筛选结果
99 篇排序
1:09:44EN10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledger主持 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.
3:15:53EN → 简体中文目标是机器人和平,而非赢得 AI 竞赛主持 Nathan Labenz在中国待了两周后,Nathan Labenz 主张美国应该用芯片换机器人,维持共享的 AI 范式,追求彼此富足,而不是再造一把达摩克利斯之剑。
5:15:51EN → 简体中文DHH 没有亲手写一行 Omarchy Quattro 的代码嘉宾 DHH · 主持 Lex Fridman与莱克斯·弗里德曼一次充满怀疑的对话过去十三个月后,Rails 的创造者讲述了 Opus 4.5、一群编码智能体(Agent)和一个一分钟的 Linux 安装器,如何结束了他一凿一凿手写 Ruby 的时代。
50:57ENA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuber主持 Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.
1:06:36ENBills Doubled Overnight. Next, the APIs Might Vanish.主持 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.
4:18:22EN → 简体中文每个周期都重要:解码几乎全网视频的志愿者们嘉宾 FFmpeg · 主持 Lex FridmanLex Fridman 与 Jean-Baptiste Kempf、Kieran Kunhya 谈 FFmpeg、VLC、手写汇编,以及 YouTube、Netflix 和火星车背后那群没有报酬的人。
1:57:29EN → 简体中文前沿视觉模型得分 12.5%:Joseph Nelson 谈计算机视觉的真实水位线主持 Nathan LabenzRoboflow 的首席执行官向 Nathan Labenz 解释,视觉为何仍落后于语言,如何把 SAM 3 蒸馏成温布尔登可用的边缘模型,以及美国为何几乎从未在开源视觉上领先。
1:34:29ENThree IMO Golds Missed the Same Problem. Harmonic Wants Math to Compile主持 Nathan LabenzVlad Tenev and Tudor Achim built Aristotle to emit Lean proofs a kernel can check—and they argue that is how mathematical superintelligence stays trustworthy.
3:15:52EN → 简体中文他的机器人处理不了的一条语音,以及那个自己补全了功能的智能体嘉宾 OpenClaw · 主持 Lex FridmanPeter Steinberger 向 Lex Fridman 讲述:一个一小时做出来的 WhatsApp 玩具,如何成了 GitHub 上增长最快的项目,以及为了让它保持开放,他付出了什么。
1:01:38EN13-Hour Coffee and 2x Throughput: Physical Intelligence Crosses the Deployment LineKarol Hausman and Tobi Springenberg tell Sequoia’s Training Data how a general robot brain, plus real-world RL, turned coffee, laundry, and chocolate boxes into jobs that actually run.
1:25:54ENHours after training ends, Z.ai puts the weights on the internet主持 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.
59:43ENGoose is writing its own pull requests: how Block is trying to save a quarter of the weekCTO Dhanji Prasanna tells Sequoia how an open-source agent, a functional reorg, and a weekly hours-saved metric are turning Block into an AI-first company.
2:20:35ENChatGPT Is a Thousand Days Old. Emad Mostaque Says We Have About a Thousand Left.主持 Nathan LabenzThe Stability AI founder’s new economics argues that when intelligence is abundant, scarcity-based money and GDP stop making sense.
43:09ENA $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.
40:54ENSeventeen Years of Flat Power, and a Plan to Bring the Factories Home主持 Sarah Guo, Elad GilJacob Helberg, the under secretary of state designate for economic growth, energy, and the environment, argues that nuclear power and AI productivity—not cheap labor—are how America reshore its supply chain.
35:45ENSix Years of Revenue, Then Four Times That in Eight Monthsn8n CEO Jan Oberhauser tells Sequoia how two bets — becoming an AI-agent builder, then deleting the leads metric — turned a workflow tool into a default orchestration layer.
47:18ENThe Analyst Tracking 200 GPU Clouds Breaks Nvidia Into a Three-Headed Dragon主持 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.
1:45:00ENAmerica Holds 45% of the World's Data Centers. Everyone Else Must Build, Buy, or Ally主持 Nathan LabenzAnjney Midha of a16z maps what “sovereign AI” actually means for companies and for countries that will never own the talent, data, and compute frontier.
36:48ENThe Weekend DeepSeek Dropped, the White House Called主持 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.
54:53ENA Free Voting Board Burned $2 Million. Then It Raised $100 Million.主持 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.
58:11ENPatrick Hsu Wants an App Store for Biology, Not Just Better DrugsThe Arc Institute co-founder argues that Evo 2, trained on genomes rather than proteins, should underpin tools for every step of the scientific method.
1:01:53ENOpen-source models are 5% of enterprise use — and GPT wrappers won主持 Jacob EffronLatent Space's Swyx and Alessio join Redpoint to map what actually has product-market fit in AI, and why the application layer is the fight that matters.
35:14ENRobots Have No Wikipedia. Chelsea Finn Is Starting With Three Buildings.主持 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.
45:06ENMike Schroepfer: AI’s Bottleneck Is Electricity, and One Tanker of Fusion Fuel Could Power the U.S. for a Year主持 Jacob EffronMeta’s former CTO tells Redpoint why hyperscaler demand is the climate story, why Llama was an access play, and why tomorrow’s CTO still lives or dies on a priority queue.
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