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1:04:26ENAt 100,000 Accelerators, Something Fails Every HourGoogle AI infrastructure chief Amin Vahdat tells Sequoia's Sonya Huang why FLOPS is a vanity metric, why the TPU line split in two, and why he would rather wait on a utility than build his own gigawatt.
45:33ENCursor Ships 1TB of Composer Weights Across Oceans in Under a MinuteFederico Cassano and Fireworks' Dima walk through the globally split RL stack that trained Composer 2 on a sparse trillion-parameter MoE.
41:32ENMoore's Law Is Slowing. Nvidia's CTO Still Wants 10× a YearMichael Kagan on why Nvidia's $7 billion Mellanox deal, not just more transistors, is how you turn a data center into one computer.
1:56:38ENo3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligencePresenta: Nathan LabenzOn Consistently Candid, the Cognitive Revolution host argues that math and coding will be superhuman by 2026, and that a reasoning core plus specialist “intuitive physics” may already be enough.
2:16:17ENA 10B Model Trained Across Three Continents — and an H200 for $1.49 an HourPresenta: Nathan LabenzPrime Intellect's founders lay out a four-step plan to turn spare global GPUs into collectively owned intelligence, and argue that reinforcement learning just made their job easier.
46:35ENThey trained a real-time video model in 20 hours and skipped the game engineDecart CEO Dean Leitersdorf tells Sequoia how Oasis runs live on H100s, why ChatGPT is a fallen wall rather than a pain point, and why the next trillion-dollar company may be a generated experience.
42:42ENEthereum Once Held Two Thousand GPT-3 Clusters of GPUsPresenta: Sarah Guo, Elad GilFoundry CEO Jared Quincy Davis on idle H100s, why today's AI cloud is still colocation, and how compound systems move work off giant interconnected clusters.
1:01:26ENAlexNet Used Two GPUs. GPT-4 Took Twenty Thousand. The Shortage Will Be Back.Presenta: Nathan LabenzRun:ai CTO Ronen Dar on filling idle accelerators, why H100s can be cheaper per experiment, and why Llama 2 undercuts compute governance.
53:37EN30 models, 42 scenarios, 7 metrics: Percy Liang's public checkup for language modelsPresenta: Sarah Guo, Elad GilA PubMed-only model once led the U.S. medical licensing exam — until a system roughly 200 times larger overtook it.






