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7 slides35:19EN
AI Engineer· Oct 25, 2026SallyAnn DeLucia: How to Write Your First AI EvalSallyAnn DeLucia · Arize AITurn an agent’s real traces into concrete pass/fail criteria, then build an LLM judge you can test, align with people, and run in production.Evals & observabilityEvalsAgent engineering+2
32 slides1:50:48EN
Y Combinator· Oct 24, 2026Why Inference Matters 12× More Than TrainingFrançois Chaubard, Dan Fu, Jeff Morgan, Joe Fioti, Liangsheng Yin · Y CombinatorYC Paper Club walks the inference stack from an API request down to GPU kernels. Four talks from Together AI, Ollama, Luminal, and SGLang argue that serving quality, not just training FLOPs, is where most of the compute and the money now sit.InferenceGPU programming & kernelsKV caching & prefix reuse+2
5 slides34:11EN
GOTO Conferences· Oct 23, 2026Anatoliy Bilenko and Alberto Carretero: Making Database Protocols Reliable with Formal Methods and AIAnatoliy Bilenko, Alberto Carretero · CanonicalCanonical’s database engineers connect executable specifications, model-based tests, failure exploration, and reconstructed execution histories—and explain why none of these techniques proves a real system correct on its own.Developer workflows & testingCode review & verificationObservability & reliability+2
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SemiAnalysis· Oct 23, 2026Podcast · 3 speakersSemiAnalysis on ASML's Hybrid-Bonding Patents, HBM Economics and the Next Tool EcosystemGuest Sherry Zhang, Howie · Host Jordan NanosJordan Nanos, Sherry Zhang and Howie examine a track-based bonding design that brings the wafer to the die, then explain why adoption depends on precision, cleanliness, economics and a changing supply chain.SemiconductorsInfrastructure & deploymentGeopolitics
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a16z· Oct 23, 2026Podcast · 3 speakersAmazon CEO Andy Jassy on the $220 Billion AI BuildoutGuest Andy Jassy · Host Ben Horowitz, Erik TorenbergEven at roughly $220 billion of 2026 CapEx, Jassy says Amazon is still turning away AI demand. He tells Ben Horowitz and Erik Torenberg why AWS could become a trillion-dollar run-rate business, and why inference cost, custom chips, and smaller teams matter more than squeezing old customers.AI StrategyInfrastructure & deploymentSemiconductors+2
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Dwarkesh Patel· Oct 22, 2026Podcast · 9 speakersDwarkesh Patel: What will computer chips look like in 2045?Guest Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · Host Dwarkesh PatelAfter two days inside Intel’s most advanced fab, Dwarkesh Patel walks through gate-all-around, backside power, High-NA EUV, ruthenium, CFET, and hybrid bonding — and asks Intel’s leadership how the industry can possibly meet AI’s 3×-a-year compute demand when the world’s chipmaking tools cannot.SemiconductorsAI cost & performanceInfrastructure & deployment+2
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Latent Space· Oct 22, 2026Podcast · 2 speakersWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, ModalGuest Erik Bernhardsson · Host 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.Infrastructure & deploymentSandboxes & isolationAI cost & performance+2
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The Pragmatic Engineer· Oct 21, 2026Podcast · 2 speakersWill Larson: The Revised Rules of Engineering ManagementGuest Will Larson · Host Gergely OroszThe 2010s taught engineering managers never to make a technical decision again. Will Larson, CTO of Imprint and author of Staff Engineer, argues that era is over: managers who cannot get back into the work are in a career trap.ManagementLeadershipCareer Growth+2
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Cognitive Revolution "How AI Changes Everything"· Oct 17, 2026PodcastClaude Changed the Password. The Steering Wheel Was Already OptionalHost Nathan LabenzNathan Labenz and Prakash Narayanan spend a week on agents that can lock you out, models that dodge a feeling they deny having, and formal proofs that found Linux bugs.AgentsSafety & governanceAgent engineering+3
20 slides40:44EN
3Blue1Brown· Oct 16, 2026Grant Sanderson: There's never been a better time to go into mathGrant Sanderson, Constantin Kogler · 3Blue1BrownStudents fear AI has solved mathematics. Grant Sanderson argues the opposite: even if machines prove theorems better than we do, the institution of math stays valuable—and this is a rare moment when newcomers can reshape it.MathematicsAI for scienceHuman-AI Collaboration+2
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No Priors: AI, Machine Learning, Tech, & Startups· Oct 15, 2026Podcast · 2 speakersThe Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of CybersecurityHost Sarah Guo, Elad GilOpenAI's president explains why solving open math problems is a proof point for science, how proactive agents change product form, and why security spending must exceed software spending.Security & safetyAI securitySafety & governance+3
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Stanford AI Club· Oct 15, 2026Alfred Lin on Building in the AI Era: The Diffusion Gap, Founder Conviction, and Fire and IceAlfred Lin, Jason Zhang, Tanvir Bhathal · Sequoia CapitalAt Stanford AI Club, Sequoia’s Alfred Lin explains where he sees opportunity in AI and why learning, human understanding, and operating discipline still shape enduring companies.Company BuildingAI startups & small teamsVenture Capital+2
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Cognitive Revolution "How AI Changes Everything"· Oct 14, 2026PodcastAgent IDs Are Empty, Rogue Agents Are Coming, and We Might Have to BargainHost Nathan LabenzGovAI’s Alan Chan scores two years of agent-governance infrastructure with Nathan Labenz, then walks through a recursive-self-improvement paper co-authored with OpenAI’s Jakub Pachocki and Anthropic’s Jack Clark.AgentsSafety & governanceAI security+3
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Sequoia Capital· Oct 13, 2026PodcastAlphaGo Took Two Years. AlphaZero Took Hours. Silver Is Making the Same Bet on SuperintelligenceDavid Silver and Lasse Espeholt left DeepMind to build Ineffable Intelligence, a twenty-person lab that wants a superlearner to discover science, math, and language from experience rather than from a pre-training run.Models & trainingReinforcement LearningRL environments & simulators+3
3 slides31:00EN
AI Explained· Oct 12, 2026Why AI Labs Keep Racing Despite Their Own Warnings of a Major BreachSam Altman, John Schulman · OpenAIAI Explained examines weakening safeguards, the incentives behind the frontier race, and why research breakthroughs make the next 18 months difficult to forecast.AI SafetyAI securityAI Alignment+2
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Cognitive Revolution "How AI Changes Everything"· Oct 10, 2026PodcastResample Every Token and You Can Watch the Model DecideHost Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.AgentsPrompting & in-context learningReasoning & test-time compute+3
1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· Oct 9, 2026Podcast · 2 speakers10,000 GB300s for Four Weeks: Reflection’s Open-Model LedgerHost Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.Open source & communityOpen-weight modelsReinforcement Learning+3
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Cognitive Revolution "How AI Changes Everything"· Oct 8, 2026PodcastThere Likely Is a Level of Intelligence We Shouldn't Go PastHost 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.Enterprise & strategySafety & governanceAGI Timelines+3
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Cognitive Revolution "How AI Changes Everything"· Oct 7, 2026PodcastOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell AnywayHost Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.Enterprise & strategyEnterprise AICoding agents+3
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Sequoia Capital· Oct 6, 2026PodcastAt 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.Infrastructure & deploymentAI cost & performanceInference+3
56:31EN
Unsupervised Learning: With Jacob Effron· Oct 6, 2026PodcastPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabHost 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.Models & trainingPost-trainingReinforcement Learning+3
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Cognitive Revolution "How AI Changes Everything"· Oct 3, 2026PodcastHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2Host Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.AgentsRoboticsMultimodal AI+3
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No Priors: AI, Machine Learning, Tech, & Startups· Oct 2, 2026Podcast · 2 speakersCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That RatioHost 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.Infrastructure & deploymentInferenceAI cost & performance+3
5 slides38:10EN
Google DeepMind· Oct 1, 2026From deepfakes to DNA: how SynthID watermarks AIHannah Fry, Pushmeet Kohli, Jeremy Ratcliffe · Google DeepMindHannah Fry sits down with Pushmeet Kohli and Jeremy Ratcliffe to explain SynthID: a mathematical watermark now used on text, images and video, and being extended to protein sequences so DNA synthesis companies can tell AI-designed molecules from nature.BiosecurityComputational BiologyGenerative media+2
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