The Data Exchange with Ben Lorica

Philip Rathle, CTO of Neo4j, joins the podcast to discuss the rising popularity of graph-enhanced retrieval augmented generation (GraphRAG).  He also discusses the potential impact of the new GQL graph query language standard. [Link to the demo that Philip showed.]

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Detailed show notes can be found on The Data Exchange web site.

Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode is part of our series of monthly roundups and covers: the proposed California Senate Bill 1047 for regulating AI models, including its feasibility and potential unintended consequences. We also discuss the rising popularity of graph retrieval augmented generation (GraphRAG) techniques to mitigate hallucinations in large language models, while acknowledging the current limitations and future potential of integrating symbolic and statistical AI approaches. Additionally, we explore the concept of AI avatars in the workplace, highlighting the challenges and ethical considerations surrounding digital twins and agent-based systems.

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Detailed show notes can be found on The Data Exchange web site.

Jiwoo Hong and  Noah Lee of KAIST AI are co-authors of ORPO: Monolithic Preference Optimization without Reference Model. 

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In this episode, Pete Warden introduces his company, Useful Sensors, which focuses on developing AI solutions for consumer electronics and appliances.  [This episode originally aired on Generative AI in the Real World, a podcast series I’m hosting for O’Reilly.]

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Detailed show notes can be found on The Data Exchange web site.

Ken Liu,  Ph.D. student in Computer Science at Stanford, is the author of Machine Unlearning in 2024. We explore the concept of machine unlearning, a process of removing specific data points from trained AI models.

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Joao (Joe) Moura is the  founder of crewAI, an open-source platform that simplifies the development and deployment of AI agents, allowing users to build autonomous systems for various tasks using multiple large language models.

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Detailed show notes can be found on The Data Exchange web site.

Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode is part of our series of monthly roundups and covers: Llama 3 and other recent LLMs, the rise of open foundation models, the evolution of AI agents, and the importance of data engineering. We also explore the limitations of leaderboards in evaluating AI models and touch upon the ethical and societal implications of AI development.

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Detailed show notes can be found on The Data Exchange web site.

Gunther Hagleither is co-founder of Waii, a startup that provides an API enabling businesses to seamlessly integrate text-to-SQL functionality into their products.

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Detailed show notes can be found on The Data Exchange web site.

In this episode we explore the latest developments in artificial intelligence with a focus on the 2024 Artificial Intelligence Index Report, edited by Nestor Maslej from Stanford’s Institute for Human-Centered Artificial Intelligence.

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Detailed show notes can be found on The Data Exchange web site.

In this episode, Hagay Lupesko, Senior Director of Engineering at Databricks MosaicAI, delves into the creation and aspirations behind DBRX, an innovative open Large Language Model (LLM) designed to bridge the gap between quality and cost-effectiveness for AI applications.

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Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode is part of our series of monthly roundups and covers: recently released large language models,  Constraint-Driven Innovation, highlights from GTC 2024, and Lessons from the First AI Workload Security Exploit.

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Steve Pike is a co-founder of Infield.ai, a startup building tools to help companies upgrade and maintain open source software dependencies, ensuring they stay up-to-date with the latest releases, features, and security fixes.

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Detailed show notes can be found on The Data Exchange web site.

Chetan Gupta is the Head of AI Research at Hitachi. This episode explores the applications and challenges of generative AI in industrial settings.

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Semih Salihoglu  is an Associate Professor at University of Waterloo, and co-creator of Kuzu an open source embeddable property graph database management system. This episode explores the use of large language models (LLMs) for generating queries across different query languages like SQL and Cypher for graphs.

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Sadegh Riazi, CEO and co-founder of Pyte, a startup offering secure, encrypted data collaboration solutions, enabling partners to maximize insights without compromising privacy or data integrity. 

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Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode explores recent developments in AI, including text-to-video models like Sora, frameworks for productionizing AI models, analyses of systems like Google’s Gemini, techniques to improve foundation models, AMD’s software innovations for AI acceleration, and knowledge graph augmentations of language models.

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Jerry Kaplan is the author of the new book “Generative Artificial Intelligence: What Everyone Needs to Know”.  

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This episode is our annual deep dive into the themes and trends of AI in 2024, emphasizing the democratization of AI hardware, advancements in generative AI models, and the integration of AI into various enterprise processes. 

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Bryan Cantrill, CTO and Co-founder of Oxide Cloud Computer, leads a startup delivering integrated hardware and software solutions for enterprises seeking cloud computing systems with hyperscaler agility. Oxide specializes in vertically integrated, scale-ready cloud infrastructure tailored for mainstream business needs.

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Evangelos Simoudis is a seasoned venture investor and a senior advisor to global corporations, and Managing Director at Synapse Partners, a company that invests in startups developing enterprise applications that exploit Big Data and AI.

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Sharon Zhou and Greg Diamos are co-founders of Lamini, a startup at the forefront of enabling enterprise adoption of large language models (LLMs). We discussed Lamini’s work with AMD, which focused on closing the gap between AMD hardware capabilities and software integration in LLM applications.

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Uri Gneezy is Professor of Economics and Strategy at UC San Diego, and author of our 2023 Book of the Year, “Mixed Signals: How Incentives Really Work”.

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Dmitriy Ryaboy is the VP of AI Enablement at Ginkgo Bioworks, a startup that uses machine learning and AI to develop a wide range of applications.  The conversation focuses on the intersection of AI, machine learning, and biology, particularly in the field of synthetic biology.

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Jian Zhang is co-founder, CTO, VP Engineering at Nexusflow AI a startup that uses Generative AI to build tools for Cybersecurity.  This conversation revolves around the integration of various AI components, with a specific focus on cybersecurity and function calling copilots.

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Sarmad Qadri, founder and CEO of LastMile, a startup building an AI developer platform for engineering teams. This conversation delves into key artificial intelligence and machine learning themes, focusing on injecting software engineering rigor into the development of LLM and GenAI applications.

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Nir Shavit, Professor at MIT’s Computer Science and Artificial Intelligence Laboratory, is also a Founder of Neural Magic, a startup working to accelerate open-source large language models and simplify AI deployments.

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Chirag Yagnik is a co-founder of Arta , a company that harnesses innovations in artificial intelligence and software to develop wealth management solutions. Arta aims to democratize access to sophisticated investment tools typically only available to ultra-high net worth individuals through family offices.

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Juan Sequeda (Principal Scientist & Head of AI Lab) and Dean Allemang (Principal Solutions Architect) are knowledge graph experts at data.world, a startup that offers a data catalog powered by a knowledge graph to help organizations better understand and gain value from their data.

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Max Mergenthaler (CEO) and Azul Garza Ramirez (CTO) are co-founders of Nixtla, a startup that seeks to make cutting-edge predictive insights widely accessible.  In this episode we discuss TimeGPT, Nixtla’s new frontier model for time series forecasting.

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Waleed Kadous, Chief Scientist at Anyscale, is one of my go-to experts for best practices on building applications leveraging large language models.

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Kieren James-Lubin, CEO of BlockApps and the Co-Chair Technical Steering Community for the Enterprise Ethereum Alliance. 

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Earlier this year, I had a conversation with Sam Ramji, Chief Strategy Officer at DataStax and host of the Open||Source||Data podcast,  where we talked about the evolution of big data and AI technologies. I’m airing our original conversation in its entirety on this holiday weekend in the U.S. 

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Malte Pietsch is co-founder & CTO of Deepset, the company behind the popular open source project Haystack, an orchestration framework for LLMs.

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In this episode, Paco Nathan and I dive into insights from the inaugural AI Conference in San Francisco (video of talks can be found here). 

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Semih Salihoglu  is an Associate Professor at University of Waterloo, and co-creator of Kuzu an open source embeddable property graph database management system.

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Philipp Moritz (Co-founder and CTO) and Goku Mohandas (ML and Product Lead) of Anyscale do a deep dive into retrieval augmented generation (RAG) and large language models (LLMs). 

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Bill  Marcellino is a senior behavioral scientist at the RAND Corporation, and Nathan Beauchamp-Mustafaga, policy researcher at the RAND Corporation. They are the principal researchers behind the new report  “The Rise of Generative AI and the Coming Era of Social Media Manipulation 3.0”. 

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Yucheng Low, Cofounder & CEO of  XetHub, discusses the challenges of managing large-scale machine learning assets and the need for version control.

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Christopher Nguyen is CEO and Co-founder of Aitomatic, a startup that builds virtual advisors tailored with domain-specific expertise, primarily catering to industrial AI applications. 

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Sudhir Hasbe, Chief Product Officer at Neo4j, and a longtime technical and product leader in the data management space.

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Yishay Carmiel is the CEO of Meaning, a startup at the forefront of building real-time speech applications for enterprises. We discuss the state of AI for speech and audio, including trends in Generative AI, automatic speech recognition, diarization, restoration, voice cloning, speech synthesis and more.

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Casey Ellis is Founder/Chair/CTO of Bugcrowd, a Crowdsourced Cybersecurity Platform. Bugcrowd recently released “Inside the Mind of a Hacker 2023”, an interesting report that provides insights into the motivations, challenges, and specializations of hackers, as well as security implications of AI.

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Daniel Lenton is the CEO of Ivy, a suite of tools designed to accelerate AI Model Development and Model Deployment. Ivy serves as a glue that connects various frameworks and compiler infrastructures, making them compatible. 

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Andrew Burt is the Managing Partner at Luminos.Law, the first law firm focused on helping teams manage the privacy, fairness, security, and transparency of their AI and data — including generative AI systems.  We explore the state of risk and compliance in light of generative AI. This episode further explores the challenges and risks posed by AI, and the implications of the FTC probe into OpenAI, as well as the NIST AI Risk Management Framework.

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Michele Catasta is VP of AI at Replit, an AI-powered software development platform that allows teams to build and deploy applications on any device, without any setup required.

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Alex Chao is a Product Manager at Microsoft focused on Semantic Kernel, an open-source AI and LLM orchestrator. Semantic Kernel (SK) is a lightweight SDK that makes it easy to integrate AI models and plugins into applications. 

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Steve Hsu wears many hats, but most recently he is co-founder of SuperFocus, a startup building LLM-backed knowledge co-pilots for enterprises.

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Brian Raymond is the founder of Unstructured, a startup building open source data pre-processing and ingestion tools specifically for Large Language Models (LLMs). 

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Emil Eifrem is co-founder and CEO of Neo4j, the leading graph database and graph data science software provider. We discussed a range of topics including: the current state of graph databases, graph data science and graph neural networks, vector databases, the interplay between LLMs, knowledge graphs, and graph databases.

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David Talby is the CTO and Founder of John Snow Labs, the company behind two popular open source projects: Spark NLP and LangTest.  In this episode we focus on LangTest, an open-source Python library designed to help developers deliver safe and effective Natural Language Processing (NLP) models. [Note: After we recorded this episode, NLTest was renamed to LangTest.]

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Jeff Jonas is Founder and CEO of Senzing, a startup focused on democratizing entity resolution – making this deceptively complicated task easy for programmers to use and deploy.

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Jerry Liu is CEO and co-founder of LlamaIndex, an open source project and startup that builds tools that enable teams to augment LLMs with their own private data. 

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Tim Davis is the Co-Founder & Chief Product Officer of Modular, a startup focused on building tools to help simplify AI infrastructure.

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Andrew Feldman is CEO and co-founder of Cerebras, a startup that has released the fastest AI accelerator, based on the largest processor. We discussed Cerebras-GPT, a family of language models that have set new benchmarks for accuracy and compute efficiency, with sizes ranging from 111 million to 13 billion parameters.

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Louis Brandy is  VP of Engineering at Rockset, the real-time search and analytics database startup formed by the creators of the popular open source project, RocksDB.

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Amin Ahmad, the co-founder of Vectara, has played a crucial role in developing a powerful API platform specifically tailored for developers.

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Jonas Andrulis is the Founder & CEO Aleph Alpha, a startup that provides enterprise software solutions backed with their own large language models and multimodal models

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Alex Remedios, founder of Treebeardtech, leads a London-based consulting firm dedicated to assisting machine learning teams in constructing dependable, secure, and adaptable cloud infrastructures crucial for delivering business-critical artificial intelligence solutions. 

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Patrick Hall, is co-founder of BNH and a visiting faculty member of decision sciences at the George Washington University School of Business.  Agus Sudjianto, EVP, Head of Corporate Model Risk at Wells Fargo. We explore several topics covered in the new book Machine Learning for High-Risk Applications, co-authored by Patrick and with a foreword by Agus.

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Omar Maher is Director of Product Marketing at Parallel Domain, a startup that is advancing machine perception capabilities by harnessing the power of synthetic data. We delve into the growing adoption of synthetic data and the factors driving its use. We discuss major developments in synthetic data generation and its overlap with Generative AI. The conversation also covers data privacy, intellectual property, the generation of structured data like LiDAR, the current state of adoption, and key research directions to overcome existing challenges.

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Simon Chan is the General Partner at Firsthand Alliance, a venture capital fund focused on the future of B2B and enterprise software. We explore the evolution of AI, cloud computing, and business collaboration tools, revealing how a new generation of generative AI technologies is enabling applications to generate content and drive transformative innovation across various industries.

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Gev Sogomonian is co-author of AimStack, an open-source, self-hosted AI metadata tracker that logs all your AI metadata, such as experiments and prompts, and provides a user-friendly UI for comparing and observing them. It also offers an SDK for programmatically querying tracked metadata.

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Raymond Perrault is a Distinguished Computer Scientist at SRI International, and Co-Director of the Steering Committee for the AI Index, an annual report that tracks, collates, distills, and visualizes data relating to AI, to help inform decision-makers and teams to take meaningful action for responsible and ethical AI. 

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Hagay Lupesko, is VP Engineering at MosaicML, a startup that enables teams to easily train large AI models on their data and in their own secure environment. We discuss the the evolution of cloud based machine learning (from “traditional” ML through LLMs), his experience building machine learning applications at leading technology companies, and the need for companies to build their own custom foundation models.

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Jakub Zavrel is the Founder and CEO at Zeta Alpha, a premier Neural Discovery Platform that utilizes cutting-edge Neural Search technology to enhance the way you and your team uncover, arrange, and disseminate knowledge. Our conversation focuses on the latest developments in artificial intelligence, taking inspiration from their recent viral article featuring the top the 100 most cited AI papers of 2022.

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Chris Wiggins is a Professor at Columbia University and the Chief Data Scientist at the NYTimes.  He is also co-author of a fascinating new historical exploration of how data has been used as a tool in shaping society, from the census to eugenics to Google search. How Data Happened traces the trajectory of data and explores new mathematical and computational techniques that serve to shape people, ideas, society, and economies.

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Paras Jain and Sarah Wooders are graduate students at UC Berkeley’s Sky Computing Lab. They are part of the team behind Skyplane, and open source project that accelerates wide-area transfers in the cloud via overlay routing and parallelism. 

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Pablo Villalobos is a Staff Researcher at  Epoch, and lead author of the recent paper “Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning”.  We discuss the key findings in this paper, as well as a related study Pablo conducted on scaling laws. 

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Jinsung Yoon (Senior Research Scientist) and Sercan Arik (Staff Research Scientist and Manager) are part of the Google team behind EHR-Safe,  a set of tools for generating highly realistic and privacy-preserving synthetic Electronic Health Records.

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Brandon Jenkins, Co-founder and COO of Fundrise, the largest direct-to-individuals alternative investment platform in the country. Our conversation centered on their recent foray into technology investing, specifically startup companies in the data infrastructure space. 

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Zongheng Yang, is a researcher in the Sky Computing Lab at UC Berkeley, a multi-year research initiative that utilizes distributed systems, programming languages, security and machine learning to separate the services that a company requires from the choice of a specific cloud. He provides a detailed overview and update on SkyPilot, a groundbreaking intercloud broker that views the cloud ecosystem as a unified and integrated entity rather than a collection of disparate, largely incompatible clouds. SkyPilot enables users to run Machine Learning and Data Science batch jobs on any cloud, realize substantial cost savings, access the best hardware across clouds, and enjoy higher resource availability.

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Jesse Anderson, Evan Chan, and I delve into the current developments and possibilities within the realm of data engineering and platforms. As the foundation for artificial intelligence and machine learning, data plays a crucial role in the advancement of these technologies.

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This week we discuss AI regulations with Gabriela Zanfir-Fortuna is VP for Global Privacy at the Future of Privacy Forum, and Andrew Burt, Managing Partner at BNH, the first law firm focused on AI and Analytics.

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Dylan Patel is the Chief Analyst at SemiAnalysis,  a boutique semiconductor research and consulting firm focused on the semiconductor supply chain from chemical inputs to fabs to design IP and strategy. In this episode, we discuss the emerging open source software stack for PyTorch that makes it easier and more accessible to implement non-Nvidia backends (see his recent post).

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Peter Norvig (of Google and Stanford) and Alfred Spector (of MIT) are part of the team of authors behind the must-read book Data Science in Context: Foundations, Challenges, Opportunities. We discussed their recent book and tool a deep dive into their Data Science Analysis Rubric, and we also talked about a trending topics in AI including looming regulations, synthetic data, and Large Language and Foundation Models.

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Percy Liang is Associate Professor of Computer Science and Statistics, and Director of the new Center for Research on Foundation Models at Stanford University. We discussed a new suit of tools (HELM) designed to help users and researchers understand language models in their totality. We also discuss recent trends in AI including the rise of Generative AI and Foundation Models.

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Jenn Webb, special correspondent and managing editor at Gradient Flow, recently organized a mini-panel to discuss themes and trends for 2023. The panel consisted of myself and Mikio Braun. More information on these trends can be found in our Annual Trends Report, which is available for free download (see details below).

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Given the growing interest in Generative AI, we revisit a conversation with Mark Chen, Research Scientist at OpenAI and part of the team behind DALL·E 2, a new AI system that can create realistic images and art based on natural language descriptions. 

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On this special end of the year episode, we revisit conversations with two data science leaders in the e-commerce space:

1. Wendy Foster, Director, Engineering & Data Science at Shopify.
2. Olivia Liao, Senior Director of Data Science at Stitch Fix.

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Shayan Mohanty is the CEO of Watchful, a modern and interactive solution that places the control of data labeling back in the hands of data scientists, machine learning practitioners, and subject matter experts. This podcast focuses on a data management system (written in Rust) they built to support the level of automation and interactivity required to support Watchful.

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Frank Liu is Director of Operations & ML Architect at Zilliz, the company behind Milvus,  an open source vector database. We discuss their recent VLDB paper (“A Cloud Native Vector Database Management System”) that describes recent updates to Milvus, as well as vector databases and vector search in general.

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Ira Cohen is co-founder, Chief Data Scientist at Anodot, a startup that uses time series tools to monitor  business data in real time, so organizations can proactively resolve revenue, cost, and customer experience issues before they impact business performance. We recently wrote a well-received post that provided a detailed overview on the state of technologies for collecting, storing, and unlocking time series. 

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Roy Schwartz is Professor of Natural Language Processing at The Hebrew University of Jerusalem. We discussed a recent survey paper that Roy co-wrote that presented a broad overview of existing methods to improve NLP efficiency through the lens of traditional NLP pipelines. 

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On this Thanksgiving holiday weekend in the U.S., we revisit a Twitter Spaces conversation I had with

• Andrew Burt, Managing Partner at BNH1, the first law firm focused on AI risks.
• Bob Friday, Chief AI Officer at Juniper Networks.

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Hung Bui is the CEO of VinAI, a premier Artificial Intelligence research-based company developing world-class products and services. Hung assembled the VinAI team just over three years ago and they are now among the Top 20 Global Companies in AI Research in 2022. 

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Bob van Luijt, is CEO of SeMI Technologies, the company behind the popular vector search engine Weaviate.   Bob describes their key features and core components, popular use cases, and he also provides an overview of Weaviate’s near-term roadmap. We also discuss how vector search engines compare with existing data management systems.

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Federico Garza and Max Mergenthaler Canseco are both CTOs and co-founders of Nixtla, a startup building developer-friendly software that helps data scientists deploy predictive pipelines.

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Christopher Nguyen is CEO and cofounder of Aitomatic, a startup that uses a knowledge-first approach to build and deploy machine learning solutions, with a focus on industrial applications (manufacturing and other physical settings).

Join us at K1st World, a fantastic symposium and networking event slated for November 16 & 17. Use the discount code GRADIENTFLOW60 to attend in person or online.

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Ram Sriharsha is VP of Engineering and R&D at Pinecone, a startup that offers a fully managed vector database (not just an index). We discuss Pinecone’s new proprietary storage engine, which was first described around the time we recorded this conversation.

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Karthik Ramasamy, is the Head of Streaming at Databricks. He has extensive experience in streaming, having led teams at Twitter (Apache Heron), Splunk, and Streamlio (Apache Pulsar).

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Piotr Żelasko is Head of Research at Meaning, a startup building an AI platform using speech technologies. He has years of experience in speech technologies, both as a researcher and as a software engineer.  We recorded this episode on the week of the release of Whisper,  deep learning model (from OpenAI) that approaches human level robustness and accuracy on English speech recognition.  Our conversation centered on Whisper and speech recognition, but also touched on the new speech data processing tools (Lhotse, k2, Icefall) that we described in our recent post.

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Yaron Singer is the CEO of Robust Intelligence, a company building tools to help manage and mitigate risks associated with machine learning models and applications.

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Yashar Behzadi is the CEO & Founder of Synthesis AI, a startup that uses synthetic data technologies to enable teams building AI applications, as well as gaming and metaverse applications.

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Sadegh Riazi is CEO and co-founder of CipherMode Labs, a startup building tools that enable data and machine learning teams to build and deploy models directly on encrypted data. CipherMode’s new open source project enables teams to develop and deploy machine learning algorithms using familiar tools, and thus opens up the possibility of using sensitive data in different scenarios both within an organization, and in cooperation with other organizations.

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John Bohannon is a Senior Director of Data Science and Head of Research at Primer AI, an end-to-end machine intelligence solution for textual data. We discussed their process of translating ML research into ML products, through the lens of several use cases.

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Jon Udell is community lead for Steampipe, an open-source tool that populates a database table with data retrieved from APIs. They use Postgres, which means that data is easy to explore and retrieve using SQL.

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Aadyot Bhatnagar, is a Senior Research Engineer at Salesforce, and co-creator of Merlion an open source framework for applying machine learning on time series data.  Merlion supports a wide range of time series learning tasks including forecasting, anomaly detection, and change point detection. 

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Maarten Grootendorst, is a data scientist at IKNL, and more importantly, he’s the author of two open source libraries that I’ve come to love: BERTopic (topic modeling with transformers and c-TF-IDF) and PolyFuzz (fuzzy string matching). Both these projects bring the power of transformers and other leading edge models, and package them with simple APIs, clear documentation, and visualization tools.

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Hamza Tahir and Adam Probst are co-creators of ZenML, an extensible open source framework for building reproducible pipelines. We discuss the current state of ZenML, the many use cases that ZenML has been designed for, and its near-term roadmap. 

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Dr. Omri Allouche is Head of Research at Gong, a company that uses advances in NLP and speech models to identify and highlight risks and opportunities during customer interactions.

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Danny Bickson and Amir Alush are the creators of fastdup, a very impressive free tool for surfacing duplicates, anomalies, and leakage in visual data. In line with its name, it’s fast: fastdup is written in C++ and can handle millions of images easily.

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Mark Chen is a Research Scientist at OpenAI and part of the team behind DALL·E 2, a new AI system that can create realistic images and art based on natural language descriptions.

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Jules Damji is lead developer advocate, and Richard Liaw is an engineering manager at Anyscale, the startup founded by the creators of Ray, the open source project that makes it simple to scale any compute-intensive Python workload.

To learn more about Ray and how to scale machine learning applications, attend the Ray Summit (San Francisco / Aug 23-24)  https://www.anyscale.com/ray-summit-2022?utm_source=gradientflow&utm_medium=DEpodcast

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Rick Lamers is co-Founder and CEO at Orchest, the startup behind an open source project that enables data scientists to create, manage, and execute complex end-to-end data pipelines. 

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Devin Petersohn is CTO and co-founder of Ponder, and the creator of Modin,  a fast, scalable, drop-in replacement for the popular Pandas library. 

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Nick Schrock is founder and Elementl, the startup behind Dagster, a popular open source, data orchestration platform. We discussed recent trends in data engineering and infrastructure, and Dagster’s introduction of software-defined assets, a new approach to managing, maintaining, and orchestrating data declaratively.

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Edmon Begoli, leads the AI Systems R&D section at Oak Ridge National Laboratory (ORNL), where he is also a distinguished member of the ORNL research staff.  Our conversation centered on his upcoming presentation at the Data+AI Summit, where he will describe the four principal categories of Adversarial AI and their future implications.

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Haytham Abuelfutuh is co-founder and CTO of Union, a startup founded by the team behind Flyte, a popular open source project originated by Lyft. Flyte is a workflow automation platform used for many different applications, but especially as an orchestrator for machine learning applications.

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This week’s guest is Hilary Mason, co-founder of Hidden Door, a startup that uses AI and machine learning to help create and power role-playing games (RPG).

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Oren Razon is CEO and co-founder of Superwise, a startup that builds tools to streamline observability for machine learning models. This episode provides a comprehensive overview of tools and best practices for deploying, monitoring, and managing machine learning models in production.

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Jeremiah Lowin is co-founder and CEO of Prefect, the company behind the popular open source data workflow orchestration system with the same name. We discussed the major design changes in Prefect 2.0, their move towards treating “code as workflows”, data engineering challenges facing data and ML teams today, and implications of looming trends in machine learning and AI.

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Sebastian Raschka is lead author of a new book from Packt entitled “Machine Learning with PyTorch and Scikit-Learn”.  He is also an Assistant Professor of Statistics at the University of Wisconsin (Madison), and serves as the Lead AI Educator at Grid.ai. 

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This week’s guests are Ade Fajemisin (Postdoctoral Researcher) and Donato Maragno (PhD Student) of the University of Amsterdam. They were co-authors of a recent paper (“Optimization with Constraint Learning: A Framework and Survey”) that explores how machine learning can be used to learn constraints in optimization problems. 

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This week’s guests are Barret Zoph and Liam Fedus, research scientists at Google Brain. Our conversation centered around Large Language Models (LLM), specifically recent work by Barret, Liam, and their collaborators on efficient scaling of large language models.

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Olivia Liao is Senior Director of Data Science at Stitch Fix, a company that uses data science and expert stylists to deliver personalization at scale. We discuss how they blend data science and domain expertise, how they tune recommendations in light of logistics and supply chain constraints, and how they incorporate new developments in large language models, multimodal  models and Responsible AI.

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Jack Clark is co-director of the AI Index Steering Committee. In this episode we discuss key findings of the fifth edition of the AI Index. The report uses multiple metrics (benchmarks, publications, patents, legislation, etc.) to track progress in AI (mainly deep learning) in key areas that include computer vision, speech recognition, and language models. 

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This week’s guests are Ajay Kulkarni (CEO) and Mike Freedman (CTO), co-founders of Timescale, the startup behind the popular relational database for time-series and analytics. Mike is also a Professor of Computer Science at Princeton University. Our conversation took place a few weeks after Timescale raised a massive funding round and achieved unicorn status. 

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This week’s guest is Wendy Foster, Director of Engineering & Data Science at Shopify. We discussed applications of data science within Shopify, how they organize their data teams, the lifecycle of a data science project within the company, and how they approach emerging challenges like Responsible AI, large language models, and multimodal models.

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This week’s guests are Elham Tabassi of the National Institute of Standards and Technology (NIST) and Andrew Burt, Managing Partner of BNH.ai, the first law firm focused on AI compliance, risk mitigation, and related topics. We discuss the new NIST framework – “AI Risk Management Framework” – intended for voluntary use to manage risks in the design, development and use of AI products and systems.

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This week’s guests are Amit Sharma (Principal Researcher) and Emre Kiciman (Senior Principal Researcher) of Microsoft Research. We talk about practical applications of causal inference, a set of tools and techniques that enable data teams to draw causal conclusions based on data.  Amit and Emre are part of the team behind DoWhy, a new open source library for estimating causal effects based on historical data alone, particularly useful when we cannot run an experiment because of time, expense, or ethical concerns.

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Leo Meyerovich is founder and CEO of Graphistry, a startup building tools to democratize visual graph intelligence and graph machine learning. Leo and I recently wrote a well-received post (“What Is Graph Intelligence?”) making the case for why companies need to revisit graph analytics and graph intelligence.

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This week’s guests are Dia Trambitas-Miron (Head of Product) and David Talby (CTO) of John Snow Labs, the startup behind the popular open source project, Spark NLP. The company also has a suite of products including an NLP platform targeted specifically for the healthcare, pharmaceutical, and biotech sectors.

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Simon Crosby is CTO of Swim.ai, a startup building tools (based on the Swim open source project) for next-generation data and AI applications. Swim is one of several projects (along with Ray and Akka) contributing to interest in the Actor Model for building large-scale machine learning and data applications and infrastructure. 

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Nicholas Boucher is a PhD at Cambridge University where his focus is on security including on topics like homomorphic encryption, voting systems, and adversarial machine learning. He is the lead author of a fascinating new paper – “Bad Characters: Imperceptible NLP Attacks” – which provides a taxonomy of attacks against text-based NLP models, that are  based on Unicode and other encoding systems.

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This week’s guest is Anjali Samani, Director of Data Science and Data Intelligence at SalesForce. We first met during the early days of Faculty, one of the leading data science and AI startups in Europe. Anjali helped design and lead the early Fellowship programs at Faculty (these are intensive bootcamps that turn STEM PhDs and turn them into industrial data scientists).

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Savin Goyal is CTO and co-founder of Outerbounds, a startup building infrastructure to help teams streamline how they build machine learning applications. Prior to starting Outerbounds, Savin and team worked at Netflix, where they were instrumental in the creation and release of Metaflow, an open source Python framework that addresses some of the challenges data scientists face around scalability and version control.

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Moshe Wasserblat is a Senior Principal Engineer at Intel, where he serves as a Research Manager focused on NLP and Deep Learning.

Download a FREE copy of our recent NLP Industry Survey Results:  https://gradientflow.com/2021nlpsurvey/

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Gaurav Chakravorty, is a Senior Manager at  Discord, where he leads the team responsible for machine learning models in the area of search and notification. Prior to discord Gaurav was a manager at Google where he led the team responsible for personalized podcast recommendations.

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This week's guest is Mike Tung, founder and CEO of Diffbot, a startup that crawls the web and offers one of the most comprehensive knowledge graphs accessible through a variety of simple interfaces.

Detailed show notes can be found on The Data Exchange web site.


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In this episode of the Data Exchange, our special correspondent and managing editor Jenn Webb organized a mini-panel composed of myself and my podcast co-organizer Mikio Braun. This conversation took place as we were assembling our list of trends for 2022.

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This episode features conversations with two experts who have helped train and release models that can recognize, predict, and generate human language on the basis of very large text-based data sets. First is an excerpt of my conversation with Connor Leahy, AI Researcher at Aleph Alpha GmbH, and founding member of EleutherAI, (pronounced “ee-luther”) a collective of researchers and engineers building resources and models for researchers who work on natural language models.   Next up is an excerpt from a recent conversation with Yoav Shoham, co-founder of AI21 Labs, creators of the largest language model available to developers.

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Azeem Ahmed, is Director of Engineering at Shopify, where he leads the team that builds the primitives and the API’s used by all data scientists, machine learning engineers, and members of Shopify's engineering team. Our conversation focused on the evolution and design of data and machine learning platforms within Shopify. Azeem and I also discussed broader trends, including the rise of modern data platforms and the maturation of data lakehouses.

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Christopher Nguyen is CEO and co-founder of Aitomatic, a startup building a platform for Industrial AI applications. Christopher previously held executive and leadership roles at organizations tasked with building machine learning solutions for traditional enterprises. Our conversation centered around what Christopher terms, AI Engineering – a new discipline concerned with the qualitative and quantitative design, construction, and operation of systems with artificial-intelligence capabilities.

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This week’s guest is Anshul Pandey, CTO and co-founder at Accern, a startup helping financial services companies build and deploy AI applications via a no-code platform. Our conversation focused on the specific challenges of building AI and NLP applications within financial services.

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Che Sharma is the founder and CEO of Eppo, an experimentation framework that integrates with modern data platforms (cloud lakehouses and cloud data warehouses). We discuss the importance of investing in experimentation tools and the power of having a well-oiled experimentation culture within an organization. Che also explains how modern data platforms enable applications like experimentation frameworks like Eppo.

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Happy Thanksgiving to listeners who celebrate it! This episode features conversations with two experts who have been applying reinforcement learning to problems in industry. First is an excerpt of my conversation with  Nicolas (Nic) Hohn, Chief Data Scientist, McKinsey/QuantumBlack Australia. Nic led a team of data scientists charged with helping America’s Cup winning team,  Emirates Team New Zealand, test new designs for hydrofoils – important sailing boat components that could be modified based on rules set forth by race organizers.  I also include an excerpt of a conversation with Max Pumperla, Data Science Professor at IU International University of Applied Sciences, who at the time of our conversation, was also the Head of Product Research at Pathmind, a SaaS that helps businesses use reinforcement learning in real-world applications.

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This week’s guest is Nikhil Muralidhar,  a Graduate Research Assistant at Virginia Tech College of Engineering. He is the lead author of an excellent survey paper entitled “Using AntiPatterns to avoid MLOps Mistakes”.

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Pardhu Gunnam (CEO) and Mars Lan (CTO), are co-founders of Metaphor Data, creators of the first Modern Metadata Platform. As we noted in a previous post, a metadata fabric is the right foundation for data governance and data discovery solutions, data catalogs, and other enterprise data services. This insight resulted in several metadata systems being created within technology companies a few years ago. In fact, the team at Metaphor created one of the more popular systems – DataHub – while they were at Linkedin.

Video version has a detailed table of contents:  https://www.youtube.com/watch?v=W8ZJHN77Ieg

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This week’s guest is Yoav Shoham, co-founder of AI21 Labs, creators of the largest language model available to developers. Yoav is also a Professor Emeritus of Computer Science at Stanford University, and a serial entrepreneur who has co-founded numerous data and AI startups. 

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This week’s guest is Jeremy Stanley, co-founder and CTO of Anomalo, a startup building SaaS tools to help companies with data quality.   Prior to Anomalo, Jeremy was VP of Data Science at Instacart.

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This week’s guest is Michel Tricot, co-founder and CEO of Airbyte, a startup behind the popular open source project with the same name. While still a relatively young open source project, Airbyte has emerged a favorite among data and platform engineers tasked with building and maintaining data integration systems within companies.

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This week’s guest is Hamel Husain, Staff Machine Learning Engineer at GitHub and a core developer for fastai. Prior to GitHub, Hamel worked on machine learning applications and systems at  Airbnb and DataRobot.

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This week’s guest is Bob Friday, VP and CTO at Mist Systems a Juniper Company.  Bob is a serial entrepreneur and seasoned technologist, and at Mist  his team uses data technologies, machine learning , and AI to “optimize user experiences and simplify operations across the wireless access, wired access, and SD-WAN domains”.

Bob and his team build models from structured, semi-structured, and unstructured data. They have deployed anomaly detection models that rely on deep learning (LSTMs) and have begun exploring the use of graph neural networks for a variety of use cases. They have also built and deployed systems that use recent advances in natural language models. Their virtual assistant provides insight and guidance to IT staff via a natural language conversational interface.

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This week’s guest is Dr. Viviana Acquaviva, Associate Professor in the Physics Department at the CUNY NYC College of Technology and at the CUNY Graduate Center. She is an Astrophysicist with a strong interest in Data Science and Machine Learning.

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This week I have my annual check-in on the state of Julia with Viral Shah, Co-founder and CEO of Julia Computing. Since we spoke last year, Julia continues to make inroads and grow its user base, and Julia Computing closed their $24M Series A round in July.

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This week our special correspondent and editor Jenn Webb and I speak with Jike Chong and Cathy Chang, executives and seasoned leaders of data science teams. Our conversation is focused on their new book “How to Lead in Data Science”.

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In this episode of the Data Exchange, our special correspondent and editor Jenn Webb organized a mini-panel composed of myself and Paco Nathan, author, teacher, and founder of Derwen.ai, a boutique consulting firm specializing in Data, machine learning, and AI.  Of late, Paco has been doing a lot of work with graphs and as such he’s had to immerse himself in the world of graph data management technologies. This conversation is focused on what’s new with graph databases, and why there’s been a resurgence in interest in them. We also discuss use cases of graph databases, graph analytics, and graph neural networks.

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