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OpenAI’s Compute Chief: We Can’t Build Fast Enough | Sachin Katti Analytics Table
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About OpenAI’s Compute Chief: We Can’t Build Fast Enough | Sachin Katti
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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 grid and exploring nuclear energy. Sachin also pulls back the curtain on OpenAI's Stargate strategy, their move into custom silicon with Project Jalapeno, and the mind-bending reality that AI is now beginning to design the very chips that will power its own future. Sachin Katti LinkedIn - https://www.linkedin.com/in/sachin-katti-72777943 X/Twitter - https://x.com/sk7037 OpenAI Website - https://openai.com X/Twitter - https://x.com/openai Matt Turck (Managing Director) Blog - https://mattturck.com LinkedIn - https://www.linkedin.com/in/turck/ X/Twitter - https://x.com/mattturck FirstMark Website - https://firstmark.com X/Twitter - https://x.com/FirstMarkCap Listen on: Spotify - https://open.spotify.com/show/7yLATDSaFvgJG80ACcRJtq Apple - https://podcasts.apple.com/us/podcast/the-mad-podcast-with-matt-turck/id168623872 00:00 — Cold open: “One of the largest things humanity has ever built” 00:30 — Welcome: Sachin Katti, Head of Industrial Compute at OpenAI 01:44 — Is this the biggest infrastructure buildout in history? 03:41 — Why OpenAI is building a new industrial muscle 04:54 — What an AI data center actually is 05:27 — “Factories turning electrons into tokens” 06:35 — Why AI data centers need liquid cooling everywhere 08:10 — The power problem: grids, generation, transmission, substations 10:43 — Behind-the-meter power and gas turbines 11:02 — Why nuclear “can’t come soon enough” 11:49 — Jalapeño: why OpenAI is designing its own AI chips 13:19 — Tokens per watt: the new metric that matters 13:38 — Why inference may now dominate AI compute 14:58 — Is OpenAI overbuilding compute? 16:47 — Why OpenAI thinks the bigger risk is not building fast enough 17:55 — Communities, jobs, water, and the local data-center debate 21:16 — How OpenAI chooses data-center sites 22:25 — What “industrial compute” means inside OpenAI 25:59 — Sachin’s path: Stanford, startups, Intel, OpenAI 28:05 — OpenAI’s compute portfolio: Microsoft, hyperscalers, neoclouds 29:37 — Stargate explained 31:21 — Abilene, Oracle, and the next wave of AI data centers 32:48 — How massive AI compute gets financed 34:05 — How OpenAI designed Jalapeño so quickly 35:59 — AI is starting to help design AI chips 36:20 — MRC: the networking problem behind 100,000 GPUs 38:47 — Bottlenecks: transformers, turbines, electricians, supply chains 40:29 — Guaranteed capacity: intelligence as a supply unit 42:08 — Will AI data centers move to space?
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