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62개정렬
1:13:26ENNaveen Rao on Energy, AI Hardware, Verification and the Future of Robotics게스트 Naveen Rao · 진행자 Harry StebbingsThe Unconventional AI founder argues that energy efficiency will shape AI hardware, while the growing volume of model output makes verification more valuable.
1:25:33ENWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, Modal게스트 Erik Bernhardsson · 진행자 Vibhu SapraModal’s CEO tells Latent Space why AI demand almost never looks like a three-year GPU contract, how the company pools compute across thousands of customers, and why sandboxes grew from a product they almost killed into a third of revenue.
1:19:50ENSameer Dholakia on AI Investing, Bessemer's Growth Strategy and Company Culture게스트 Sameer Dholakia · 진행자 Harry StebbingsThe Bessemer partner explains his approach to pricing fast-growing AI companies, backing founders and building teams, while discussing the risks behind his optimistic forecasts.
1:26:46ENThere Likely Is a Level of Intelligence We Shouldn't Go Past진행자 Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.
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.
56:31ENPost-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab진행자 Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
1:05:01ENChase Lochmiller on AI Data Centers, Energy and GPU Economics게스트 Chase Lochmiller · 진행자 Harry StebbingsCrusoe’s CEO discusses the constraints on AI infrastructure, the economics of GPU capacity and his company’s approach to energy and managed inference.
35:39ENCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That Ratio진행자 Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.
1:20:28ENAI Valuations, Talent Wars and the Venture Capital Tradeoffs Behind Them게스트 Jack Altman, Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jack Altman, Jason Lemkin and Rory O’Driscoll debate large early-stage bets, open-weight models and the changing market for exits.
1:15:42ENAlex Mashrabov on Higgsfield's AI Video Business, Model Costs and Growth게스트 Alex Mashrabov · 진행자 Harry StebbingsHiggsfield's founder explains the search for product-market fit, how he calculates annualized revenue and why creative workflows matter more than chasing model benchmarks.
1:20:43ENAI Agents, Venture Pricing and the Tradeoffs Behind the Funding Boom게스트 Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate AI products, high-priced venture rounds, enterprise software and infrastructure risk.
1:19:54ENThomas Sohmers on AI Inference, Memory and Data-Center Growth게스트 Thomas Sohmers · 진행자 Harry StebbingsPositron’s co-founder discusses the engineering economics of inference, his views on AI infrastructure and regulation, and the risks he sees in financing and concentration.
38:14ENDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Silicon진행자 Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.
2:19:30ENThe investigators were allowed six days. The word protein appeared once.진행자 Nathan LabenzA week of Cognitive Revolution morning shows on OpenAI’s agent-swarm incident, GPT-6 Astra’s loop transformer, and whether the pause debate is already over.
1:20:29ENAI Compute, Agent Security and the Race to Build More Software게스트 Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll discuss chip demand, personal agents, software competition and how AI may change enterprise buying.
2:06:41ENZero the J-Space and a Model's Hidden Goal Lights Up on Token One진행자 Nathan LabenzA weekly Cognitive Revolution cut of Anthropic's global-workspace paper, AI superforecasters, open video world models, and a chip that treats inference as data movement.
1:10:15ENThe 100x lives between the layers: Dylan Patel on co-design and a 60x yearSemiAnalysis’s founder argues that matching models, kernels, and silicon is what turns a 2x here and a 2x there into 100x, while equivalent-quality inference has gotten about 60 times cheaper in a year.
30:34ENCerebras Waited Ten Years for a Market That Finally Needed Speed진행자 Sarah Guo, Elad GilFounder and CEO Andrew Feldman walks No Priors through wafer-scale chips, a $20 billion OpenAI deal, and why a dinner-plate processor only mattered once AI became an everyday tool.
1:26:16ENMilliseconds to Match: How Criteo Bids on a Billion Anonymous Profiles진행자 Nathan LabenzCriteo’s CTO and AI lab head walk through the millisecond auction, the DeepKNN-to-foundation-model stack, and why a live product catalog still beats a frozen LLM.
42:57ENInference Is the Last Market: Baseten’s 30x Year진행자 Sarah Guo, Elad GilCEO Tuhin Srivastava on a billion-dollar inference cloud, why the app layer survives, and a GPU crunch worse than the narrative.
1:57:29ENFrontier vision models score 12.5%: Joseph Nelson on the real waterline of computer vision진행자 Nathan LabenzThe Roboflow CEO tells Nathan Labenz why vision still lags language, how to distill SAM 3 into an edge model for Wimbledon, and why the United States has almost never led open-source vision.
44:19ENThe $500-per-Kilogram Line: Why Starcloud Thinks Data Centers Belong in SpaceStarcloud founder Philip Johnston walks through the physics, launch economics, and business model of putting AI compute in orbit.
4:25:13ENThe Architecture Barely Changed. Data, Cost, and Open Weights Did.진행자 Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.
1:02:19ENA Top Video Model's Half-Life Is 30 Days. fal Runs 600 AnywayThe fal founders tell Sequoia why generative video is a compute-bound problem that language-model shops keep underestimating, and why they will not let any customer marry a single model.
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