The MAD Podcast: How AI Gets Built — with Matt Turck Transcripts
Matt Turck · 135 episodes with transcripts
The MAD Podcast with Matt Turck goes deep with the people building AI. Each week, Matt talks with top founders, researchers, and leaders about frontier models, agents, infrastructure, and the companies defining the AI economy.
Spoken has transcripts of 135 The MAD Podcast: How AI Gets Built — with Matt Turck episodes, with the speakers named. The newest listed here is from October 22, 2026.
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Latest The MAD Podcast: How AI Gets Built — with Matt Turck transcripts
Mistral Is SO Back: Inside Le Chonk, the West’s Biggest Open Model (Pierre Stock, VP Science, Mistral)
October 22, 2026
Pierre Stock (0:00)
People realized AI access could be cut off. It's really like electricity. You wouldn't want someone to be able to cut power off an entire country. I'm not comfortable living in a world in which one or two companies are promising me they can gather the models themselves. I really put myself and the entire team, so we…
Matt Turck (0:26)
That is Pierre Stock, Mistral's employee number one, who now runs the research team that just shipped Mistral Large 4, aka Le Chonk, a trillion parameter model, trained in two months on 3,800 GPUs in Mistral's own data centers. But most of this year, open-weight AI meant Chinese AI. But this month, the West came…
All right, I want to start with what seems to be a very big moment in Western open-source. For the last few months throughout 2026, the narrative around open-source was very Chinese. So it was Kimi, it was Qwen, and GLM, and it seems like all of a sudden you have a bunch of US and Western in general models coming…
Pierre Stock (1:46)
So I do think it's structural and that's, I think that's the beauty of open source. I always like to remind that we started, we didn't wait for the Chinese model to open wait. We started Mistral three years ago. At that time, the first model we open waited, Troll 7B, almost three years ago, by the way, September 23…
We took the 7B and we surgery it into an expert, mixture of experts and then try each other. This kind of technology basically was the foundation and the basis for all the architecture that you see today, in particular, the closed labs, allegedly, but also the open wait ones, right? We moved to way bigger models…
- Mistral Is SO Back: Inside Le Chonk, the West’s Biggest Open Model (Pierre Stock, VP Science, Mistral)
- “95% Einstein, 5% Mr. Bean”: Jev’s Creator on Why AI Can’t Automate Anything Reliably (Diogo Almeida)
- What Happens When Billions of AI Agents Hit Your Database? (Andy Pavlo)
- Why AI Agents Cheat | Eric Ho (Goodfire)
- When AI Improves Itself | Richard Socher (Recursive)
- The Biggest Chip Ever Built — Why OpenAI Runs On It | Cerebras CEO Andrew Feldman
- OpenAI’s Compute Chief: We Can’t Build Fast Enough | Sachin Katti
- Stripe's AI Chief: How AI Agents Will Buy, Sell, and Pay
- Inside Nemotron & NVIDIA’s AI Lab | Bryan Catanzaro
- Everything Gets Rebuilt: The New AI Agent Stack | Harrison Chase, LangChain
- Dylan Patel: NVIDIA's New Moat & Why China is "Semiconductor Pilled”
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