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10 slides18:31EN
AI Engineer· Oct 25, 2026Janie Gu and Suyeol Yun: Why Frontier Models Fail as Buy-Side AnalystsJanie Gu, Suyeol Yun · Google DeepMindJanie Gu explains why benchmark scores can mislead, while Suyeol Yun presents MandateBench, which tests whether a model can turn a fund mandate into a defensible investment memo. The two talks show why real workflows, reproducible grading, and evidence-backed reasoning matter.AI in financeBenchmarksEvals+2
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Latent Space· Oct 22, 2026Podcast · 2 speakersAnekha Sokhal on Moshi, a Recommendation Engine for Commodity TradersGuest Anekha Sokhal · Host swyxThe Moshi founder tells swyx how she would rebuild a trader’s workflow: connect market data, private files and conflicting sources, then push the second-order effects people would otherwise miss. The hard part is not the dashboard. It is getting someone to actually use it.AI in financeRecommendation systemsData quality & curation+2
52:27EN
Sequoia Capital· Sep 1, 2026PodcastAfter Two Dozen Police Departments Said No, They Built an Anti-Network-Effect AI CompanyA Wisconsin county had 300 gigabytes sitting on a cold case—and Peregrine's founders still refuse to take the credit.Security & safetyForward-deployed engineeringCompany Building+3
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No Priors: AI, Machine Learning, Tech, & Startups· Aug 27, 2026Podcast · 2 speakersGoogle Paid $10 Million for a Bankrupt Airline’s Data. That’s the Moat.Host Sarah Guo, Elad GilEon co-founders Ofir Ehrlich and Gonen Stein argue that models and compute are rented commodities — the only asset enterprises can actually keep is their data.Enterprise & strategyInfrastructure & deploymentData quality & curation+3
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Sequoia Capital· Mar 10, 2026PodcastFour of the Top Five Defense Primes Still Run Hardware Tests on PowerPointNominal’s cofounders argue that hardware never got the last twenty years of software infrastructure, and that physical AI will stall until test data lives in one place.Infrastructure & deploymentData quality & curationObservability & reliability+3
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Cognitive Revolution "How AI Changes Everything"· Feb 1, 2026Podcast125 million cells took a decade. The next billion takes monthsHost Nathan LabenzMark Zuckerberg and Priscilla Chan on pairing a frontier biology lab with a frontier AI lab so models train on data that was designed for them.Models & trainingAI for scienceData quality & curation+3
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Unsupervised Learning: With Jacob Effron· Dec 18, 2025PodcastThe Real Bottleneck in AI Research Is Compute, Not IdeasHost Jacob EffronAfter NeurIPS, Ari Morcos and Rob Toews sit down with Jacob Effron to argue about plateauing models, SSI’s secrecy, OpenAI’s cash burn, and a set of spicy 2026 bets.Enterprise & strategyAI StrategyScaling Laws+3
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Unsupervised Learning: With Jacob Effron· Dec 15, 2025PodcastA Two-Second Vote Is Training Models to Be ClickbaitHost Jacob EffronSurge AI CEO Edwin Chen tells Redpoint why LMArena rewards length and emojis, how one lab's models got worse for a year, and why frontier labs are no longer on the same path.Evals & observabilityRL environments & simulatorsData quality & curation+3
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Cognitive Revolution "How AI Changes Everything"· Dec 6, 2025PodcastPolish Is 1% of Frontier Training Data, So Poland Built Its Own ModelHost Nathan LabenzMarek Kozlowski of Poland's National Information Processing Institute explains how PLLuM uses language adaptation, organic instructions, and on-prem small models to keep a mid-size country in control of its AI.Enterprise & strategyOpen-weight modelsData quality & curation+3
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No Priors: AI, Machine Learning, Tech, & Startups· Nov 19, 2025Podcast · 2 speakers500 Gloves, 10 Million Trajectories, and a $10,000 Home RobotHost Sarah Guo, Elad GilSunday Robotics co-founders Tony Zhao and Cheng Chi map the gap between a scalable imitation-learning recipe and a machine that actually does the dishes.RoboticsData quality & curationScaling Laws+3
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Sequoia Capital· Nov 18, 2025PodcastFour Months to Drive Tokyo: How Wayve Bet the Company on One End-to-End NetworkWayve CEO Alex Kendall tells Sequoia’s Training Data why AV 2.0 ditches HD maps and hand-written stacks for a foundation model that can adapt to a new car and a new country in weeks.Models & trainingAutonomous DrivingWorld models+3
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No Priors: AI, Machine Learning, Tech, & Startups· Nov 13, 2025Podcast · 2 speakersA New Drug Burns $2 Billion and 10 Years. Benchling's CEO Wants AI to Cut That to ThreeHost Sarah Guo, Elad GilMost medicines fail in years seven to ten, after hundreds of millions have already gone into the clinic—and Sajith Wickramasekara thinks sending things to space may already be easier.AgentsAI for scienceAI in healthcare+3
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Unsupervised Learning: With Jacob Effron· Oct 24, 2025PodcastKarpathy Called Today's Models Slop. His Decade Timeline Still Sounds BullishHost Jacob EffronDatology AI's Ari Morcos and Radical Ventures' Rob Toews walk through Karpathy's cold water, OpenAI's dealmaking, and who actually pays for the data-center boom.Enterprise & strategyAI StrategyCompany Building+3
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Cognitive Revolution "How AI Changes Everything"· Oct 2, 2025PodcastChatGPT's Co-Creator Left to Put Nature in the Reward LoopHost Nathan LabenzLiam Fedus and Ekin Dogus Cubuk on why language models still fail at physics, why literature data is too noisy to train on, and why Periodic Labs is aiming at a 200K superconductor.Models & trainingAI for scienceReinforcement Learning+3
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Cognitive Revolution "How AI Changes Everything"· Sep 25, 2025PodcastEvery payment is a frame in a movie. Stripe’s foundation model took card-testing detection from 59% to 97%Host Nathan LabenzEmily Sands, Stripe’s head of data and AI, explains how a domain-specific payments model, shared embeddings, and mixed rules turn a $1.4 trillion network into compounding advantage.Models & trainingAI in financeEmbeddings+3
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Cognitive Revolution "How AI Changes Everything"· Aug 30, 2025PodcastA hundred experiments a day, and the valley of death in materialsHost Nathan LabenzRadical AI’s co-founders tell Nathan Labenz how a closed loop of frontier models and a self-driving lab is meant to collapse a forty-year materials cycle into less than a decade.AgentsAI for scienceAutonomous Systems+3
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Unsupervised Learning: With Jacob Effron· Aug 13, 2025PodcastThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.Host Jacob EffronJoshua Meier on three waves of AI drug discovery, why Chai-2 behaves like Photoshop for molecules, and why a 1% hit rate was supposed to be enough to change the industry.Models & trainingAI for scienceComputational Biology+3
32:59EN
No Priors: AI, Machine Learning, Tech, & Startups· Jul 24, 2025Podcast · 2 speakersA Hundred People, a Billion in Revenue, and Zero Venture MoneyHost Sarah Guo, Elad GilSurge AI founder Edwin Chen on why quality human data is a poetry problem, not a bounding-box problem, and why leaderboards keep training models to write clickbait.Evals & observabilityData quality & curationHuman-in-the-loop validation+3
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Cognitive Revolution "How AI Changes Everything"· Jul 8, 2025PodcastEvery Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It GoesHost Nathan LabenzLabelbox CEO Manu Sharma on the $15 billion Scale deal, RL “gyms,” $250,000 trainers, and why post-training now eats the budget that used to belong to pre-training.Models & trainingPost-trainingData quality & curation+3
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Unsupervised Learning: With Jacob Effron· Jun 4, 2025PodcastMercor's CEO: Knowledge Work's Next Job Is Writing EvalsHost Jacob EffronBrendan Foody tells Redpoint how Mercor turned AI hiring and expert data into a $100 million round — and why he thinks a huge slice of white-collar work will become creating tests for models.Evals & observabilityEvalsData quality & curation+3
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No Priors: AI, Machine Learning, Tech, & Startups· Apr 17, 2025Podcast · 2 speakersDiscovery rates collapsed tenfold. KoBold still found a 5% copper depositHost Sarah Guo, Elad GilJosh Goldman explains why KoBold Metals treats mineral exploration as an information problem, pairing AI with century-old maps to hunt lithium and copper.Enterprise & strategyAI for scienceData quality & curation+3
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Cognitive Revolution "How AI Changes Everything"· Mar 23, 2025PodcastA Year to Grow a Brain Organoid, an Hour to Simulate ItHost Nathan LabenzStanford postdoc Siyu He tells Nathan Labenz how Squidiff and CORAL move single-cell and spatial experiments into the computer — and where the models still cannot go.Models & trainingAI for scienceComputational Biology+3
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No Priors: AI, Machine Learning, Tech, & Startups· Mar 20, 2025Podcast · 2 speakersRobots Have No Wikipedia. Chelsea Finn Is Starting With Three Buildings.Host Sarah Guo, Elad GilPhysical Intelligence’s cofounder tells No Priors why a generalist robot model has to be trained across embodiments, why open-sourcing hardware is a bet against the problem going unsolved, and why humanoids are a little overrated.Models & trainingRoboticsData quality & curation+3
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Sequoia Capital· Feb 25, 2025PodcastDon't draw the flowchart: OpenAI's Deep Research team on training agents end to endIsa Fulford and Josh Tobin explain why Deep Research was trained with reinforcement learning on hard browsing tasks instead of a human-written graph of model calls.AgentsAgent engineeringReinforcement Learning+3
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