The Data Exchange with Ben Lorica
A series of informal conversations with thought leaders, researchers, practitioners, and writers on a wide range of topics in technology, science, and of course big data, data science, artificial intelligence, and related applications. Anchored by Ben Lorica (@BigData), the Data Exchange also features a roundup of the most important stories from the worlds of data, machine learning and AI. Detailed show notes for each episode can be found on https://thedataexchange.media/ The Data Exchange podcast is a production of Gradient Flow [https://gradientflow.com/].
Episodes
Zhen Lu, CEO of Runpod, joins the podcast to discuss what it means to build an “AI-first” cloud, moving beyond the architectures of the Web 2.0 era.
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Detailed show notes - with links to many references - can be found on The Data Exchange web site.
Yoni Leitersdorf, CEO of Solid, joins the podcast to demystify why simply pointing an LLM at a database for text-to-SQL doesn’t work. He explains the critical need for a semantic layer to provide business context, turning raw data into a “Rosetta Stone” that AI can actually understand.
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Ben Lorica and Evangelos Simoudis discuss some takeaways for AI practitioners from the recent AI Conference. They cover the disconnect between the hype and reality of AI agents in the enterprise, the critical importance of building reliable and trustworthy AI applications, and the potential impact of new H-1B visa policies on tech startups and innovation.
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Jakub Zavrel, CEO of Zeta Alpha, joins the podcast to discuss the practical evolution from traditional enterprise search to powerful “deep research” systems.
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Detailed show notes - with links to many references - can be found on The Data Exchange ...
Andrew Rabinovich, CTO and Head of AI at Upwork, discusses how digital work marketplaces serve as ideal testing grounds for AI agents, exploring their custom reinforcement learning approach called RLEF (Reinforcement Learning from Experience).
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Jay Alammar is Director and Engineering Fellow at Cohere and co-author of the O’Reilly book “Hands-on Large Language Models.”
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Detailed show notes - with links to many references - can be found on The Data Exchange web site.
Ben Lorica and Evangelos Simoudis discuss three critical topics for AI practitioners: the complexities of AI regulation, with debates over foundation model oversight versus domain-specific regulations and concerns about IP protection in AI training data.
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In this episode, Anant Bhardwaj, CEO of Instabase, provides a pragmatic guide for AI practitioners building enterprise solutions.
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Detailed show notes - with links to many references - can be found on The Data Exchange web site.
Ben Lorica and David Talby present findings from the 2025 AI Governance Survey of 350+ respondents, revealing that while 30% have AI models in production, there are significant gaps in risk management practices.
🚨 This episode is based on an online presentation, see the YouTube version for a visual presentation.
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Kostas Paralis, co-founder of Typedef , discusses Fenic, an open-source data frame framework designed specifically for AI applications that treats inference as a first-class operation within the query engine.
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Detailed show notes - with links to m...
Ben Lorica and Evangelos Simoudis discuss three critical trends shaping the AI industry: the “Great Hollowing Out” where AI automation is eliminating entry-level positions and disrupting talent pipelines, the financial implications of rapid AI hardware depreciation versus traditional accounting practices, and OpenAI’s shift to router-based model selection as foundation model providers search for sustainable business models.
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Raiza Martin, co-founder of Huxe and former leader of Google’s NotebookLM team, discusses leaving Google at the height of NotebookLM’s success to build an audio-first personal AI companion.
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Detailed show notes - with links to many references - can...
The discussion with CEO Akshay Agrawal covers how Marimo’s AI integration provides runtime context to LLMs for superior code generation, its adoption across industries from cybersecurity to DevOps, and the technical innovations that make notebooks viable for production environments.
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Josh Pantony, CEO of Boosted AI, discusses Alfa, an agentic AI platform that creates persistent AI workers for finance professionals, moving beyond traditional prompt-response AI to proactive, autonomous systems.
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Jennifer Prendki explains that while universal quantum computers are a decade away, specialized quantum accelerators are already tackling AI problems in finance and pharma. She argues the biggest hurdle isn’t the hardware but the profound software and infrastructure gap, as fundamental principles like the “no-cloning theorem” break traditional MLOps.
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Sagar Batchu, CEO of Speakeasy, joins the podcast to discuss the critical shift in API development as AI agents become primary consumers.
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Detailed show notes - with links to many references - can be found on The Data Exchange web site.
In this episode, Yishay Carmiel and Roy Zanbel of Apollo Defend discuss the rapidly evolving landscape of voice AI and its emerging security threats.
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Detailed show notes - with links to many references - can be found on The Data Exchange web...
Shreya Shankar is a PhD student at UC Berkeley in the EECS department. This episode explores how Large Language Models (LLMs) are revolutionizing the processing of unstructured enterprise data like text documents and PDFs. It introduces DocETL, a framework using a MapReduce approach with LLMs for semantic extraction, thematic analysis, and summarization at scale.
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Douwe Kiela, Founder and CEO of Contextual AI, discusses why RAG isn’t obsolete despite massive context windows, explaining how RAG 2.0 represents a fundamental shift to treating retrieval-augmented generation as an end-to-end trainable system.
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Zach Lloyd, Founder/CEO of Warp, joins the podcast to discuss how Warp is revolutionizing the command-line terminal by integrating AI.
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Detailed show notes - with links to many references - can be found on The Data Exchange web site.
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