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Training Data

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Training Data is a podcast with leading AI builders and researchers where we ask critical questions to deepen our understanding.

Episodes

How Glean CEO Arvind Jain Solved the Enterprise Search Problem – and What It Means for AI at Work

OpenAI Researcher Dan Roberts on What Physics Can Teach Us About AI

Google NotebookLM’s Raiza Martin and Jason Spielman on Creating Delightful AI Podcast Hosts and the Potential for Source-Grounded AI

Snowflake CEO Sridhar Ramaswamy on Using Data to Create Simple, Reliable AI for Businesses

Noam Brown, Ilge Akkaya & Hunter Lightman of OpenAI’s o1 Research Team on Teaching LLMs to Reason Better by Thinking Longer

Why Vlad Tenev and Tudor Achim of Harmonic Think AI Is About to Change Math—and Why It Matters

Jim Fan on Nvidia’s Embodied AI Lab and Jensen Huang’s Prediction that All Robots will be Autonomous

Founder Eric Steinberger on Magic’s Counterintuitive Approach to Pursuing AGI

Sierra Co-Founder Clay Bavor on Making Customer-Facing AI Agents Delightful

Phaidra’s Jim Gao on Building the Fourth Industrial Revolution with Reinforcement Learning

Fireworks Founder Lin Qiao on How Fast Inference and Small Models Will Benefit Businesses

GitHub CEO Thomas Dohmke on Building Copilot, and the the Future of Software Development

Meta’s Joe Spisak on Llama 3.1 405B and the Democratization of Frontier Models

Klarna CEO Sebastian Siemiatkowski on Getting AI to Do the Work of 700 Customer Service Reps

Reflection AI’s Misha Laskin on the AlphaGo Moment for LLMs

Microsoft CTO Kevin Scott on How Far Scaling Laws Will Extend

Zapier’s Mike Knoop launches ARC Prize to Jumpstart New Ideas for AGI

Factory’s Matan Grinberg and Eno Reyes Unleash the Droids on Software Development

LangChain’s Harrison Chase on Building the Orchestration Layer for AI Agents