筛选结果
15 篇排序
56:31ENPost-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab主持 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.
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.
1:13:33EN → 简体中文一万亿个 Token 之后,概念终于落地:Łukasz Kaiser 谈 Transformer 仍然缺什么主持 Jacob Effron《Attention Is All You Need》合著者在 Unsupervised Learning 节目中表示,Transformer 大概率会继续胜出,但它们学习的方式仍然与人不同。
59:41ENThe GPT moment for video hasn’t arrived, but AGI may already be here主持 Jacob EffronA day after Google I/O 2026, Gemini co-lead Oriol Vinyals argues that world models, file-system memory, and infinite-complexity RL environments will define the next era of frontier models.
1:21:56EN → 简体中文Yann LeCun 离开 Meta:大语言模型通向不了智能主持 Jacob Effron这位图灵奖得主对 Jacob Effron 讲述了他为何从 Meta 分拆出 AMI Labs,为何类 JEPA 的世界模型胜过像素生成器,以及他为何认为 Hinton 在 2023 年改变了看法。
58:46EN → 简体中文OpenAI 首席科学家给出两个时间点:9 月前做到研究实习生,2028 年前做到自动化研究员主持 Jacob EffronJakub Pachocki 在 Jacob Effron 的节目上解释,为什么这些时间表依然成立,为什么持续学习并不是弯路,以及为什么在产品中展示思维链,会让训练信号与监控相互对抗。
1:03:00ENA Model That Solves New Math Problems Every Week Still Isn't AGI主持 Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.
57:52ENThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.主持 Jacob EffronJoshua Meier on three waves of AI drug discovery, why Chai-2 behaves like Photoshop for molecules, and why a 1% hit rate was supposed to be enough to change the industry.
47:00ENAn Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a Decade主持 Jacob EffronOpenAI’s GPT-4.1 post-training lead Michelle Pokrass tells Unsupervised Learning how the team spent three months on evals before training, why agents fail on wiring more than intelligence, and when to reach for RFT.
1:10:23EN → 简体中文每美元一百万个 Token:为什么 Noam Shazeer 认为推理算力(inference compute)仍未被充分挖掘主持 Jacob EffronTransformer 共同发明人 Noam Shazeer 与 Gemini 研究员 Jack Rae 讲述测试时算力(test-time compute)、Ilya Sutskever 对通用人工智能(AGI)的批评,以及一个四岁孩子如今能给老师讲蜥蜴的故事。
1:07:32ENo1 Is a New Generation — and the Day AGI Arrives Will Feel Boring主持 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 Headroom主持 Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.
1:06:48ENo1 Is Slow and Hard to Use. Percy Liang Still Calls It a Turning Point主持 Jacob EffronStanford’s Percy Liang splits OpenAI’s o1 into a disappointing product and the most important research signal in years.
1:10:19ENThe Robot That Folded the Laundry: Physical Intelligence’s Three Frontiers主持 Jacob EffronKarol Hausman and Danny Driess explain how robot foundation models moved from coded primitives to web-scale pretraining, and why performance is now the hard gate.
57:25ENFrom RAG to Reasoning: Why the Future of AI Is a System, Not a Model主持 Jacob EffronDouwe Kiela explains what OpenAI's o1 reveals about test-time compute, why enterprise AI must be specialized, and where post-training and evaluations are heading.









