筛选结果
94 篇排序
9:58EN → 简体中文
Matthew Berman· 2023年4月26日HuggingChat 的 2023 年初测：写作、推理与 Python 编程Matthew Berman · Forward FutureMatthew Berman 测试早期由 OpenAssistant 驱动的 HuggingChat，让它写作、算术、推理和编写贪吃蛇游戏，并将几个输出与 GPT-3.5 和 GPT-4 比较。这次小规模历史测试展示了潜力，也暴露出局限。
1:00:36EN → 简体中文
No Priors: AI, Machine Learning, Tech, & Startups· 2023年2月2日播客 · 2 人对谈连下 40 局《外交》（Diplomacy），没人发现对手是机器人：Noam Brown 的 10 万倍教训主持 Sarah Guo, Elad GilMeta 的 Noam Brown 讲述 Cicero 如何在一个小型网络社区里用英文谈判、连下 40 局，以及为什么决策时的思考，胜过了三年的规模化训练。
1:26:21EN → 简体中文
Lex Fridman· 2018年12月9日播客 · 2 人对谈机器绝不该把自己的目标奉为圭臬嘉宾 Stuart Russell · 主持 Lex FridmanStuart Russell 与 Lex Fridman 谈元推理（metareasoning）、自动驾驶的可靠性，以及为什么对人类目标的不确定性是控制问题（control problem）的核心。
1:45:49EN
Cognitive Revolution "How AI Changes Everything"播客Trust at Scale: Elicit's Founders on Reasoning Languages, World Models and Automating the Company主持 Nathan LabenzAndreas Stuhlmüller and Jungwon Byun explain how Elicit keeps frontier models checkable for high-stakes science, and where they think AI reasoning is heading.
15:01ENLex Fridman播客 · 2 人对谈Deep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still Lacks嘉宾 Daniel Kahneman · 主持 Lex FridmanThe Nobel-winning psychologist tells Lex Fridman how his fast-and-slow thinking framework maps onto deep learning, and why driving among pedestrians may require understanding people.
10:16ENLex Fridman播客 · 2 人对谈Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Think嘉宾 Yann Lecun · 主持 Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
58:57ENCognitive Revolution "How AI Changes Everything"播客When the Model Learns to Look Around: Apollo Research on Testing o1 for Scheming主持 Nathan LabenzApollo Research founder Marius Hobbhahn explains how his team probed OpenAI's o1 for deception, what it found, and why the trajectory worries him more than the model itself.
57:25EN
Unsupervised Learning: With Jacob Effron播客From 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.
10:34ENLex Fridman播客 · 2 人对谈Why Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AI嘉宾 François Chollet · 主持 Lex FridmanFrançois Chollet explains why neural networks only interpolate between points they have seen, and why the best AI systems pair them with symbolic rules.
1:03:10ENCognitive Revolution "How AI Changes Everything"播客Pause Tokens, Analogical Prompts and Ring Attention: A Tour of the Transformer's Next Upgrades主持 Nathan LabenzNathan Labenz and Trey Kollmer walk through five recent papers on pausing, backspacing, prompting, streaming and long-context training, and sketch how they might combine into a more capable model.