Lex Fridman Podcast
英文 · Lex Fridman
长访谈覆盖 AI、科研与更广泛的人文议题，按单集主题选择。
已核对订阅 · 2026/10/11
AI 与经济播客
听研究、产品、产业与经济的深入讨论。节目标签表示关注方向，跨领域节目并非每期都谈 AI。
节目目录 · 17 档
TWIML AI Podcast
英文 · Sam Charrington
机器学习研究与工程实践，关注大模型、Agent 和基础设施。
已核对订阅 · 2026/10/11
Latent Space
英文 · Swyx、Alessio Fanelli
AI 工程、开发工具与开源生态；仅提取订阅源中带音频的单集。
已核对订阅 · 2026/10/11
Practical AI
英文 · Daniel Whitenack、Chris Benson
AI 工程与应用落地，适合从实践视角理解技术。
已核对订阅 · 2026/10/11
Machine Learning Street Talk
英文 · Machine Learning Street Talk
AI 基础研究、认知科学与哲学长谈，部分单集不限于 AI。
已核对订阅 · 2026/10/11
The Cognitive Revolution
英文 · Nathan Labenz
AI 研究、产品与社会影响，偏深入访谈。
已核对订阅 · 2026/10/11
Dwarkesh Podcast
英文 · Dwarkesh Patel
研究准备充分的长访谈，涉及 AI、经济与历史；并非每期都谈 AI。
已核对订阅 · 2026/10/11
No Priors
英文 · Sarah Guo、Elad Gil / Conviction
AI 技术、创业与产业变化，带有明确创投视角。
已核对订阅 · 2026/10/11
硅谷101
中文 · 硅谷101
技术、产业与商业的中文深度访谈，适合连接 AI 与经济议题。
已核对订阅 · 2026/10/11
张小珺Jùn｜商业访谈录
中文 · 张小珺
创业、AI 与产业人物长访谈，适合深入了解一线经营视角。
已核对订阅 · 2026/10/11
Planet Money
英文 · NPR
用故事解释经济机制与商业现象，适合建立经济直觉。
已核对订阅 · 2026/10/11
The Indicator from Planet Money
英文 · NPR
篇幅较短，解释经济数据、工作和商业中的具体问题。
已核对订阅 · 2026/10/11
Macro Musings
英文 · David Beckworth / Mercatus Center
货币政策、央行与宏观经济的专业访谈。
已核对订阅 · 2026/10/11
Odd Lots
英文 · Bloomberg
市场机制、宏观与产业访谈，也有 AI、算力和能源相关内容。
已核对订阅 · 2026/10/11
Unhedged
英文 · Financial Times
金融市场、利率与全球经济的分析和讨论。
已核对订阅 · 2026/10/11
EconTalk
英文 · Russ Roberts
经济学思维与公共议题的长对话，范围也包含社会与哲学。
已核对订阅 · 2026/10/11
知行小酒馆
中文 · 有知有行
投资、经济与生活的中文讨论；AI 相关单集可作为交叉阅读。
已核对订阅 · 2026/10/11
16 个可收听单集单集标题与简介保留节目方原文
Machine Learning Street Talk · 英文
What Most People Get Wrong About Evolution | Akarsh Kumar
A lot of people in AI treat evolution as a dumb fallback, basically random search for when you can't take a gradient. Akarsh Kumar thinks that is wrong. Selection hangs on to partial solutions, so mutations only need to be useful about 1% of the time for the search to keep making progress.Akarsh is a PhD student at MIT working with Phillip Isola, works with Sakana AI, and is first author of the Fractured Entangled Representation paper with Kenne…
47:54 · 2026/10/10
Machine Learning Street Talk · 英文
How a Voice Agent Learns the Rhythm of Conversation — Shawn Wen
Tsung-Hsien (Shawn) Wen, CTO of PolyAI, tells Tim Scarfe why voice agents are harder than text agents. Voice adds time, and a good conversation depends on adapting to the person on the line, not just on reasoning to the best answer. Shawn describes an audio-native model (Dialog-RSN-1) that first predicts a turn-taking signal, then replies in text with citations, and writes the transcript last so enterprises can audit it.Along the way: training o…
1:10:09 · 2026/10/2
Machine Learning Street Talk · 英文
Who Checks a Proof No Human Can Read? — Leo de Moura
Leonardo de Moura created Lean and co-created Z3. ---This episode is sponsored by Parallel.Parallel, where agents find answers: web search, extraction and deep research APIs built for AI agents.Start free with the Parallel MCP server and $5 of credits every month: https://parallel.ai/mlst?utm_source=creator&utm_medium=podcast&utm_content=MLST---Tim Scarfe talks with Leo about how Lean escaped its original audience, why dependent types and Mathli…
1:14:19 · 2026/9/30
Machine Learning Street Talk · 英文
When AI Research Starts Moving Faster Than Human Research - Zhengyao Jiang
Weco let an AI coding agent rewrite the harness around another agent for eight days: its code, prompts and tools, while the underlying language model stayed fixed. Tim Scarfe asks Weco co-founder Zhengyao Jiang what the reported gains over two years of human engineering actually demonstrate.The discussion examines AIDE 85's generated code, held-out evaluation and the difficulty of separating useful discoveries from reward hacking. Jiang explains…
43:42 · 2026/9/27
Machine Learning Street Talk · 英文
How Deep Learning Finally Cracked Messy Tables - Frank Hutter
Frank Hutter, co-founder of Prior Labs, talks about TabPFN, a tabular foundation model that makes predictions in a single forward pass, and the research behind it. TabPFN is pre-trained on synthetic datasets drawn from a prior over structural causal models, rather than on real data. At prediction time it takes the whole training table as context and outputs an approximation of the Bayesian posterior predictive distribution, without per-dataset t…
1:53:12 · 2026/9/24
Machine Learning Street Talk · 英文
Why Scaling Prediction Cannot Create Intelligence - Alexander Mattick
Alexander Mattick is a researcher at Fraunhofer IIS and a PhD researcher at the University of Technology Nuremberg (UTN), and a regular on Yannic Kilcher's Discord. He first came on MLST in 2022, after helping research the Yann LeCun and Randall Balestriero episode on interpolation. SPONSOR: --- Cyber Fund built the Monastery to help founders ship products that were impossible a year ago. Applications for Batch 1 are now open. Apply now: https:/…
2:14:20 · 2026/9/21
Machine Learning Street Talk · 英文
How Physical AI Learns Across Language, Video and Action — Ming-Yu Liu
The car making a left turn at the start of this episode was never filmed. Cosmos 3 generated it. Ming-Yu Liu, who leads the Cosmos research at NVIDIA, explains how one model can describe a video, generate one, and produce robot actions. He walks Tim through the architecture. A vision language model reasons one token at a time; its weights then initialise a bidirectional diffusion generator for video, audio and action, and a shared temporal posit…
25:57 · 2026/9/16
Machine Learning Street Talk · 英文
Speech Recognition Is Not a Solved Problem — Pavan Kumar Reddy
Pavan Kumar Reddy leads audio research at Mistral AI. He joins Tim Scarfe for a deep technical tour of Voxtral — and explains why the frontier of deployed voice is still a cascade of specialised models rather than one end-to-end system. IN PARTNERSHIP WITH MISTRAL AI: --- This episode was produced in partnership with Mistral AI. Mistral AI: https://mistral.ai/ --- The conversation opens on architecture. Voxtral Chat feeds a 3B Ministral text tru…
1:42:22 · 2026/9/15
Machine Learning Street Talk · 英文
How Replication Could Teach Machines What Good Science Looks Like — Edward Hughes
Can a machine learn the judgement that separates a plausible-looking result from a faithful experiment? Edward Hughes, Chief Scientist and co-founder of Inherent, joins Tim Scarfe to argue that creativity is not optimisation, and that the missing capability in AI is choosing which questions are worth asking. SPONSOR: --- Cyber Fund built the Monastery to help founders ship products that were impossible a year ago. Apply now: https://cyber.fund -…
2:01:53 · 2026/9/12
Machine Learning Street Talk · 英文
AI 2040: Plan A report - Daniel Kokotajlo & Thomas Larsen
Could slowing AI development make superintelligence safer? Daniel Kokotajlo and Thomas Larsen of the AI Futures Project join Tim Scarfe to examine AI 2040: Plan A, a proposal to buy time before AI exceeds human control. SPONSOR: --- Cyber Fund built the Monastery to help founders ship products that were impossible a year ago. Apply now: https://cyber.fund --- After revisiting AI 2027 and the limits of forecasting, they ask what happens when AI c…
1:29:46 · 2026/9/8
Machine Learning Street Talk · 英文
Designing How AI Grows — Tom McGrath
Tom McGrath is co-founder and Chief Scientist at Goodfire, and a former Google DeepMind researcher. He joins Tim Scarfe to ask what neural networks actually learn, whether their internal representations converge on structures in the world, and whether interpretability can extract new scientific knowledge rather than merely explain model outputs. Beginning with AlphaZero and learned modularity, the conversation moves into neural geometry: concept…
1:40:14 · 2026/9/3
Machine Learning Street Talk · 英文
Stealing Reasoning Traces from Proprietary LLM APIs — Ilia Shumailov & Alexander Panfilov
Tim Scarfe speaks with Ilia Shumailov and Alexander Panfilov about their paper, Stealing Reasoning Traces from Proprietary LLM APIs.The core bug sounds deceptively simple: providers return encrypted reasoning state so conversations can be resumed or forked. But those blobs can be replayed across users and sibling models. A smaller model can ask the provider to decrypt the trace, then repeat the hidden reasoning in plain text. The discussion cove…
49:00 · 2026/8/23
Machine Learning Street Talk · 英文
Every Exponential Ends — Silicon Valley Forgot — Adam Becker
Astrophysicist Adam Becker, author of "What Is Real?", joins Tim Scarfe to take apart the futures Silicon Valley keeps selling: the 2045 singularity, mind uploading, Mars colonies, and the AI apocalypse. His new book *More Everything Forever* argues these ideas are hugely influential, mostly evidence-free, and bankrolled by tech billionaires who need a story in which growth never ends.Becker does the physics the boosters skip. Kurzweil's "law of…
1:18:23 · 2026/8/21
Machine Learning Street Talk · 英文
AI Is Learning at the Wrong Level of Abstraction — Matthieu Wyart
This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at https://notion.com/mlstWhy can deep networks discover abstractions that shallow models miss? Statistical physicist Matthieu Wyart joins Tim Scarfe to argue that the answer lies in the hidden hierarchy of data. Language and images are built from parts within parts; depth lets a network recover those coarse-grained variables and escape the curse of dimension…
1:18:56 · 2026/8/11
Machine Learning Street Talk · 英文
How Researchers Test AI for Hidden Goals — Apollo Research
Can an AI do the right thing for the wrong reason? Tim Scarfe speaks with Apollo Research’s Alexander Meinke, Axel Højmark and Jérémy Scheurer about Measuring Reward-Seeking via Contrastive Belief Updates, their new research with OpenAI. The panel asks how models infer what graders reward, why good behaviour can come from the wrong reason, and whether that difference can be measured. The conversation moves through promise-breaking, grader awaren…
1:18:59 · 2026/8/1
Machine Learning Street Talk · 英文
Why a Nation Can't Outsource Its Frontier AI - Alistair Pullen (Cosine AI)
This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at https://notion.com/mlst Britain's most capable coding model can't be exported, and that ban is the whole reason Cosine set out to build one from scratch. Alistair Pullen, CEO and co-founder of Cosine, sits down with Tim Scarfe to explain how a frontier system he calls Fable, locked behind US export controls, became the founding case for a UK sovereign mode…
55:56 · 2026/7/14