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1:40:22ENTwenty-atom crystals taught an AI the physics of a heartbeatAnime : Nathan LabenzOrbital Materials' Jonathan Godwin and Tim Duignan tell Nathan Labenz how a neural network trained on tiny crystals simulated a potassium ion channel on a single 2017 GPU.
2:04:45ENo3 Hit Superhuman on ARC-AGI. It Still Lost at Tic-Tac-ToeAnime : Nathan LabenzNathan Labenz walks through OpenAI's o3 scores, deliberative alignment, and why 2024's biggest surprise was beating PhDs while failing to book a calendar invite.
30:29ENHow Researchers Think o1-Style Reasoning Models WorkMatthew Berman · Forward FutureMatthew Berman explains a research survey of policy initialization, rewards, search and reinforcement learning, and the open questions behind reasoning models.
1:27:13ZH李想:汽车将从交通工具进化为空间机器人Invité : 李想 · Anime : 张小珺理想汽车 CEO 李想谈公司为何从造车走向人工智能:基座模型是 AI 时代的操作系统,汽车是进入物理世界的重要载体。对他而言,技术路线最终要落实为更好的用户体验、能力与长期价值。
1:07:32ENo1 Is a New Generation — and the Day AGI Arrives Will Feel BoringAnime : Jacob EffronOpenAI’s former chief research officer Bob McGrew on why o1 is a 100x leap, why agents stall on reliability, and why AGI may land as office tedium rather than a single dramatic moment.
48:18ENNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of HeadroomAnime : Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.
1:49:41ENA Team of Fifteen Matched Meta’s Post-Training on Meta’s Own BaseAnime : Nathan LabenzNathan Lambert walks through Tulu 3: the three-stage recipe, the 1 percent versus 14 percent lesson, and why open post-training now lives or dies on data and evals.
5:15:00ENDario Amodei Has Seen This Scaling Movie Enough TimesInvité : Dario Amodei · Anime : Lex FridmanAnthropic’s CEO puts numbers on frontier training costs and AGI, then hands the mic to the people who shape Claude’s character and look inside its weights.
0:35ENAn IBM Visit: Granite Models, InstructLab and Quantum ComputingMatthew Berman · Forward FutureMatthew Berman previews a longer discussion of IBM’s small AI models, model customization and quantum research.
2:24:18ENMMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.Anime : Nathan LabenzZyphra’s training lead walks through Zamba 2’s hybrid architecture, the evals that actually matter, and the trade secrets small labs still have to rediscover.
41:42ENNeural Networks Are Still Waiting for Their ThermodynamicsOpenAI researcher Dan Roberts on why physicists keep migrating into AI, and why the field still lacks the equivalent of the ideal gas law.
1:19:00ENEiso Kant on Poolside, Compute and AI for Software DevelopmentInvité : Eiso Kant · Anime : Harry StebbingsPoolside’s CTO explains code-execution feedback, the cost of model development and his company’s ambitions in the AI race.
1:06:48ENo1 Is Slow and Hard to Use. Percy Liang Still Calls It a Turning PointAnime : Jacob EffronStanford’s Percy Liang splits OpenAI’s o1 into a disappointing product and the most important research signal in years.
45:22ENAlphaGo Thought 30 Seconds a Move. o1 Made “Think Longer” GeneralOpenAI researchers Noam Brown, Ilge Akkaya, and Hunter Lightman on teaching language models to reason, the generator-verifier gap, and a second scaling curve at inference time.
9:15ENLlama 3.2 Adds Vision and Smaller On-Device ModelsMatthew Berman · Forward FutureIn a Meta-partnered 2024 video, Matthew Berman reviews the model family, its tooling and a brief hosted 1B demonstration.
39:45ENHarmonic’s Bet: Teach AI Math Directly, and the Riemann Hypothesis Falls by 2029Robinhood’s Vlad Tenev and Harmonic co-founder Tudor Achim tell Sequoia why math is reasoning, why Lean is the verifier, and why they refuse to wait for mathematical skill to emerge from scale.
1:18:32ENA DNA Model That Can Tell Which Genes You Cannot TouchAnime : Nathan LabenzStanford's Brian Hie walks through hybrid architectures, a genome-scale language model trained only on DNA, and an antibody that binds 25 times tighter than nature.
0:54ENOpenAI’s o1 Preview: A First Look at Longer ReasoningMatthew Berman · Forward FutureMatthew Berman introduces the o1-preview and o1-mini models and tries a Python game prompt.
35:30ENReflection 70B: Its Creators Explain the Proposed Self-Correction MethodMatthew Berman, Matt Shumer, Sahil Chaudhary · Forward FutureA launch-day discussion with Matt Shumer and Sahil Chaudhary covers synthetic data, selective reflection and evaluation limits.
1:03:46ENZico Kolter on AI Safety, Scaling and the Limits of Open ModelsInvité : Zico Kolter · Anime : Harry StebbingsThe Carnegie Mellon researcher and OpenAI board member explains why prompt injection worries him, how he thinks about open weights, and why AI progress remains uncertain.
50:20ENArvind Narayanan on AI Scaling, Real-World Risks and the Limits of Model BenchmarksInvité : Arvind Narayanan · Anime : Harry StebbingsThe Princeton professor challenges simple claims about scaling, AGI timelines and AI adoption while discussing deepfakes, healthcare, education and security.
9:43ENMatthew Berman Tests Jamba 1.5 on Coding and Reasoning PromptsMatthew Berman · Forward FutureA 2024 hands-on test of AI21’s hybrid model finds slow output in one hosted session and mixed answers to a small set of prompts.
1:03:26ENAidan Gomez on Model Scaling, Data and Enterprise AIInvité : Aidan Gomez · Anime : Harry StebbingsThe Cohere CEO discusses the economics of foundation models, enterprise adoption, AI agents and the future he hopes the technology will enable.
1:33:07ZH广密复盘全球大模型这一年:Scaling Law、AGI 豪赌与中美格局Invité : 李广密 · Anime : 张小珺拾象创始人李广密从硅谷一线观察出发,回顾 OpenAI、Anthropic、Google 与中国模型公司的竞争。他认为,模型能力与成本共同决定新一轮应用爆发,而巨额投入押注的是智能能否持续扩展以及 AI 对经济和产业的长期重构。
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