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Training Data

von Sequoia Capital

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Join us as we train our neural nets on the theme of the century: AI. Sonya Huang, Pat Grady and more Sequoia Capital partners host conversations with leading AI builders and researchers to ask critical questions and develop a deeper understanding of the evolving technologies—and their implications for technology, business and society.

The content of this podcast does not constitute investment advice, an offer to provide investment advisory services, or an offer to sell or solicitation of an offer to buy an interest in any investment fund.

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  1. European Defense Sovereignty Starts in the Factory: Stark’s Uwe Horstmann and Johannes Schaback

    Two years after its founding, Stark has roughly 700 employees and strike drones in the field in Ukraine. CEO Uwe Horstmann and CTO Johannes Schaback argue that the real lesson of that war is not any single weapon: the innovation ecosystem b

  2. Inside the Robot Data Factory: Mecka's Josh Gao on Sensorizing Humans to Train Robots

    Robotics never got the internet's gift of free training data, so someone has to manufacture it. Josh Gao, founder and CEO of Mecka AI, runs one of the largest robot data factories, and he explains what that actually involves: custom basebal

  3. David Silver and Lasse Espeholt of Ineffable Intelligence: A Superlearner for the Age of Experience

    David Silver spent two years building AlphaGo on human data. When he removed human data altogether building AlphaGo Zero, the AI surpassed AlphaGo in under two days. He left DeepMind to run that same bet in pursuit of superintelligence. Dav

  4. Google's AI Infrastructure Chief, Amin Vahdat, on the Physics & Economics of Frontier AI

    At 100,000-accelerator scale, something fails multiple times an hour, which is why Google's Chief Technologist for AI Infrastructure Amin Vahdat thinks FLOPS is a vanity metric. The metric that matters is what he calls goodput: the useful w

  5. Box's Aaron Levie: On Reinventing Yourself in the AI Age and Enterprise Diffusion

    Starting a company is hard. Reinventing your company for AI as a public company with quarterly earnings results is even harder. Aaron Levie has pulled off the transition with Box and offers hard-won advice for founders. The cofounder and CE

  6. Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph

    Most public safety technology companies grow by collecting more data. Peregrine inverted the model: no sensors, no new data, a business built on connecting the data and information cities already own. Co-founders Nick Noone and Ben Rudolph

  7. Parallel’s Parag Agrawal: Building a New Web for AI Agents

    Parag Agrawal is making a bet that goes against two decades of web search: agents will query the web a thousand times more than humans ever have, and the infrastructure built around human clicks is wrong for them. The former Twitter CEO, no

  8. Rich Sutton and Khurram Javed: Why AI Models Stop Learning, and How to Start It Again

    Rich Sutton, who helped pioneer reinforcement learning and wrote the seminal AI essay The Bitter Lesson, has now cofounded Oak Lab with his former student Khurram Javed. Their goal: to build agents that continuously learn from their own exp

  9. Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem

    Most people treat biology as a bespoke, messy science. Josh Meier and Matt McPartlon, co-founders of Chai Discovery, treat it as an engineering problem. They make the case that drug design obeys the bitter lesson: scale data, models, and co

  10. Building the Automated AGI Lab: Core Automation's Jerry Tworek and Rohan Anil

    Jerry Tworek led reasoning at OpenAI, convinced that scaling reinforcement learning was the path to AGI. Rohan Anil co-led Gemini pre-training and built the Shampoo optimizer. Now they've teamed up at Core Automation on a contrarian premise

  11. Factory's Matan Grinberg: The Coming ‘Dark Factory’ Where Software Builds Itself

    Factory started building fully autonomous coding agents in April 2023, two years before enterprises were ready. Matan Grinberg now says this is indistinguishable from being wrong. The Factory co-founder and CEO explains how the company surv

  12. Anthropic's Katelyn Lesse & Angela Jiang: Building an Ecosystem, not a Walled Garden

    Katelyn Lesse and Angela Jiang lead the team building Anthropic's developer platform - the layer that both outside builders and Anthropic's own products run on top of. Angela frames the platform as a three-layer stack: knowledge, execution,

  13. Inside Zipline's Autonomous System: 140M Miles, Zero Incidents

    The largest commercial autonomous system on earth isn't a robotaxi fleet — it's Zipline, which has flown 140 million autonomous miles with zero safety incidents. Co-founder Keller Rinaudo Cliffton and Eric Watson, who leads systems engineer

  14. Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis

    Dylan Patel, founder of SemiAnalysis, argues the biggest gains in AI don't come from faster chips, they come from software-hardware co-design. Optimizing the model, the kernels, and the silicon together turns a 2x here and a 2x there into 1

  15. Memory and Continual Learning: Engram's Dan Biderman and Jessy Lin

    Dan Biderman and Jessy Lin, co-founders of Engram, are building a neolab around memory and continual learning, which they call two sides of the same coin. Their contrarian premise: instead of stuffing ever-larger prompts into the context wi

  16. Simulating Humans at Scale: Simile's Joon Sung Park

    The race to build superintelligence is producing models that keep getting better at objective problems, but not at behaving like actual people. Joon Sung Park, founder and CEO of Simile and creator of Stanford's "Smallville" generative agen

  17. Google DeepMind's Logan Kilpatrick: Why the Model Eats the Harness

    The entire startup ecosystem is racing to build agent harnesses. Logan Kilpatrick, who leads Google AI Studio and the Gemini API, argues that scramble has a roughly 12-month shelf life. Models will absorb the scaffolding and run it natively

  18. LIVE: Jensen Huang on Building the Dynamo of the Intelligence Age

    Jensen Huang, founder and CEO of NVIDIA, makes the case that computing is undergoing its biggest shift in 60 years: from retrieval, where data centers store files we look up, to generation, where every word, image, and video is produced in

  19. Knowing What Your Customers Want, All the Time: Listen Labs' Alfred Wahlforss

    Alfred Wahlforss, co-founder and CEO of Listen Labs, is building an AI agent that interviews your customers at a scale no focus group ever could—thousands of voice conversations at once, drawn from an audience of 30 million people. A year a

  20. How Cursor Trained Composer on Fireworks: Distributed Infrastructure for High-Performance RL

    Cursor's Federico Cassano and Fireworks' Dmytro Dzhulgakov explain how they collaborated to build Composer as a specialized foundation model. The core insight: models have finite capacity in their weights, and allocating all those bits to t

  21. Rebuilding IT From the Ground Up for the AI Age: Serval's Jake Stauch

    Jake Stauch, founder and CEO of Serval, is building a ServiceNow for the AI era. His most contrarian bet is that the product should look like boring old enterprise software, but with unlimited intelligence. Serval's architecture splits work

  22. Suno's Mikey Shulman: Everyone Can Make Music Now

    Most music platforms assume you're a listener. On Suno, 90% of daily users make something. Founder and CEO Mikey Shulman explains why that flips the model: the act of creating IS the entertainment, with closer parallels to gaming and Claude

  23. ElevenLabs' Mati Staniszewski: How Voice Becomes the Interface for Everything

    Mati Staniszewski, co-founder and CEO of ElevenLabs, joins Sequoia partner Andrew Reed at AI Ascent 2026 to talk about how a four-year-old company built a frontier audio AI business with just over 400 people and over $400M in revenue. He ex

  24. Anthropic's Boris Cherny: Coding's Printing Press Moment

    Boris Cherny, creator of Claude Code at Anthropic, joins Sequoia partner Lauren Reeder at AI Ascent 2026 to talk about where coding goes from here. He explains why he hasn't written a line of code in 2026, why he now ships dozens of PRs a d

  25. Waymo's Dmitri Dolgov: 20 Million Rides and the Road to Full Autonomy

    Dmitri Dolgov, co-CEO of Waymo, joins Sequoia partner Konstantine Buhler at AI Ascent 2026 to talk about the 20-year arc from the DARPA Grand Challenge to fully autonomous service in eleven cities and counting. He explains how Waymo persist

  26. OpenAI's Greg Brockman: Why Human Attention Is the New Bottleneck

    Greg Brockman, co-founder and president of OpenAI, joins Sequoia partner Alfred Lin at AI Ascent 2026 for a conversation that spans the full OpenAI stack. He explains why the company will never have enough compute, why he believes we're 80%

  27. Demis Hassabis on Building DeepMind, AlphaFold, and the Final Stretch to AGI

    Demis Hassabis, co-founder and CEO of Google DeepMind and 2024 Nobel laureate in chemistry for AlphaFold, joins Sequoia partner Konstantine Buhler at AI Ascent 2026 for a wide-ranging conversation about the path to AGI and what comes after.

  28. Andrej Karpathy: From Vibe Coding to Agentic Engineering

    Andrej Karpathy (co-founder of OpenAI, former head of AI at Tesla, and now founder of Eureka Labs) talks with Sequoia partner Stephanie Zhan at AI Ascent 2026 about what's changed in the year since he coined "vibe coding." He explains why h

  29. From SEO to Agent-Led Growth: Profound’s James Cadwallader

    James Cadwallader, co-founder and CEO of Profound, makes the case that we are living through the biggest platform shift in marketing history. The front door of the internet hasn't changed, but the visitor walking through it has. Where consu

  30. How Autonomous Labs Will Transform Scientific Research: Ginkgo Bioworks’ Jason Kelly

    Jason Kelly founded Ginkgo Bioworks in 2008 with a simple but radical idea: DNA is code, and cells are programmable. Sixteen years later, AI is finally making that vision real in ways that could reshape science itself. Jason describes a lan

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