce businesses.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Confusion Matrix, Accuracy, Precision, F1, Recall, Sensitivity, Specificity, Receiver-Operating Characteristic (ROC) Curve, explain how these terms relate to AI and why it’s important to know about them.
Show Notes:
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Model Validation, Validation Data, Test Data, Cross-Validation, explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts?
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Model Tuning and Hyperparameter, explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest technologies?
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss and define at a high level the terms OpenAI, GPT, DALL-E, and Stable Diffusion, and share why you should know these terms and how they relate to the overall AI landscape.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts?
Large Language Models (LLMs) are all the rage these days. It’s hard to have a conversation about AI without ChatGPT, Google Bard, or LLMs being brought up. However, what if these LLMs could learn more about you individually and provide a much more hyperpersonalized experience and responses?! In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Dmitry Shapiro who is CEO of YouAi.
Transformer models have proven to be especially powerful for Natural Language Processing applications and image generation, and have been popularized by models such as GPT-3, Stable diffusion, and BERT. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Transformer Networks, explain how these terms relate to AI and why it’s important to know about them.
Continue reading AI Today Podcast – AI Glossary Series: Transformer Networks at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Boltzmann Machine, explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest technologies?
Continue reading AI Today Podcast: AI Glossary Series – Boltzmann Machine at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Decoder, AutoEncoder, Generative Adversarial Network (GAN), explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts?
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Convolutional Neural Network (CNN), explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest technologies?
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Recurrent Neural Networks (RNN) and Long-Short Term Memory (LSTM), explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts?
Usually used as a simple example for how deep learning neural networks work, a feed-forward neural network is the most basic, “vanilla” general kind of neural network. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Feed-Forward Neural Network, explain how these terms relate to AI and why it’s important to know about them.
Continue reading AI Today Podcast: AI Glossary Series – Feed-Forward Neural Network at Cognilytica.
In order for machine learning systems to work, they need to be trained on data. But there are different types of data and depending on the situation you may want to use one type of data over another, or a combination of different types. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms “Ground Truth” Data and Synthetic Data, explain how these terms relate to AI and why it’s important to know about them.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Pre-Trained Model and Transfer Learning, explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts?
As AI applications become more complex and data-intensive, the need for scalable and efficient storage solutions becomes increasingly important. AI models require vast amounts of data to be processed, and as the size and complexity of these models continue to grow, so does the need for more storage. Storage considerations are critical for both the training and the deployment of AI models.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms CPU, GPU, TPU, and Federated Learning, explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts?
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Tokenization and Vectorization, explain how these terms relates to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest technologies?
Backpropagation was one of the innovations by Geoff Hinton that made deep learning networks a practical reality. But have you ever heard of that term before and know what it is at a high level? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Backpropagation, Learning Rate, and Optimizer, explain how these terms relates to AI and why it’s important to know about them.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Loss Function, Cost Function and Gradient Descent, explain how these terms relates to AI and why it’s important to know about them.
Show Notes:
Deep Learning is powering this current wave of AI interest. But do you really know what Deep Learning is? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms hidden layer and deep learning, explain how these terms relates to AI and why it’s important to know about them.
The Perceptron was the first artificial neuron. The theory of the perceptron was first published in 1943 by McCulloch & Pitts, and then developed in 1958 by Rosenblatt. So yes, this was developed in the early days of AI. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Perceptron and explain how the term relates to AI and why it’s important to know about it.
Continue reading AI Today Podcast: AI Glossary Series – Perceptron at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Bias, Weight, Activation Function, Convergence, and ReLU and explain how they relate to AI and why it’s important to know about them.
Show Notes:
If we can replicate neurons and how they are connected, can we replicate the behavior of our brains? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms (Artificial) Neural Networks, Node, and layer, and explain how they relate to AI and why it’s important to know about them.
For a number of reasons, it can be important to reduce the number of variables or identified features in input training data so as to make training machine learning models faster and more accurate. But what are the techniques for doing this? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Feature Reduction, Principal Component Analysis (PCA), and t-SNE, explain how they relate to AI and why it’s important to know about them.
For time-consuming parts of the machine learning workflow people often look for tricks and techniques to help speed up the process. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms feature and feature engineering, explain how they relate to AI and why it’s important to know about them.
Regression is a statistical and mathematical technique to find the relationship between two or more variables. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Regression and Linear Regression and explain how they relate to AI and why it’s important to know about them.
Show Notes:
The idea of grouping similar types of data together is the main idea behind clustering. Clustering supports the goals of Unsupervised Learning which is finding patterns in data without requiring labeled datasets. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Clustering, Cluster Analysis, K-Means, and Gaussian Mixture Model, and explain how they relate to AI and why it’s important to know about them.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define DeepBlue, including what it is and why it’s notable for AI.
Show Notes:
Continue reading AI Today Podcast: AI Glossary Series – Deep Blue at Cognilytica.
Before this latest wave of AI where neural nets became the hottest algorithm of choice, an approach to machine learning that uses logic and constructs similar to the way that humans reason through problems called Symbolic Systems were actually the system of choice. Popularized in the late 1980s and early 1990s expert systems became the AI system of choice for organizations investing in cognitive technology.
Sometimes for reasons such as improving performance or robustness it makes sense to create multiple decision trees and average the results to solve problems related to overfitting. Or, it makes sense to boost certain decision trees. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Random Forest and Boosted Trees, and explain how they relate to AI and why it’s important to know about them.
Sometimes for reasons such as improving performance or robustness it makes sense to combine the results of multiple different models trained on the same data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Ensemble Models, and explain how it relates to AI and why it’s important to know about them.
Continue reading AI Today Podcast: AI Glossary Series – Ensemble Models at Cognilytica.
There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Support Vector Machine & Kernel Method, and explain how they relate to AI and why it’s important to know about them.
Continue reading AI Today Podcast: AI Glossary Series – Decision Trees at Cognilytica.
There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Support Vector Machine & Kernel Method, and explain how they relate to AI and why it’s important to know about them.
There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms K-Nearest Neighbor and Lazy Learning, and explain how they relate to AI and why it’s important to know about them.
Probabilities play a big part in AI and machine learning. After all, AI systems are Probabilistic systems that must learn what to do. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Bayes’ Theorem, Bayesian Classifier, Naive Bayes, and explain how they relate to AI and why it’s important to know about them.
Determining which categories or “classes” data belongs to in the core aspect of classification. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Classification & Classifier, Binary Classifier, Multiclass Classifier, Decision Boundary, and explain how they relate to AI and why it’s important to know about them.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer have a discussion with Bill Raymond who is the host of the Agile In Action podcast. We discuss why project managers should pay attention to AI, how the areas of Agile and AI are intersecting, and how artificial intelligence fits within the project management space both from running AI projects to also how AI will enhance the project manager’s role.
When it comes to building ML models, you want to make a model simple enough so that it can handle a wide range of real-world data on the one hand, but not too simple that it overgeneralizes or underfits the available data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Overfitting, Underfitting, Bias, Variance, and Bias/Variance Tradeoff, and explain how they relate to AI and why it’s important to know about them.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Dimension, Curse of Dimensionality, Dimensionality Reduction, and explain how they relate to AI and why it’s important to know about them.
Show Notes:
Pattern recognition in general is what machine learning systems do. They use an algorithm to learn patterns from data that can be then used to make predictions on new data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Pattern Recognition and explain how they relate to AI and why it’s important to know about them.
Continue reading AI Today Podcast: AI Glossary Series- Pattern Recognition at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define terms related to Machine Learning Approaches including Supervised Learning, Unsupervised Learning, Reinforcement Learning and explain how they relate to AI and why it’s important to know about them.
Show Notes:
Even though the term Artificial Intelligence does not have an agreed upon definition, the term machine learning does have a definition. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Machine Learning, Algorithm, Model and explain how they relate to AI and why it’s important to know about them.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss and define at a high level DeepMind, AlphaGo, and AlphaZero.
Show Notes:
Continue reading AI Today Podcast: AI Glossary – DeepMind, AlphaGo, and AlphaZero at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schemlzer define and discuss at a high level the terms Prediction, Inference, and Generalization, why it’s important to understand these terms, and how they fit into the overall picture of AI.
Show Notes:
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schemlzer define and discuss at a high level the terms Heuristic & Brute-force Search, why it’s important to understand these terms, and how they fit into the overall picture of AI.
Show Notes:
One of the seven patterns of AI, the objective of goal driven systems is to find the most optimal path or solution to a problem. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schemlzer define and discuss at a high level the terms Goal-Driven Systems as well as Roboadvisor, why it’s important to understand these terms, and how they fit into the overall picture of AI.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Probabilistic & Deterministic and explain how they relate to AI and why it’s important to know about them.
Show Notes:
The objective of the hyperpersonalization pattern of AI is to treat each individual as an individual. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define and discuss at a high level the terms Personalization, Recommendation, and Hyperpersonalization, how they are related, and why it’s important to have a light level understanding of these terms, and how machine learning makes hyperpersonalization possible.
The objective of the recognition pattern of AI is to have machines identify and understand the real world and unstructured data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define and discuss at a high level the terms Recognition Systems, Computer Vision, and ImageNet, how they are related, and why it’s important to have a light level understanding of these terms.
Named after researcher and AI pioneer Alan Turing, the Turing Test aims to test whether a machine or system is “intelligent” by putting the system to a test. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the Turing Test at a high level and discuss if it’s now possibly an overly simplistic assessment of whether or not machines have achieved necessary levels of intelligence.
Continue reading AI Today Podcast: AI Glossary Series: Turing Test at Cognilytica.
Virtual agents and chatbots have been proving useful at organizations. But is their real potential yet to be tapped? In this episode of the AI Today Podcast hosts Kathleen Walch and Ron Schmelzer interview Pat Calhoun who is CEO of Espressive. He shares with us where he thinks virtual agents are headed in 2023 including why he thinks virtual agents will be the next Intranet, what the pervasiveness of chatbots means for organizations, and the impact virtual agents will have on the way we work.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define AI Today the term Conversational Systems. We also define the terms Chatbots, Voice Assistants, and Machine Translation and explain how they relate to AI and why it’s important to know about them.
Show Notes:
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define Content Summarization and Analysis and Sentiment Analysis. We explain at a high level what these terms are and how they relate to AI.
Show Notes:
Cybernetics has actually been around longer than the term AI. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define what Cybernetic systems are at a high level.
Show Notes:
Continue reading AI Today Podcast: Glossary Series: Cybernetics at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer have a discussion with the hosts of PM Point of View Podcast Kendall Lott and Mike Fortezza. We discuss why project managers should pay attention to AI, why data-centric approaches are needed to run AI projects, and how CPMAI can enhance PM’s ability to run data projects.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define Natural Language Processing (NLP), Natural Language Understanding (NLU), Natural Language Generation (NLG), Speech-to-Text, Test-to-Speech, and (Automated) Speech Recognition. We share how these terms are related and how they fit into AI.
Show Notes:
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define Autonomous Systems, as well as related terms including Levels of Autonomy, Autonomous vehicle, and Autonomous (automated) Retail.
Show Notes:
Continue reading AI Today Podcast: AI Glossary Series- Autonomous Systems at Cognilytica.
Like all technologies, Artificial Intelligence (AI) is not immune to the waves of obscurity, hyped promotion, plateauing of interest, and decline. In fact, the AI industry has been through two such major waves of interest, hype, plateau, and decline, commonly referred to as the “AI Winters”. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define an “AI Winter” at a high level.
Continue reading AI Today Podcast: AI Glossary Series: AI Winters at Cognilytica.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However we are seeing the cross section of AI and project management and felt it was important to bring in PM experts to the discussion. In this episode hosts Kathleen Walch and Ron Schmelzer interview Bob Payne who is host of the Agile Toolkit podcast.
Cognilytica has spent a considerable amount of time on AI use cases and how different industries are using various AI and cognitive technologies and we’ve found that there are seven common patterns that seem to continuously show up in all these use cases. In this podcast hosts Kathleen Walch and Ron Schmelzer define at a high level the seven patterns of AI and explain how they can be used to shortcut AI projects.
Continue reading AI Today Podcast: AI Glossary Series: Seven Patterns of AI at Cognilytica.
It’s one thing for us to talk about the Cognitive Project Management for AI (CPMAI) Methodology and the benefits it can bring to project managers running AI and advanced data projects, but hearing directly how individuals are applying the CPMAI Methodology and how it has directly benefit their projects can be incredibly valuable. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Andre Barcaui who is a Brazilian project manager and professor and he is also CPMAI certified.
Rather than replacing humans with autonomous agents, businesses and agencies can see significant value in enhancing the capabilities of their existing staff and leveraging AI as a “force multiplier” that enables them to do more with their existing resources. This is the key idea behind the concept of Augmented Intelligence. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss the idea of augmented intelligence and what it means when AI can be used to assist humans, rather than replacing them.
Continue reading AI Today Podcast: AI Glossary Series: Augmented Intelligence at Cognilytica.
On the AI Today podcast we regularly interview thought leaders and practitioners who are implementing and managing AI and cognitive technology projects at various companies and government agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Galen Low, host of The Digital Project Manager podcast and co-founder of the Digital Project Manager.
Sometimes, talking about what is and isn’t AI isn’t helpful given the lack of a commonly accepted definition of AI. Instead we find that using the term Cognitive technologies when we’re talking about goals of Machines mimicking and approaching Human Intelligence can provide much better results.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Cognitive Technology.
Continue reading AI Today Podcast: AI Glossary Series: Cognitive Technology at Cognilytica.
On the AI Today podcast we regularly interview thought leaders and practitioners who are implementing and managing AI and cognitive technology projects at various companies and government agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Ann Campea who is the host of The Everyday PM Podcast. Her podcast focuses on project management and we discuss how the project management industry has changed and evolved with technological advancements, how she sees artificial intelligence impact the project management space, as well as what opportunities AI will bring to project managers.
In order to understand the goal of Artificial General Intelligence (AGI) which is also sometimes reffered to as Strong AI, it’s important to understand the difference between strong AI versus narrow or weak AI. In this episode of the AI Today podcast, hosts Kathleen Walch and Ron Schmelzer share the definitions for AGI/Strong AI and Narrow/Weak AI and explain why the terms Strong AI and Weak AI have fallen out of favor in recent years.
Companies of all sizes in just about every single industry are looking to see how Artificial Intelligence (AI) and machine learning (ML) can provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity for people looking to manage these types of projects and there is a significant and growing demand for skilled AI project managers across the whole range of AI capabilities.
The term Artificial Intelligence (AI) was coined in 1956. Despite the fact that the term is now decades old, there still is no commonly accepted definition. In this episode of the AI Today podcast, hosts Kathleen Walch and Ron Schmelzer share Cognilytica’s definition for AI.
Show Notes:
Continue reading AI Today Podcast: AI Glossary Series: Artificial Intelligence at Cognilytica.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Greg Mester who is host of the 5am Mester Scrum podcast. As his podcast talks about Scrum and Agile, he shares with us common misunderstandings about Agile and Scrum, how he sees AI helping Application or Agile Teams, and how the role of project managers is evolving.
It’s one thing for us to talk about the Cognitive Project Management for AI (CPMAI) Methodology and the benefits it can bring to managers running AI and advanced data projects, but hearing directly how individuals are applying the CPMAI Methodology can be incredibly valuable. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Andrew Stone who is Lead Specialist – Product Owner, Data Science at Maximus and he is also CPMAI certified.
When putting together your Ethical and Responsible AI Framework it’s important to remember that it needs to be actually implemented. Why spend all this time and resources to put together a framework just to let it sit on a shelf untouched. Remember: Ethical & Responsible AI is something you do, not a statement! In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer talk more about this topic and why it’s so important to actually do AI right which means doing ethical and responsible AI right as well.
When working on your ethical and responsible AI framework you should not overlook the roles, boards, and committees that will need to be put in place to ensure that the framework is actually implemented and updated as needed for overall AI project success for the long term. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer provide a high level overview on how to set up your organization for ethical and responsible AI success.
The pace of adoption for artificial intelligence (AI) and cognitive technologies continues unabated with widespread, worldwide, rapid adoption of AI and its various patterns. However with any transformative technology laws and regulations may be slow to catch up with the quickly changing technology. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss the global and regional impacts laws and regulations have related to data and AI.
Not all algorithms are explainable. So does that mean that it’s ok to not provide any explanation on how your AI system got to the decision it did if you’re using one of those “black box” algorithms? The answer should obviously be no. So, what do you do then when creating Ethical and Responsible AI systems to address this issue around explainable and interpretable AI?
In order to have people use AI systems they need to feel that they can trust these systems. That includes putting measures in place around AI Auditability, Traceability, and System Control. But what exactly does that mean and how do you do this in the context of your Ethical and Responsible AI Framework? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss issues related to AI Auditability, Traceability, and System Control, why it’s important to be transparent with users, and what steps and controls you should have in place.
When building Ethical and Responsible AI systems it’s important to think about AI System Transparency. These are ethical principles that focus on giving human users as much visibility into overall system behavior, including issues of visibility into data and AI configuration, appropriate disclosure and user consent, means for gaining visibility into bias and potential mitigation of that bias, and use of open systems.
In order to have people use AI systems they need to feel that they can trust these systems. That includes when they system provides an answer they may not want to hear. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss issues related to AI Today Podcast: Ethical & Responsible AI Series: Disclosure & Consent including why it’s important to disclose to users they are interacting with an AI, why it’s important to be transparent with users, and what steps you should consider to have users provide consent.
If data is the heart of AI, then it should come as no surprise that data privacy plays a big role in building ethical and responsible AI systems. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss issues related to AI and data privacy, why it’s important to stay up to date on these topics, how they can impact your project, and additional factors that need to be taken into consideration when building trustworthy AI systems.
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss issues that related to AI safety and security and why building trustworthy AI is critical for the success of the project.
Construction companies are increasingly using AI in a range of ways to tackle a number of challenges. From optimizing work schedules to improving workplace safety to keeping a secure watch on construction facilities, AI in the construction industry is already producing value. One such company, ALICE Technologies, is focused on a different challenge: scheduling. In this podcast hosts Kathleen Walch and Ron Schmelzer interview with René Morkos, CEO of ALICE Technologies and Adjunct Professor at Stanford.
Organizations are increasingly making use of AI systems to power their operations and enable a wide range of applications from the trivial to the mission-critical. As a result it’s more important than ever to understand the many complex issues related to AI and Data fairness and bias. In this Ethical and Responsible AI Series hosts Kathleen Walch and Ron Schemlzer dig deeper into the role data plays in AI, and how building AI systems with fairness in mind is critical.
Organizations are increasingly making use of AI systems to power their operations and enable a wide range of applications from the trivial to the mission-critical. Many of the concepts of AI ethics generally revolve around the set of what is “right” vs “wrong” with regards to intelligent systems. However, the sort of ethical concepts that are discussed in AI ethics frameworks tend to cluster around five different areas including: Societal Ethical AI, Responsible AI, Trustworthy AI, AI Governance, and Interpretable and Explainable AI.
AI systems have the potential to provide great value, but also the potential to cause great harm. Knowing how to build or use AI systems is simply not going to be enough. You need to know how to build, use, and interact with these systems ethically and responsibly. As more organizations adopt AI technologies the need to do AI ethically and responsibly is becoming incredibly important.
Companies of all sizes in just about every single industry are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity for people looking to manage these types of projects and there is a significant and growing demand for skilled AI project managers across the whole range of AI capabilities.
It’s one thing for us to talk about the Cognitive Project Management for AI (CPMAI) Methodology and the benefits it can bring to managers running AI and advanced data projects, but hearing directly how individuals are applying the CPMAI Methodology can be incredibly valuable. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Karen McCann who is a Product Manager at Toshiba Global Commerce Solutions and is also CPMAI certified.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer revisit the discussion around common reasons why AI projects fail. Sometimes AI systems can be too creepy and go into the uncanny valley. The uncanny valley is a relationship between the degree of an object’s resemblance to a human being and the emotional response to the object.
It’s one thing for us to talk about the Cognitive Project Management for AI (CPMAI) Methodology and the benefits it can bring to managers running AI and advanced data projects, but hearing directly how companies are applying the CPMAI Methodology can be incredibly valuable. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Charles Mendoza, who is Sr.
If you have ever tried to apply Agile methodologies to your AI projects you’ve probably noticed that Agile is challenged by the requirements of AI systems. We need to evolve Agile Methodologies from a Data-First Perspective. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer revisit the Agile Manifesto and Agile Methodologies and share why AI and data-centric methodologies, and specifically CPMAI Methodology, are needed for running AI projects successfully.
Continue reading AI Today Podcast: Why can’t we use Agile for AI? at Cognilytica.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss what AI in the cloud really means. They break down what is the cloud with a technical definition and then an economic definition to level set the topic and then dig into the question: What does AI have to do with the Cloud?
Continue reading AI Today Podcast: AI in the Cloud at Cognilytica.
Our AI Failures Series podcast was so popular we wanted to revisit some of the main reasons why we see AI projects fail. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer revisit the discussion around common reasons why AI projects fail. Not every vendor solution solves your problem, regardless of what they may tell you.
Back in 2012 an article was published in HBR stating that Data Scientist was the sexiest job of the 21st Century. However, about a decade later, does this still hold true? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss how Data Project Manager is becoming the new sexy job title of the next decade, why certifications for PMs matter, and how certifications like CPMAI are quickly gaining traction in the PM community.
Continue reading Is Data Scientist still the sexiest job of the 21st Century? at Cognilytica.
Far too often, agencies, organizations, and consulting firms are running data and AI projects without taking the right steps to ensure their success. Agile and iterative approaches have become adopted best practices for application development projects, but why don’t we have something similar when it comes to advanced analytics, big data, and AI projects? Without using best-practices approaches that standardize steps for data preparation, data identification, and data protection, it’s hard to achieve the success you’re expecting, wasting money and resources, leading to failure.
Continue reading AI Today Podcast: An Intro to CPMAI Methodology at Cognilytica.
Like all technologies, Artificial Intelligence (AI) is not immune to the waves of obscurity, hyped promotion, plateauing of interest, and decline. In fact, the AI industry has been through two such major waves of interest, hype, plateau, and decline, commonly referred to as the “AI Winters”. Is the next AI Winter approaching? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss the 3 main reasons for a winter: decline in investment, interest, and research.
Continue reading AI Today Podcast: Is the next AI Winter approaching? at Cognilytica.
Level 3 Intelligent Automation allows you to address the greatest challenges of unpredictability and variability and be able to achieve autonomous process discovery, autonomous process analytics, and autonomous process optimization. But is Level 3 Intelligent Automation right for your team or process? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss what Level 3 Intelligent Automation is, what questions you need to ask to identify opportunities for Level 3 automation, and some of the challenges with Level 3 automation.
Level 2 Intelligent Automation allows you to address greater challenges of unpredictability and variability. But how do you know if Level 2 Intelligent Automation is even right for your team? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss what Level 2 Intelligent Automation is, how to go beyond NLP & computer vision to use cognitive technology to help spot patterns & anomalies, as well as some of the challenges Level 2 Intelligent Automation presents.
Adding intelligence to automation enables greater degrees of variability and unpredictability. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss what it means to have Level 1 automation to handle variability and unpredictability, how to incorporate NLP and computer vision to help handle tasks with unstructured data, some of the challenges Level 1 automation can present, and what the key ingredient to Level 1 automation is.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer dive deep into Level 0 Automation, why so-called “dumb” automation provides tremendous value to your team when implemented correctly. This episode shares examples for immediate ROI with Level 0 automation, how your team should go about identifying and prioritizing opportunities for Level 0 automation, how to plan and iterate, then implement automation.
For organizations who want to get started on their AI journey, a great first place to start is with automation. However, what exactly do you automate? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss how to find automation opportunities in business processes, questions your team should ask when figuring out what to automate, and when and when not to start with “low hanging fruit”.
In our first ever AI Today podcast we asked the question “Does AI Matter?” and we revisited this question in our one year anniversary podcast as well. Now about 5 years from our first ever podcast episode we wanted to ask this question again: Does AI still matter in 2022? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer dig into this question and share how AI has changed and evolved over the past 5 years.
Continue reading AI Today Podcast: Does AI Still Matter in 2022? at Cognilytica.
For organizations who want to get started on their AI journey, a great first place to start is with automation. However before even figuring out what to automate you should have a solid understanding of your business processes and tasks. But, what exactly is a business process? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss what a business process is, define processes versus tasks, and bring this into the context of automation.
Data science is transforming business and generating new value across the organization. However, for large organizations they need a centralized group that centers on a discipline’s vision, governance, technique, and framework. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer Venkat Gunnu who is Senior Director, Data Science & Innovation at Comcast.
For organizations who want to get started on their AI journey, a great first place to start is with automation. However, figuring out what to automate, why to automate, and what return on investment (ROI) it will provide can be tricky. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss level 0 automation – what is it, why organization should look to automate processes, and what questions to ask in order to get started.
Shopify has over 1.7 million merchants across over 175 countries, with hundreds of millions of consumers shopping at their stores. By leveraging the scale of their data they are able to create new experiences for their merchants, and apply Machine Learning at scale. In this episode of the AI Today podcast, hosts Kathleen Walch and Ron Schmelzer interview Ella Hilal, who is the Head of Data Science, Engineering, Revenue and Growth at Shopify.
As companies are looking to leverage cognitive technology, and deploying machine learning models, organizations need to make sure they have the correct people, processes, and technology in place to succeed. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss with Anil Kumar, Exec. Director AI Industrialization at Verizon what AI industrialization is and how Verizon is moving from pockets of AI/ML to AI/ML being implemented across the organization.
The idea of bringing organizations from automation to intelligence is about the journey, not the destination. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss and overview of the automation to intelligence journey including introducing benefits of automation, discussing why the automation journey matters, and how to go about moving up the ladder of automation to intelligence.
Heavily regulated industries such as healthcare can pose unique challenges, but also provide unique opportunities with it comes to AI and ML. In this episode of the AI Today podcast, hosts Kathleen Walch and Ron Schmelzer interview Vignesh Shetty who is Senior Vice President & General Manager Edison AI and Platform at GE Healthcare Digital.
At a very fundamental level facial recognition is a way of recognizing a human face through technology. Seems straight forward enough, right? Not so fast. For many industries, facial recognition technology is still a gray area, clouded with mystery and mistrust. In this episode of the AI Today podcast, hosts Kathleen Walch and Ron Schmelzer provide an overview of how facial recognition works, discuss the concerns and issues around facial recognition technology, news about how the technology was misused or raised ethical concerns, and pose the question: Is facial recognition technology a technology that is too difficult to get right in practice?
Continue reading AI Today Podcast: The Challenges and Issues with Facial Recognition at Cognilytica.
Machine learning algorithms need examples of data from which they can learn, especially supervised machine learning algorithms. However, one big challenge for those looking to put machine learning into practice is the lack of a sufficient quantity of good quality data examples from which to train systems. To address the needs for large quantities of high quality data, vendors have emerged to provide computer-generated data, known as synthetic data, that matches the range and quality of data needed to train systems.
Continue reading AI Today Podcast: Overview of Synthetic Data at Cognilytica.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. Data is at the heart of AI. It should be no surprise then that proper data management is crucial for AI projects. This podcast is an excerpt from our Cognilytica Education course discussing data pipelines. In this clip we discuss the training pipeline the inference pipeline.
Continue reading AI Today Podcast: AI Education Series: Data Pipelines at Cognilytica.
As the markets for Data, Automation, Analytics, and AI continue to evolve, so too does Cognilytica’s coverage of these areas. In today’s podcast we discuss how we are expanding our current Cognilytica Classification of the AI Vendor Ecosystem to include a data infrastructure layer. Within this layer falls data generation, big data storage and query, and data engineering and DataOps.
Continue reading AI Today Podcast: The Expanding Data Infrastructure Layer at Cognilytica.
In order for many machine learning algorithms to be trained, especially supervised learning algorithms, they need to be fed relevant data along with the desired meaning of the data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer provide an overview of the data labeling market, what “ground truth” labeling is, the different data labeling and annotation needs, and data labeling and annotation use cases.
Continue reading AI Today Podcast: An Overview of the Data Labeling Market at Cognilytica.
On today’s AI Today podcast hosts Kathleen Walch and Ron Schmelzer are going to do their annual AI Market Forecast & Trends. They will spend some time reflecting on what they are seeing in the market and where they forecast the AI markets will go in 2022. They will talk about the Data Labeling, Data Engineering & Preparation, ML Platforms, ML Ops, and RPA markets.
Continue reading AI Today Podcast: The State of AI (and AI Today) heading into 2022 at Cognilytica.
With 2021 quickly fading into the rear view mirror it’s time to do our annual yearly AI recap. On today’s podcast hosts Kathleen Walch and Ron Schmelzer are going to take a look back at 2021 as it relates to AI and share some of the hottest news from the past year, including acquisitions and fund raises, and some of our favorite podcasts of 2021.
Continue reading AI Today Podcast: Looking back at AI (and AI Today) in 2021 at Cognilytica.
Earlier in 2021, The National Security Commission on AI (NSCAI) published their final report that presents the NSCAI’s strategy for winning the artificial intelligence era and provides a strategy to get the United States AI-ready by 2025. On this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer had the opportunity to interview Gilman Louie who is one of 15 commissioners for the National Security Commission on AI (NSCAI) and co-founder and partner of Alsop Louie Partners, an early-stage technology venture capital firm.
For anyone following AI, it should come as no surprise that countries around the world are taking a vested interest in AI. In 2021 the NSCAI published their final report explaining the steps the United States must take to responsibly use AI for national security and defense, defend against AI threats, and promote AI innovation.
It’s important for organizations to understand all that’s involved that goes into the model. A common reason that AI projects fail is that the team does not understand the model and data lifecycle. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer dig deeper into this subject and share tips for organizations to overcome this common issue.
AI is not the solution to all problems. And, not every vendor solution solves your problem, regardless of what they may tell you. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer continue the discussion around common reasons why AI projects fail. In this episode they dig into issues that can happen when companies don’t ask the right questions and get caught up believing vendor and industry hype.
Far too often, organizations move forward with AI projects without having a clear understanding of how their AI and ML models are going to be used in the real world. This lack of real world understanding is a major reasons why AI projects fail. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer dig deeper into this topic, and share ways companies can overcome this issue.
Continue reading AI Today Podcast: AI Failure Series – The Real World Mismatch at Cognilytica.
Countries across the world are understanding that they can take advantage of the tremendous transformation presented by AI and cognitive technologies and position themselves for global competitiveness in the future. As a result, countries are coming up with their own unique AI strategies. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Albert King, Chief Data Officer of the Scottish Government to discuss the Scottish AI strategy that was published in March 2021.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Felipe Flores, host of Data Futurology Podcast. On his podcast he talks about Data Science through a human lens and discusses the human side of data with leaders from across the globe.
In order for projects to be successful, the time between concept to execution needs to be reasonably set. Far too often, we see the iteration time of AI projects to be months, if not years, from the initial pilot. Additionally, we see organizations run a proof of concept in a controlled lab setting (why?) rather than a pilot using real world systems.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. Data is at the heart of AI. It should be no surprise then that proper data management is crucial for AI projects. This podcast is an excerpt from our Cognilytica Education course “Managing Data for AI”. In this clip we discuss the history of how we stored data in the past and moving from transactional systems to analytics systems.
Continue reading AI Today Podcast: AI Education Series: Managing Data for AI at Cognilytica.
The saying garbage in is garbage out couldn’t be more true when it comes to data being fed into AI and ML models. In this podcast, hosts Kathleen Walch and Ron Schmelzer discuss the importance of data quality and why bad data is a main reason for AI project failure.
Show Notes:
Continue reading AI Today Podcast: AI Failure Series- Data Quality Issues at Cognilytica.
Organizations are finding that data is only part of their AI strategy. In order to fully utilize their data, they need to be able to make sense of that data and effectively communicate the story their data is telling. In this episode of the AI Today podcast, hosts Kathleen Walch and Ron Schmelzer interview Mara Pometti, Global AI Strategist at IBM.
AI and ML projects revolve around data so it’s important to understand how much data you really need. Understanding how to plan, manage, and operationalize AI & ML Projects is crucial for project success. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer continue the discussion around common reasons why AI projects fail.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. When creating ML models it’s important to focus on model evaluation and testing and evaluating AI models vs. the heuristic. This podcast is an excerpt from our Cognilytica Education course “Model Evaluation and Testing”. In this clip we discuss what is overfit and underfit and bias and variance of data.
Continue reading AI Today Podcast: AI Education Series: Model Evaluation and Testing at Cognilytica.
In order for a project to be successful, there needs to be some positive return on the investment (ROI) involved to get this project off the ground and into production. This ROI can be measured by cost savings, but also by people savings, resource savings, and/or time allocation savings.
A common reason we see AI projects fail is that the ROI is not justified.
Continue reading AI Today Podcast: AI Failure Series – ROI Misalignment at Cognilytica.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Jessie J. Smith and Dylan Doyle, hosts of the Radical AI podcast. On their podcast they try to probe and advance the field of Artificial Intelligence Ethics so it was only natural to discuss what they see as the most common themes around responsible and ethical use of AI as well as where we currently stand with ethical AI.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Sanyam Bhutani, host of Chai Time Data Science podcast. As his podcast talks about Data Science, he shares with us where things really stand in enterprises with data science, some of the biggest trends emerging in data and data science today, and some of the mundane but crucial aspects to data science that people need to be aware of.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Alexandra Petrus, host of the Applied AI Pod. On her podcast she talks to anyone who is applying AI today including startup founders, startup engineers, AI community leaders, research scientists, innovation leaders, product builders, passionate AI practitioners.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. There are many paths to data science and different skills are needed for creating successful data scientists. These skills include curiosity, analytical thinking, performing analysis, taking a strong position and arguing that position, being a data driven problem solver, having an impact-driven mindset, and being good at storytelling.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Andy Ilachinski and David Broyles, hosts of the AI with AI podcast. On their podcast they explore the latest breakthroughs in artificial intelligence and autonomy, as well as their military implications so naturally we discussed with them some of the biggest trends they are seeing emerging out of AI today, some of the challenges to AI adoption especially in military applications, and some of the surprising insights and trends they have seen over the 4 years they have hosted their podcast.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Liberty Vittert & Xiao-Li Meng, hosts of the Harvard Data Science Review (HDSR) podcast. On their podcast they discuss news, policy, and business through the lens of data science so they shared ways in which data is being used or misused as well as some of the most interesting articles published in Harvard Data Science Review.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. For AI to have a lasting positive impact it must be done responsibly. In our education we go into great detail explaining and breaking down AI, including fundamentals of AI including terms and concepts of AI and how it all fits together.
Continue reading AI Today Podcast: AI Education Series: Ethical & Responsible AI at Cognilytica.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Craig Smith, host of the Eye on AI podcast. Just like with our podcast, Craig interviews thought leaders in AI. He shares with us interesting insights and common themes he has seen among guests as well as what guests have surprised him.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. In this episode hosts Kathleen Walch and Ron Schmelzer interview Alex Castrounis, the host from AI with Alex YouTube channel and Why of AI founder. We discuss the area of responsible AI including ethics, fairness, and safety as well as some of the biggest trends emerging in AI today.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. In our education we go into great detail explaining and breaking down AI, including fundamentals of AI including actually learning the terms and concepts of AI and how it all fits together. This podcast is an excerpt from our Cognilytica Education course “Data Preparation of AI”.
Continue reading AI Today Podcast: AI Education Series: Data Preparation for AI at Cognilytica.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview David Asboth and Shaun McGirr, the hosts from Half Stack Data Science podcast. As their podcast talks about realities of Data Science in the enterprise, they share with us where things really stand in enterprises with their data science practices and some of the biggest trends emerging in data and data science today.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Francesco Gadaleta, host of the Data Science at Home podcast. As his podcast talks about about data and data science trends, Francesco shares with us some of the biggest trends emerging in this area today as well as how organizations are dealing with and managing their data.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. In our education we go into great detail explaining and breaking down AI, including fundamentals of AI including actually learning the terms and concepts of AI and how it all fits together. This podcast is an excerpt from our Cognilytica Education course “Fundamentals of AI”.
Continue reading AI Today Podcast: AI Education Series: Fundamentals of AI at Cognilytica.
On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Andrey Kurenkov and Sharon Zhou from the Let’s Talk AI Podcast. As their podcast covers the latest AI news, we discussed what they are seeing as some of the biggest trends emerging out of AI today.
Automation has provided tremendous value to organizations and agencies of all sorts. However, if you want to see real value from automation, and in particular Robotic Process Automation (RPA), it’s important to know what these bots can and can’t do, and how AI is being applied to help handle more complex tasks.
Hosts Kathleen Walch and Ron Schmelzer walk through different methodologies including the Cognitive Project Management for AI (CPMAI) methodology to provide you with the foundation needed for project success, especially as you incorporate AI into your intelligent automation projects.
This podcast episode is part of our AI Education series and provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. In this podcast we’re sharing a clip from our Best Practices & Methodologies for Successful AI Implementation course. Knowing best practices for implementing AI on a large scale is critical for the success of your project.
Many companies are trying to adopt AI at their organization. However, it’s important to have the right mindset and methodologies in place when adopting a transformative technology. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Sagar Indurkhya who is Head of NLP at Virtualitics. He shares with us challenges he has seen organizations face regarding AI and ML adoption, especially for non-technical users.
The legal profession is still largely dominated by humans. However, AI and ML is steadily being adopted, enhancing legal processes and activities of all sorts. In this episode of the AI Today podcast, Cognilytica analysts interview Rick McFarland, Chief Data Officer at LexisNexis. He shares with us some of the challenges with AI adoption in the legal profession as well as some of the opportunities he sees around domain specific AI-driven Q&A platforms.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. In our education we go into great detail explaining and breaking down AI, including applications of AI. Because, it’s one thing to learn the terms and concepts of AI but it’s another thing to see how AI can actually be applied.
Continue reading AI Today Podcast: AI Education Series: Applications of AI at Cognilytica.
AI and advanced big data analytics have been transforming organizations and helping them get answers from their largest datasets for years. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Antonio Cotroneo, Director of Technical Content Strategy at OmniSci. He shares how big data analytics has evolve over the past few years, how different industries are embracing AI and ML, and where the future is headed when it comes to AI usage.
At Cognilytica we’re spending lots of time educating our customers about Artificial Intelligence and related topics and areas. This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription where we dig deeper into the foundations of Data Science. The course is for those looking to get a foundational level overview of data science and provides a foundation of data science concepts, key terms, and additional knowledge and competencies needed to perform analysis.
Continue reading AI Today Podcast: AI Education Series: Foundations of Data Science at Cognilytica.
In this episode of the AI Today podcast we’ll share some of our insights and key findings from a recent Cognilytica market intelligence coverage area. We’ll be digging deeper into the state of worldwide laws and regulations and in particular data and AI laws. In recent research, Cognilytica analyzed over 200 countries with specific emphasis of various regions, states, and territories to figure out the real state with regards to laws and regulations around AI and related areas.
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. While automation is not intelligence, the real value of automation, especially software automation and Robotic Process Automation (RPA) comes from removing the bot from the human. In this podcast we’ll explain in more detail what attended and unattended bots are as well as the benefits of each.
The role of automation, and more intelligent forms of process automation, have played a big role for companies during the pandemic. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview James Spencer who is a Solutions Engineer Manager at Blue Prism. He shares with us how important robotic process automation (RPA) has become since the pandemic dramatically changed the way people work, examples of RPA in practice, as well as what he predicts the future of process automation will be and how AI is changing process automation for the better.
Heineken has leveraged AI and ML to help with a variety of things at the company . In this episode of the AI Today podcast we interview Raam Roch Hai who is Engineering Chapter Lead at Heineken. He shares with us examples of how Heineken has leveraged AI and ML, some of the challenges highly distributed organizations like Heineken face with adoption of ML and AI, as well as general issues and challenges related to enterprise data science.
Continue reading AI Today Podcast: AI at Heineken, Interview with Raam Roch Hai at Cognilytica.
For many years companies in the financial services industry have been at the forefront of using technology to help with many operations and processes. In this interview podcast hosts Kathleen Walch and Ron Schmelzer interview Sravan Kasarla, Chief Data Officer (CDO) of Thrivent Financial. He discusses how AI is currently being applied in financial services, where the financial services industry rates in their adoption of AI compared to other industries, as well as how can companies create a responsive business especially from an AI perspective.
AI Ethics is a critical topic that organizations adopting or building AI systems need to consider. In recent research, Cognilytica analyzed over 60 ethical AI frameworks produced by governmental organizations, corporations, multinational groups, non-profits, and other groups. We learned a lot about the state of those AI Ethics frameworks, and this podcast will share some of those insights that will help you as a builder, user, or participant in the AI ecosystem.
Continue reading AI Today podcast: The State of Ethical AI Frameworks 2021 at Cognilytica.
To the surprise of some, the National Science Foundation (NSF) is a very large funder of many AI projects every year. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Erwin Gianchandani, Deputy Assistant Director, Computer and Information Science and Engineering at National Science Foundation. He discusses some of the projects that the NSF has funded.
As organizations continue to hire more data scientists it’s important to make sure they are being utilized to emphasize their skill sets. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Ylan Kazi, Vice President, Data Science and Machine Learning at UnitedHealth Group. He shares with us his thoughts on why it’s important to leading data scientists the right way, what are some of the key traits you look for when hiring data scientists, as well as some of the barriers to ML adoption he has seen.
The Federal Government continues to modernize their management of data, including data governance and analytics. In the episode of the AI Today podcast we interview Justin Marsico who is the Chief Data Officer at the Bureau of the Fiscal Service, a part of the United States Department of the Treasury. Justin oversees the Fiscal Service’s provision of data to the public, including on USAspending.gov and shared with us some of the unique opportunities around data at the federal level, challenges in data governance, security, ownership, as well as what areas of seeing AI he sees effectively being used in the federal government.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Matt Chambers, Principal Architect & Juan Buhler, Sr. Data Science Engineer at Boon AI. They share with us some challenges they see organizations face today with trying to make sense of their unstructured data, especially video data, as it relates to AI.
On the AI Today podcast we often discuss how AI is being applied at the federal level. However many states are also facing many of the same data challenges, hiring needs, and adopting AI technologies as well. In the episode of the AI Today podcast we interview Joy Bonaguro, Chief Data Officer for the state of California.
As companies begin to move machine learning models into production there are a variety of factors that need to be addressed. In this podcast Cognilytica analysts Kathleen Walch and Ronald Schmelzer interview Gideon Mendels, CEO of Comet. He discusses challenges organizations face today with trying to bring ML models into production, why it’s important to have a tool for data scientists and teams to track, compare, explain and optimize experiments and models, and where ML Ops fits into the overall ML ecosystem.
The finance and banking industries have long been ahead of other industries with their adoption of AI. From fraud detection, to roboadvising, to NLP applications the finance industry is adopting every pattern of the Seven Patterns of AI. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Agus Sudjianto, Executive Vice President, Head of Corporate Model Risk at Wells Fargo.
AI is transforming the federal workplace, allowing employees to work more productively and efficiently. However with this technology comes the need for oversight considerations for policymakers and federal managers related to such issues as the right to privacy, accuracy of results, safety assurances, and algorithmic oversight. In this episode of the AI Today podcast we interview Dr.
Successful MLOps not only requires strong collaboration between the AI data team, AI model team, and DevOps it’s the ability to effectively manage and mitigate risk across the deployment, integration, scale, monitoring, and compliance stages of an AI project. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Kfir Yeshayahu who is the Senior Vice President of Products at Veritone.
As AI continues to move into the mainstream and more companies are looking to bring AI and ML into their organizations, the tools have also evolved to keep up with the changing demand. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schemlzer interview Sivan Metzger, Managing Director of MLOps and Governance at DataRobot.
As companies move from building models to buying models the focus shifts from tooling and platforms focused solely on model development to tools and platforms focused on the overall usage, consumption, and management of models. In this podcast Cognilytica analysts Kathleen Walch and Ronald Schmelzer interview Nir Bar-lev, CEO of ClearML to discuss the overlap between DevOps and MLOps, where ML Ops is fitting into the overall ML ecosystem, and how he thinks it will continue to evolve over the next few years.
As companies move from AI and ML projects as just a concept to actual production they need to find value in these projects. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Ahmer Inam and Mark Persaud at Pactera Edge. They discuss some of the challenges they have seen companies face with their data science projects and why they fail to deliver for their executive sponsors and how companies can overcome this.
As companies continue to advance in their adoption of AI and ML, they need a trusted approach to machine learning operations (MLOps). In this podcast hosts Kathleen Walch and Ron Schmelzer interview Harish Doddi who is CEO of Datatron. He shares with us some of the challenges companies face as they use ML models in production.
In the face of the many of the challenges that 2020 represented, AI has continued at its unrelenting pace of adoption, investment and growth in both the private and public sectors. In this podcast hosts Kathleen Walch and Ron Schmelzer share their AI market predictions and forecasts for where AI will make waves in 2021 including the continued worldwide adoption of AI and ML, hot markets including the ML Platforms space, ML Ops players, and data labeling.
Continue reading AI Today Podcast: 2021 AI Market Predictions at Cognilytica.
On the AI Today podcast we often discuss how AI is being applied at the federal level. However many states are also applying automation and AI technologies as well. In the episode of the AI Today podcast we interview Dorman Bazzell, Chief Data Officer for the state of North Dakota. He shares with us some of the unique challenges around data, data science and data privacy at the state level.
In this episode of the AI Today podcast we wanted to highlight our upcoming Machine Learning Lifecycle 2021 Conference taking place Jan 26-28, 2021. The 5 main areas of focus for sessions and content during the conference include: ML Model Development, ML Model Management, ML Operations (MLOps), ML Model Governance, and General Sessions Related to the ML Lifecycle.
With 2020 quickly (thankfully) fading into the rear view mirror it’s time to reflect on the year that was including looking at our predictions for 2020 and see how accurate they were, some of the big AI news, use cases and activity. In this podcast hosts Kathleen Walch and Ron Schmelzer discuss some of the big newsmakers and insights from this year in the world of AI as well as some of the highlight episodes from 2020.
Continue reading AI Today Podcast: A Look Back at AI in 2020 at Cognilytica.
Machine learning systems are core to enabling each of the seven patterns of AI. Machine learning platforms facilitate and accelerate the development of machine learning models by providing functionality that combines many necessary activities for model development and deployment. In this podcast, hosts Kathleen Walch and Ron Schmelzer share high level details for the recent ML Platforms Report 2020 report.
Artificial Intelligence (AI) is rapidly transforming the pharmaceutical and health care industries. No doubt with the recent global pandemic AI and machine learning is being put to use in the fight against the pandemic. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Subroto Mukherjee, Head of Innovation and Emerging Technology, Americas at GlaxoSmithkline Consumer Healthcare.
The energy sector has long used data methods and various technologies to make processes more efficient. However, in heavily regulated industries such as the energy industry there can be some unique challenges to technology adoption. In this episode of the AI Today podcast hosts Ron Schmelzer and Kathleen Walch interivew Dr. Satyam Priyadarshy, who is Technology Fellow and the Chief Data Scientist at Halliburton.
The pace of worldwide AI adoption continues to accelerate. AI is transforming just about every single industry and transforming the way humans work, live, and interact with each other. It’s no surprise then that countries see this technology as so important they are creating their own country level AI strategies. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Gergely Szertics who is leading the transformative programs in the AI strategy for Hungary.
Continue reading AI Today Podcast: AI in Hungary, Interview with Gergely Szertics at Cognilytica.
The US Department of Defense (DoD) takes the topics of topics of Ethics, transparency, and Ethics Policy very seriously. A few years ago the DoD stood up the Joint Artificial Intelligence Center, also referred to as the JAIC, to help figure out how to best move forward with this transformative technology. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Alka Patel, who is Head of AI Ethics Policy at Department of Defense, Joint AI Center.
You may have seen headlines in the news about GPT-3. But, what exactly is it, and, why is it important? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss what GPT-3 is, how it came about, what we can do with it, and the future of GPT-3.
Show Notes:
Continue reading AI Today Podcast: What is GPT-3 and why is it important? at Cognilytica.
The General Services Administration (GSA) has been a very forward thinking agency in the US Federal Government. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Emily Murphy, Administrator of the General Services Administration (GSA). She shares with us how is AI helping with GSA’s mission, what role the Center of Excellence is playing at the GSA, and some of the unique opportunities the public sector has around AI.
AI technologies have been positively impacting a number of industries, and medicine and healthcare is one of these such industries. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Gil Alterovitz, Director of Artificial Intelligence at the Department of Veterans Affairs (VA). He shares how how AI is impacting the VA, details about recently created the National Artificial Intelligence Institute at the VA, and how AI will provide benefits to veterans.
Over the last decade, data and analytics has grown to be more than just a quantitative support function. In this episode of the AI Today we interview Shiv Misra who is the Head of Medicare Retention Analytics at CVS Health. He has a very diverse background working at multiple large organizations. He shares with us how these various companies have approached data, some of the insights and challenges for dealing with data and AI from a healthcare and insurance perspectives, and more.
Data is increasingly playing an important role at organizations, and especially financial institutions. Data privacy is increasingly becoming an important topic and something that should be considered through all stages of the data lifecycle and ML model lifecycle. In this episode of the AI Today podcast we interview Rajeev Sambyal who is Director, Artificial Intelligence and Innovation at BNY Mellon.
Retailers are turning to artificial intelligence and data science to help solve challenging E-commerce problems. From product recommendation systems to logistics and supply management, AI is helping in a variety of ways. In this AI Today podcast episode we interview Khalifeh Al Jadda, Director of Core Data Science at The Home Depot. He shares with us how The Home Depot is using data science, AI, and ML to help solve challenging e-commerce problems for HomeDepot, some opportunities retail operations face when it comes to AI adoption, as well as some of the challenges involved.
On the AI Today podcast we often discuss how AI is being applied at the federal level. However many states are also applying automation and AI technologies as well. In the episode of the AI Today podcast we interview Carlos Rivero, Chief Data Officer for the Commonwealth of Virginia. He shares will us how automation, advanced data analytics, and AI play an increasing role in state government, some unique challenges around data at the state level, some interesting or surprising insights you can share about how Virginia is using ML and AI and more.
Morningstar has been forward thinking in their use of artificial intelligence and machine learning to enhance various processes. In this episode of the AI Today podcast we interview Shariq Ahmad, Head of Technology for Morningstar’s Data Collection group. He shares with us how Morning is automating data collection, lessons learned along the way, as well as insights on responsible AI.
Voice assistants are increasingly becoming a part of our everyday lives. It should come as no surprise then that one of the visions for voice assistants is to bring voice applications to vehicles. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Shyamala Prayaga, Autonomous Digital Assistant Vision Lead at Ford.
It’s so surprise that the Federal Government is adopting AI. However it’s often less talked about how AI is being adopted at the state and local level. In the episode of the AI Today podcast we interview Dan Hoffman, Assistant City Manager for the City of Gainesville. He shares will us how automation, advanced data analytics, and AI play an increasing role in local government, some unique challenges local governments face with implementing AI solutions and attracting AI talent, and more.
The United States Department of Energy (DOE) has a long history with AI. As the first Director of the Artificial Intelligence & Technology Office (AITO) within the DOE, Cherly has been helping to develop, deliver and manage AI technologies in support of DOE with over 600 AI projects currently in place. In this podcast we explore how AI is impacting the DOE, their perspective on ethics and responsible use of AI, how the DOE is engaging industry and private sector in their AI efforts, and more.