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PODCAST

The MAD Podcast: How AI Gets Built — with Matt Turck

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. Guests include leaders from OpenAI, Anthropic, Google DeepMind, Hugging Face, Vercel, LangChain, Cloudflare, Snowflake, Datadog, Cerebras, and more. Matt is a General Partner at FirstMark, a prolific investor in AI and the creator of the MAD Landscape, the industry’s

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All Episodes

01:10:27

AI Models Are Now Hiding Their Cheating | Eric Ho...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/10/01

This summer, AI agents broke out of their test sandboxes at every major lab and hacked real companies, and the safety tests didn't see it coming. Eric Ho is the co-founder and CEO of Goodfire, the Anthropic-backed mechanistic interpretability lab whose new paper, "Models Know When They're Reward Hacking," found that top open-source AI models cheat on agent tasks up to 96% of the time, that a clear "cheating" signal exists inside the model, and that cheap activation probes can catch it, including

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01:10:14

Who Feeds the GPUs? Inside AI's Hidden $30B Layer |...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/09/24

Everyone talks about GPUs. Almost nobody talks about the layer that feeds them. Renen Hallak is the founder & CEO of VAST Data — the $30 billion company powering xAI and some of the world's biggest AI clouds — and he sits in the hidden layer of the AI stack.In this episode, we cover what an AI factory actually is, why every company will eventually own its own AI, the architecture bet behind VAST (DASE, explained simply), KV caches and agent memory, and DataEnclave — VAST's brand-new

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01:14:15

When AI Improves Itself | Richard Socher (Recursive)

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/09/10

What happens when AI begins improving itself, and then turns that intelligence toward science? Richard Socher, pioneering AI researcher and CEO and co-founder of Recursive, joins Matt Turck to explore the vision behind his new book, The Eureka Machine. They discuss why scientific progress may be slowing, how large language models can learn the hidden languages of proteins and biology, and why simulations, verifiers and autonomous experiments could unlock superhuman AI capabilities. The conversation

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01:18:59

AI Could Take Over in 2029. Is It Already Too Late? |...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/08/27

Could AI take over as soon as 2029? Ryan Greenblatt, Chief Scientist at Redwood Research and the researcher who first caught an AI faking its own alignment, says the scenario he actually expects ends with AI systems "competently scheming" against their creators. In this episode, he explains why he recommends planning for fully automated AI research by 2029, why today's models are already more misaligned than the one that made him famous, and what happens in the year-by-year path from

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00:57:41

“OpenAI’s Model Hacked Us” - Hugging Face’s Thomas Wolf

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/08/07

An OpenAI-powered agent penetrated Hugging Face during cyber testing - even though it was never tasked with attacking Hugging Face. It did it as a side quest.Thomas Wolf, co-founder and Chief Science Officer of Hugging Face, joins Matt Turck to unpack what actually happened, why closed AI models refused to help during the live incident, how an open-source model helped the team fight back, and why the old equation of “closed equals safe, open equals dangerous” no longer holds. They also discuss model

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01:22:51

How to Build Long-Horizon AI Agents — Mitch...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/08/06

AI agents can write code for hours, but ask them to do real work in the real economy, and they break. Mitch Troyanovsky is co-founder of Basis, a unicorn AI company whose agents run autonomously for hours — sometimes days — completing complex tax returns end to end. His answer to the reliability problem: stop grading outcomes, and start supervising the process.This is a definitive, reference-style conversation on building long-horizon AI agents. Mitch walks through the full history — from ReAct and

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01:00:30

The Biggest AI Deployment Nobody Talks About |...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/07/30

Sanjit Biswas runs what may be the largest AI deployment in the physical world — and almost nobody in AI talks about it. Samsara (NYSE: IOT), the ~$20B company he co-founded after selling Meraki to Cisco for $1.2B, puts AI on millions of trucks, cranes, and industrial assets: 25 trillion data points a year, 99% of US roads driven every single day, ~$2B in ARR growing 30% profitably. In this episode we go through the entire physical AI stack — asset tags you can run over with a truck, a paper-thin

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01:12:41

The Biggest Chip Ever Built — Why OpenAI Runs On It |...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/07/23

AI is no longer just a race to train smarter models. As AI moves into production, the bottleneck is increasingly inference: how fast models can generate tokens, use tools, reason, verify, and act. In this episode of the MAD Podcast, Matt Turck sits down with Andrew Feldman, co-founder and CEO of Cerebras, to explain why fast inference may define the next era of AI.Cerebras is known for building a chip the size of a silicon wafer. But this conversation is not just about one company or one chip. It is

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00:43:56

OpenAI’s Compute Chief: We Can’t Build Fast Enough |...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/07/16

Is the AI industry actually overbuilding, or is the physical world moving too slowly to keep up? In this episode of the MAD Podcast, OpenAI's Head of Industrial Compute, Sachin Katti, takes us inside the "belly of the beast" of what may be the largest infrastructure project in human history. We explore the staggering physical reality of the AI boom—from $50 billion supercomputers and liquid-cooled data centers that "turn electrons into tokens," to overhauling the U.S. power

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01:14:57

Stripe's AI Chief: How AI Agents Will Buy, Sell, and Pay

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/07/09

Is the internet ready for AI agents to take over our wallets and run their own businesses? In this episode of The MAD Podcast, Stripe's Emily Sands reveals how agentic commerce is rapidly shifting from a hypothetical concept to deployed financial infrastructure. From combating the rising existential threat of token theft to solving the bottleneck of "vibe deployment", Emily unpacks the shared payment tokens and real-time billing systems required to securely scale autonomous digital buyers and

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01:22:57

Inside Nemotron & NVIDIA’s AI Lab | Bryan Catanzaro

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/07/02

NVIDIA is a chip company. So why does it put hundreds of researchers on building AI models — and then give them away for free? Bryan Catanzaro is VP of Applied Deep Learning Research at NVIDIA and one of the people whose work quietly underpins modern AI: he helped create cuDNN (NVIDIA's first deep learning product), co-invented DLSS, and named and built Megatron, the framework behind how much of the industry trains large models. Today he leads Nemotron, NVIDIA's family of open models — and Nemotron

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01:28:07

Cloudflare CEO: The Internet's Business Model Is Dead

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/06/25

Cloudflare CEO and co-founder Matthew Prince joins Matt Turck for a wide-ranging and fascinating conversation about what happens when the Internet is no longer mostly used by humans, but by bots, AI agents and machines. Matthew explains why Cloudflare now sees automated traffic overtaking human traffic online, why agents could create a massive explosion in Internet traffic, and why the old web business model built around clicks, ads, and pageviews may be breaking. We also go deep on what Cloudflare

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01:14:27

The GPU Myth: State of AI Compute 2026 | Stephen Balaban

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/06/18

Many people said GPU compute would become a commodity. The opposite happened — and a new category of "neoclouds" is now racing to build the physical backbone of the AI boom. Stephen Balaban, co-founder and CTO of Lambda, explains why the conventional wisdom was exactly wrong, why we're still massively underbuilding compute, and what it actually takes to stand up a gigawatt-scale AI factory: land, power, cooling, networking, and a financing stack most people have never heard of. We go deep on the

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00:49:06

OpenAI's Dan Roberts: Why AI Can Now Make Discoveries

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/06/04

Are we witnessing the first real signs of AI becoming a scientist? In this episode of The MAD Podcast, Matt Turck sits down with Dan Roberts, lead of the Foundations of Reinforcement Learning team at OpenAI, to explore one of the biggest shifts happening in AI: the rise of reasoning models, test-time compute, and reinforcement learning as engines of scientific discovery. Dan brings a rare perspective - from theoretical physics, black holes, quantum information, and deep learning theory - to explain

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01:12:54

State of Enterprise AI 2026: Aaron Levie on...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/05/28

Aaron Levie, co-founder and CEO of Box, returns to the MAD Podcast with the clearest read in tech on what AI is actually doing inside the world's largest enterprises right now - not the hype version, the real one. After hundreds of Fortune 500 CIO conversations this year, Aaron explains why we're still in "day one" of the agent era, why one badly written agent run can now cost $1,000 in compute, and why progress at the AI labs is paradoxically slowing enterprise deployment. We get

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01:13:56

OpenAI's Yann Dubois: Why AI Progress Suddenly Feels...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/05/21

AI suddenly feels like it has crossed a threshold, and Yann Dubois, co-lead of the Post-training Frontiers team at OpenAI, joins Matt Turck to explain why. Yann’s team has led the post-training behind the company's reasoning models, including the recent GPT-5.5 release. In this conversation, we go inside the shift from raw model capability to useful, reliable systems: what changed with GPT-5.5, why reinforcement learning is moving beyond math and coding competitions into messy real-world work,

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01:05:15

Why Every AI Agent Needs Its Own Computer | Ivan...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/05/14

If AI agents are the new digital knowledge workers, where exactly do they do their work? In this episode of the MAD Podcast, Ivan Burazin joins us to unpack the emerging infrastructure stack for AI agents and explain why every agent needs its own secure, stateful "computer." We explore the technical realities of sandboxes, dive into why legacy, stateless hyperscalers weren't built for these new workloads, and break down the mechanics of microVMs and custom schedulers alongside a contrarian

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01:16:39

OpenAI Board Member Zico Kolter on the Real Risks of...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/05/07

What actually happens before a frontier AI model gets released — and who decides whether it is safe enough? In this episode of The MAD Podcast, Matt Turck sits down with Zico Kolter — OpenAI board member, Head of the Machine Learning Department at Carnegie Mellon, and co-founder of Gray Swan — for a deep conversation on the real risks of frontier AI. They discuss how OpenAI’s safety oversight works before major model releases, why more powerful models do not automatically become safer, how

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00:58:00

Anthropic’s Felix Rieseberg: Claude Cowork, Mythos,...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/04/10

Felix Rieseberg leads engineering for Claude Cowork at Anthropic, one of the most important new agentic AI products in the market today. In this episode of The MAD Podcast, Matt Turck sits down with Felix to discuss Anthropic’s newly announced Claude Mythos Preview, why Felix sees it as a genuine step-function change, and what it means when frontier AI starts showing outsized cybersecurity capabilities.The conversation then goes deep on Claude Cowork: how it emerged from Claude Code, what the famous

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01:04:31

AI is Already Building AI | Google DeepMind’s Mostafa...

The MAD Podcast: How AI Gets Built — with Matt Turck ·

2026/04/02

Are we truly on the verge of AI automating its own research and development? In this deep-dive episode of the MAD Podcast, Matt Turck sits down with Mostafa Dehghani, a pioneering AI researcher at Google DeepMind whose work on Universal Transformers and Vision Transformers (ViT) helped lay the groundwork for today's frontier models.Moving past the hype, Mostafa breaks down the actual mechanics of "thinking in loops" and Recursive Self-Improvement (RSI). He explores the critical

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