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.

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 be found on The Data Exchange web site.

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

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

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

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 site.

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

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