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68개정렬
1:50:48EN
Y Combinator· 2026년 10월 24일Why 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.
2:00:51EN
Cognitive Revolution "How AI Changes Everything"· 2026년 10월 10일팟캐스트Resample Every Token and You Can Watch the Model Decide진행자 Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.
1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026년 10월 9일팟캐스트 · 2명10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledger진행자 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.
56:31EN
Unsupervised Learning: With Jacob Effron· 2026년 10월 6일팟캐스트Post-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.
2:06:11ENCognitive Revolution "How AI Changes Everything"· 2026년 8월 14일팟캐스트Lindy Runs on DeepSeek. Its CEO Still Wants Chinese Models Banned진행자 Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.
2:16:29ENCognitive Revolution "How AI Changes Everything"· 2026년 8월 2일팟캐스트From Two Papers a Month to Sixty: What Two Weeks in China Revealed About AI Safety진행자 Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.
51:31EN
Sequoia Capital· 2026년 7월 21일팟캐스트They Refunded Nearly $2 Million. Then Factory’s CEO Explained the Dark FactoryMatan Grinberg on being two years early, why a model-agnostic harness beats lab co-design, and why 90 percent of coding tokens will soon run with the lights off.
1:47:38ENCognitive Revolution "How AI Changes Everything"· 2026년 7월 4일팟캐스트19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chip진행자 Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.
1:06:36ENUnsupervised Learning: With Jacob Effron· 2026년 6월 12일팟캐스트Bills Doubled Overnight. Next, the APIs Might Vanish.진행자 Jacob EffronSix months after their last roundup, Ari Morcos and Rob Toews tell Jacob Efron why coding agents finally work, why near-frontier open weights may have peaked, and why a compute famine could pull the plug on public APIs.
42:57ENNo Priors: AI, Machine Learning, Tech, & Startups· 2026년 5월 1일팟캐스트 · 2명Inference 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.
54:26ENCognitive Revolution "How AI Changes Everything"· 2026년 2월 22일팟캐스트Ten Billion Active Parameters, and the Unsexy Work of Making Them Agent-Ready진행자 Nathan LabenzMiniMax researcher Olive Song explains how M2 was trained with expert developers as reward models, interleaved thinking, and a perturbation pipeline that treats every scaffold change as the real generalization test.
4:25:13EN
Lex Fridman· 2026년 1월 31일팟캐스트The 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.
1:54:30ENCognitive Revolution "How AI Changes Everything"· 2026년 1월 9일팟캐스트From One in Ten Cancer Cells to One in a Million진행자 Nathan LabenzNathan Labenz's solo AMA updates his son's lymphoma treatment, calls Claude Opus 4.5 software AGI, and ranks the live players of early 2026.
1:16:21ENNo Priors: AI, Machine Learning, Tech, & Startups· 2026년 1월 8일팟캐스트 · 2명Jensen Huang’s Year-End Case That Token Costs Can Fall a Billion-Fold Without Killing Jobs진행자 Sarah Guo, Elad GilOn No Priors, NVIDIA’s CEO uses radiology, open source, and a $2 trillion R&D budget to argue that 2025’s extremes missed the stack.
1:18:40ENCognitive Revolution "How AI Changes Everything"· 2026년 1월 1일팟캐스트When AI Becomes the Oil Well: Luke Drago on the Intelligence Curse진행자 Nathan LabenzThe Workshop Labs co-founder tells the FLI Podcast why a world of non-human production could recreate the resource curse — and how private data, open weights, and moonshot careers might still break it.
1:32:38ENCognitive Revolution "How AI Changes Everything"· 2025년 12월 6일팟캐스트Polish Is 1% of Frontier Training Data, So Poland Built Its Own Model진행자 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.
1:09:48ENUnsupervised Learning: With Jacob Effron· 2025년 12월 5일팟캐스트China's AI Labs Went From 15 to Six. The Compute Gap Is 15-to-1.진행자 Jacob EffronJordan Schneider tells Unsupervised Learning that Chinese models were a private-capital story, that Beijing still thinks in hardware, and that the West's real edge is chips it can serve — not a state master plan.
1:25:54ENCognitive Revolution "How AI Changes Everything"· 2025년 12월 3일팟캐스트Hours after training ends, Z.ai puts the weights on the internet진행자 Nathan LabenzZixuan Li of Z.ai tells ChinaTalk how a Chinese lab ships GLM, treats open weights as a ticket into Western ecosystems, and still sees itself as an upstart.
43:09ENSequoia Capital· 2025년 9월 9일팟캐스트A $100 Arm and a $300 Robot: Hugging Face Wants an App Store for Physical AIThomas Wolf tells Sequoia's Training Data why LeRobot, cheap hardware, and open datasets are Hugging Face's bet that software developers can become roboticists.
47:18ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025년 8월 14일팟캐스트 · 2명The Analyst Tracking 200 GPU Clouds Breaks Nvidia Into a Three-Headed Dragon진행자 Sarah Guo, Elad GilSemiAnalysis founder Dylan Patel on OpenAI’s open-weight model, a coming neocloud wipeout, and why a chip startup has to beat Nvidia on hardware, networking, and software at once.
36:48ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025년 7월 31일팟캐스트 · 2명The Weekend DeepSeek Dropped, the White House Called진행자 Sarah Guo, Elad GilSriram Krishnan walks No Priors through America’s 28-page AI Action Plan, a token-share definition of winning, and why the lead over China is too small to take for granted.
2:14:55ENCognitive Revolution "How AI Changes Everything"· 2025년 7월 26일팟캐스트From Character AI to a 1% Warning Shot: Gabriel Weil's Case for Liability as AI Governance진행자 Nathan LabenzA Touro law professor tells Nathan Labenz how negligence, strict liability, and punitive damages could make frontier labs treat public risk as a hit to their own balance sheet.
23:39ZH
跟李沐学AI· 2025년 7월 23일李沐：给文本大模型加入一千万小时语音，开源 Higgs Audio李沐 · Boson AI李沐介绍团队如何在文本大语言模型的训练里加入大量语音数据，做成能听能说的 AudioLLM，并把 Higgs Audio 开源。他讲了架构取舍、token 压缩、数据从哪来，以及怎么在 3090 上跑起来。
54:53ENUnsupervised Learning: With Jacob Effron· 2025년 6월 17일팟캐스트A Free Voting Board Burned $2 Million. Then It Raised $100 Million.진행자 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.더 보기68개 중 24개 표시