The Data Exchange with Ben Lorica

Yoon Kim, President and Chief Strategy Officer of TwelveLabs, explains why understanding video takes more than bolting a language model onto a stream of frames. He walks through how TwelveLabs’ two foundation models, Marengo and Pegasus, embed and describe video content at scale, and how the company’s new agent, Jockey, orchestrates them for tasks like security investigations, sports film review, and documentary editing.

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

Andrew Burt, CEO and co-founder of Luminos, joins Ben Lorica to unpack Luminos’s new report, A Practical Guide to Agentic and Gen AI Risk Evals. 

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

Ben Lorica speaks with Denise Teng, partner at Gradient Ventures, about the real state of enterprise AI adoption, why security and data privacy still slow deployment, and why open weights may become increasingly important for regulated industries.

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

Ameet Talwalkar, Carnegie Mellon ML professor and Chief Scientist at Datadog, joins Ben Lorica to trace time series foundation models from skepticism to Datadog’s Toto V1 and V2. 

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

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.

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.

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.

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.

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.

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.