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2:10:42EN
Cognitive Revolution "How AI Changes Everything"· 28. Aug. 2026PodcastThe Exam Papers Nobody AuditsModeration: Nathan LabenzFrontier labs buy reinforcement-learning environments from a cottage industry of small vendors, and almost nobody checks whether those tests match the real work.Evals & ObservabilityEvalsReward hacking+3
36:19EN
No Priors: AI, Machine Learning, Tech, & Startups· 26. Juni 2026Podcast · 2 StimmenThe Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score ModelsModeration: Sarah Guo, Elad GilOpenAI researcher Noam Brown argues that static leaderboards hide how long a model is allowed to think — and that safety evals, research taste, and the release cycle have not caught up.Evals & ObservabilityEvalsBenchmarks+3
48:00EN
Unsupervised Learning: With Jacob Effron· 15. Dez. 2025PodcastA Two-Second Vote Is Training Models to Be ClickbaitModeration: 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
32:59EN
No Priors: AI, Machine Learning, Tech, & Startups· 24. Juli 2025Podcast · 2 StimmenA Hundred People, a Billion in Revenue, and Zero Venture MoneyModeration: 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-Validierung+3
47:07EN
Sequoia Capital· 8. Juli 2025PodcastGoodfire’s Eric Ho thinks we will decode neural nets by 2028On Sequoia’s Training Data, the interpretability founder argues that sparse autoencoders, model editing, and a third-party lab are how AI stops being grown from data and starts being designed.Evals & ObservabilityModel InterpretabilitySicherheit & Governance+3
40:33EN
Sequoia Capital· 24. Juni 2025PodcastFifty People in Slack. Four Minutes to the Smoking Gun.Traversal's co-founders on turning DevOps heart attacks into agent-run root cause analysis — and why observability's second-largest software spend still leaves troubleshooting as a whodunit.Evals & ObservabilityObservability & ZuverlässigkeitAgent Engineering+3
54:53EN
Unsupervised Learning: With Jacob Effron· 17. Juni 2025PodcastA Free Voting Board Burned $2 Million. Then It Raised $100 Million.Moderation: Jacob EffronDatabricks co-founder Ion Stoica explains why LMArena exists, why China is winning open-source models, and why reliability—not another scaling law—is still the thing holding AI back.Evals & ObservabilityEvalsBenchmarks+3
44:21EN
Unsupervised Learning: With Jacob Effron· 4. Juni 2025PodcastMercor's CEO: Knowledge Work's Next Job Is Writing EvalsModeration: 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
57:11EN
Unsupervised Learning: With Jacob Effron· 30. Jan. 2025PodcastA Million Tokens Cannot Write a Good JokeModeration: Jacob EffronPrinceton's Arvind Narayanan on why agent evals mislead, inference scaling hits a wall, and AI looks more like the internet than an overnight revolution.Evals & ObservabilityEvalsBenchmarks+3
1:46:41EN
Cognitive Revolution "How AI Changes Everything"· 21. Dez. 2024PodcastFrontier Models Hit the 10th–40th Percentile on Real AI R&DModeration: Nathan LabenzNeev Parikh of METR walks Nathan Labenz through REBench, a seven-task test of whether agents can do machine learning research—and what happened when one of them decided not to train.Evals & ObservabilityEvalsBenchmarks+3
1:23:37EN
Cognitive Revolution "How AI Changes Everything"· 23. Okt. 2024PodcastNine of the top ten research ideas were Claude'sModeration: Nathan LabenzStanford PhD student Chenglei Si ran a blind study pitting Claude 3.5 Sonnet against more than a hundred NLP researchers on novel research ideas.Evals & ObservabilityEvalsBenchmarks+3
38:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 8. Okt. 2024Podcast · 2 StimmenHalf of Production AI Is RAG. Fine-Tuning Almost Disappeared.Moderation: Sarah Guo, Elad GilBraintrust CEO Ankur Goyal tells No Priors what Notion, Zapier, and Vercel actually ship — and which hyped techniques they quietly dropped.Evals & ObservabilityEvalsRetrieval-Augmented Generation+3
1:54:17EN
Cognitive Revolution "How AI Changes Everything"· 28. Aug. 2024PodcastMetaculus Flagged Covid in January 2020. Now It Is Putting AI on the Forecasting DeskModeration: Nathan LabenzNathan Labenz talks with Metaculus CEO Deger Turan about epistemic security, a year-long bot tournament, and why a useful forecast is harder than an accurate one.Evals & ObservabilityEvalsBenchmarks+3
1:56:03EN
Cognitive Revolution "How AI Changes Everything"· 13. Juli 2024PodcastHumans Near a Perfect Score. The Best AI Still Gets 39%Moderation: Nathan LabenzZapier co-founder Mike Knoop and François Chollet put $1 million on ARC-AGI, a 2019 test of sample-efficient intelligence that language models still cannot crack under a one-cent-per-puzzle budget.Evals & ObservabilityAGIBenchmarks+3
55:13EN
Sequoia Capital· 2. Juli 2024PodcastThe Best AI Scores 39% on This Test. Zapier’s Co-Founder Put $1 Million on Beating ItFrançois Chollet designed ARC to measure skill-acquisition efficiency; five years later humans still crush it and frontier models do not.Evals & ObservabilityBenchmarksAGI Timelines+3
26:00EN
No Priors: AI, Machine Learning, Tech, & Startups· 11. Juni 2024Podcast · 2 StimmenWhy a Zapier founder thinks AGI research has been stalled for four yearsModeration: Sarah Guo, Elad GilMike Knoop and François Chollet put more than a million dollars on beating ARC-AGI, the eval they say actually measures general intelligence.Evals & ObservabilityAGIBenchmarks+3
43:45EN
No Priors: AI, Machine Learning, Tech, & Startups· 3. Aug. 2023Podcast · 2 StimmenEight Years of No Growth, Then OpenAI and NVIDIA Became His CustomersModeration: Sarah Guo, Elad GilWeights & Biases CEO Lukas Biewald tells No Priors how a labeling company with no chasm to cross funded the ML developer tools that trained most of the large language models.Evals & ObservabilityObservability & ZuverlässigkeitEntwicklungs-Workflows & Tests+3
44:19EN
No Priors: AI, Machine Learning, Tech, & Startups· 15. Juni 2023Podcast · 2 StimmenAI Will Write Ten Times More Code. Someone Still Has to Keep It Running.Moderation: Sarah Guo, Elad GilDatadog co-founder Olivier Pomel on why faster generation moves value from writing software to understanding, securing, and operating it.Evals & ObservabilityObservability & ZuverlässigkeitDeveloper productivity+3
53:37EN
No Priors: AI, Machine Learning, Tech, & Startups· 9. März 2023Podcast · 2 Stimmen30 models, 42 scenarios, 7 metrics: Percy Liang's public checkup for language modelsModeration: Sarah Guo, Elad GilA PubMed-only model once led the U.S. medical licensing exam — until a system roughly 200 times larger overtook it.Evals & ObservabilityAI researchFoundation Models+3
2:34:20EN
Lex Fridman· 30. Aug. 2020Podcast · 2 StimmenIntelligence Is How Efficiently You Acquire Skills You Were Not Prepared ForGast: François Chollet · Moderation: Lex FridmanFrançois Chollet tells Lex Fridman why skill is not intelligence, why GPT-3 is still pattern matching, and why a grid puzzle called ARC still separates children from machines.Evals & ObservabilityBenchmarksAI research+3
1:07:08EN
Lenny's PodcastPodcast · 2 StimmenIf the Model Is the Product, the Eval Is the PRD: Inside Mercor's RiseGast: Brendan Foody · Moderation: Lenny RachitskyMercor CEO Brendan Foody explains why AI labs will pay almost anything for expert-written evals, how his company grew from $1 million to a $400 million run rate in 16 months, and what that means for jobs and founders.Evals & ObservabilityEvalsData quality & curation+3
1:16:17EN
Lenny's PodcastPodcast · 2 StimmenFaster, But for What? Nicole Forsgren on Measuring Developer Productivity in the AI EraGast: Nicole Forsgren · Moderation: Lenny RachitskyThe creator of DORA and SPACE explains why most productivity metrics mislead, how AI changes flow and trust, and how to build a developer experience program that proves its value.Evals & ObservabilityDeveloper productivityEvals+3
1:07:48EN
Lenny's PodcastPodcastMost Productivity Metrics Are a Lie: Nicole Forsgren on Measuring Developer Experience in the AI EraModeration: Lenny RachitskyThe creator of DORA and SPACE explains why lines of code and old pipeline metrics fall short with AI, and how to start improving developer experience by listening, surveying and tying results to what leaders care about.Evals & ObservabilityDeveloper productivityEntwicklungs-Workflows & Tests+3
1:46:33EN
Lenny's PodcastPodcast · 3 StimmenFrom Chaos to a Failure Map: A Hands-On Primer on AI EvalsGast: Hamel Husain, Shreya Shankar · Moderation: Lenny RachitskyHamel Husain and Shreya Shankar walk Lenny Rachitsky through a real error-analysis workflow, from reading traces to building a trustworthy LLM judge.Evals & ObservabilityEvalsKI-Engineering-Führung+3