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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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

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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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

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 web site.

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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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

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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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

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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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

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 many references - can be found on The Data Exchange web site.

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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Detailed show notes - with links to many references - can be found on The Data Exchange web site.