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AI Engineer· 25 oct 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.
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Y Combinator· 24 oct 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.
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GOTO Conferences· 23 oct 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.
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SemiAnalysis· 23 oct 2026Pódcast · 3 vocesSemiAnalysis on ASML's Hybrid-Bonding Patents, HBM Economics and the Next Tool EcosystemInvitado: Sherry Zhang, Howie · Presenta: 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.
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a16z· 23 oct 2026Pódcast · 3 vocesAmazon CEO Andy Jassy on the $220 Billion AI BuildoutInvitado: Andy Jassy · Presenta: 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.
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Dwarkesh Patel· 22 oct 2026Pódcast · 9 vocesDwarkesh Patel: What will computer chips look like in 2045?Invitado: Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · Presenta: 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.
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Latent Space· 22 oct 2026Pódcast · 2 vocesWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, ModalInvitado: Erik Bernhardsson · Presenta: 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.
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The Pragmatic Engineer· 21 oct 2026Pódcast · 2 vocesWill Larson: The Revised Rules of Engineering ManagementInvitado: Will Larson · Presenta: 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.
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Cognitive Revolution "How AI Changes Everything"· 17 oct 2026PódcastClaude Changed the Password. The Steering Wheel Was Already OptionalPresenta: 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.
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3Blue1Brown· 16 oct 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.
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No Priors: AI, Machine Learning, Tech, & Startups· 15 oct 2026Pódcast · 2 vocesThe Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of CybersecurityPresenta: 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.
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Stanford AI Club· 15 oct 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.
2:17:48ENCognitive Revolution "How AI Changes Everything"· 14 oct 2026PódcastAgent IDs Are Empty, Rogue Agents Are Coming, and We Might Have to BargainPresenta: 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.
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Sequoia Capital· 13 oct 2026PódcastAlphaGo 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.
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AI Explained· 12 oct 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.
2:00:51ENCognitive Revolution "How AI Changes Everything"· 10 oct 2026PódcastResample Every Token and You Can Watch the Model DecidePresenta: Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.
1:09:44ENNo Priors: AI, Machine Learning, Tech, & Startups· 9 oct 2026Pódcast · 2 voces10,000 GB300s for Four Weeks: Reflection’s Open-Model LedgerPresenta: 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.
1:26:46ENCognitive Revolution "How AI Changes Everything"· 8 oct 2026PódcastThere Likely Is a Level of Intelligence We Shouldn't Go PastPresenta: 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.
1:10:12ENCognitive Revolution "How AI Changes Everything"· 7 oct 2026PódcastOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell AnywayPresenta: 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.
1:04:26ENSequoia Capital· 6 oct 2026PódcastAt 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.
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Unsupervised Learning: With Jacob Effron· 6 oct 2026PódcastPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabPresenta: 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.
1:30:54ENCognitive Revolution "How AI Changes Everything"· 3 oct 2026PódcastHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2Presenta: Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.
35:39ENNo Priors: AI, Machine Learning, Tech, & Startups· 2 oct 2026Pódcast · 2 vocesCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That RatioPresenta: 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.
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Google DeepMind· 1 oct 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.Cargar másMostrando 24 de 1650