The Data Exchange with Ben Lorica

By Ben LoricaNews Technology Business News Tech News

The Data Exchange with Ben Lorica episodes

July 11 AI Is Producing More Code, but Is It Producing More Value?
Ben Lorica sits down with Evangelos Simoudis to unpack why open-weights models are closing the gap with frontier labs and pushing enterprises toward “corporate AI sovereignty.” They then apply an attenuation-funnel lens to AI coding tools — more code, but far less shipped software and usage growth — before turning to “neoconsulting,” the outcomes-based services model reshaping Accenture, Palantir, and the big Indian IT firms.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
57 min
July 09 Stop Renting Generic Intelligence for Your Business
Manos Koukoumidis, CEO of Oumi, returns to the podcast to make the case that most enterprises are wildly inefficient, using bloated generic AI models for tasks that demand specialized ones. He argues that companies should stop renting intelligence from frontier labs and start owning, customizing, and compounding it.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
54 min
July 02 The Data Layer Enterprise AI Has Been Missing
Andrew Moore, CEO of Lovelace, former head of Google Cloud AI, and former dean of Carnegie Mellon’s School of Computer Science, joins the podcast to discuss YottaGraph, a knowledge graph growing by a billion facts a week that serves as a context engine for enterprise AI agents. He explains why fully automatic knowledge graph construction is the only viable path at scale, why entity resolution remains a brutal engineering problem, and how graph theory tricks make million-node queries answerable in under a second.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
51 min
June 25 The Hidden Failure Modes of AI Agents
Ben Lorica speaks with Helen Gu, CEO of InsightFinder AI and professor at North Carolina State University, about why reliability is becoming a central challenge for enterprise AI. They discuss AI incident response, monitoring agents in production, domain-specific small language models, causal inference for operational data, and why the “last 1%” of accuracy and reliability is often the hardest part of deploying AI systems.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
52 min
June 18 The Data Stack Wasn't Built for AI — Here's What Comes Next
Ben Lorica talks with Chang She, co-founder and CEO of LanceDB, about the limitations of traditional analytical data tools like Pandas and Parquet when applied to AI workloads. They discuss the rise of the “multimodal lakehouse,” the unique data storage and retrieval challenges introduced by AI agents, and how LanceDB provides both lightweight embedded memory and massive-scale infrastructure.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
41 min
June 13 The SaaSpocalypse Is Coming — But Don't Count Out the Incumbents
Ben Lorica is joined by Evangelos Simoudis for a wide-ranging check-in on how AI is reshaping mobility, enterprise software, and corporate strategy.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
42 min
June 11 AI Agents Are Implemented, Not Adopted
Ben Lorica speaks with Hamza Tahir, co-founder of Kitaru, about what it takes to move AI agents from demos to production. They discuss the difference between workflows and agents, why “harness engineering” is becoming a useful frame for application builders, and why long-running agent workloads require orchestration, durable execution, retries, state management, and human-in-the-loop semantics.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
46 min
June 04 Why Your AI Agent Isn't Ready to Ship (And How to Know When It Is)
In this episode, host Ben Lorica sits down with Zhou Yu, associate professor of computer science at Columbia University and co-founder of Arklex AI.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
44 min
May 28 Why Foundation Models Haven’t Replaced Classical Machine Learning
In this episode, Ben Lorica sits down with Doris Xin and Moustafa Abdelbaky, co-founders of Disarray, to discuss why classical machine learning models remain essential despite the rise of foundation models and LLMs.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
53 min
May 21 When "Garbage In, Garbage Out" Gets It Wrong
Ben Lorica speaks with Terrence Lee-St. John, founder of Enli and lead author of From Garbage to Gold: A Data Architectural Theory of Predictive Robustness.
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Detailed show notes and transcript, can be found on The Data Exchange web site.
44 min

About The Data Exchange with Ben Lorica

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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…