Dwarkesh Podcast

Dwarkesh Patel
  • 0.0 (0)
  • 科技
  • 每星期更新

Deeply researched interviews www.dwarkesh.com

  1. Elon Musk - "In 36 months, the cheapest place to put AI will be space”

    2月5日

    Elon Musk - "In 36 months, the cheapest place to put AI will be space”

    In this episode, John and I got to do a real deep-dive with Elon. We discuss the economics of orbital data centers, the difficulties of scaling power on Earth, what it would take to manufacture humanoids at high-volume in America, xAI’s business and alignment plans, DOGE, and much more. Watch on YouTube; read the transcript. Sponsors * Mercury just started offering personal banking! I’m already banking with Mercury for business purposes, so getting to bank with them for my personal life makes everything so much simpler. Apply now at mercury.com/personal-banking * Jane Street sent me a new puzzle last week: they trained a neural net, shuffled all 96 layers, and asked me to put them back in order. I tried but… I didn’t quite nail it. If you’re curious, or if you think you can do better, you should take a stab at janestreet.com/dwarkesh * Labelbox can get you robotics and RL data at scale. Labelbox starts by helping you define your ideal data distribution, and then their massive Alignerr network collects frontier-grade data that you can use to train your models. Learn more at labelbox.com/dwarkesh Timestamps 00:00:00 - Orbital data centers 00:36:46 - Grok and alignment 00:59:56 - xAI’s business plan 01:17:21 - Optimus and humanoid manufacturing 01:30:22 - Does China win by default? 01:44:16 - Lessons from running SpaceX 02:20:08 - DOGE 02:38:28 - TeraFab Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    2 小時 50 分鐘
  2. Adam Marblestone – AI is missing something fundamental about the brain

    30/12/2025

    Adam Marblestone – AI is missing something fundamental about the brain

    Adam Marblestone is CEO of Convergent Research. He’s had a very interesting past life: he was a research scientist at Google Deepmind on their neuroscience team and has worked on everything from brain-computer interfaces to quantum computing to nanotech and even formal mathematics. In this episode, we discuss how the brain learns so much from so little, what the AI field can learn from neuroscience, and the answer to Ilya’s question: how does the genome encode abstract reward functions? Turns out, they’re all the same question. Watch on YouTube; read the transcript. Sponsors * Gemini 3 Pro recently helped me run an experiment to test multi-agent scaling: basically, if you have a fixed budget of compute, what is the optimal way to split it up across agents? Gemini was my colleague throughout the process — honestly, I couldn’t have investigated this question without it. Try Gemini 3 Pro today gemini.google.com * Labelbox helps you train agents to do economically-valuable, real-world tasks. Labelbox’s network of subject-matter experts ensures you get hyper-realistic RL environments, and their custom tooling lets you generate the highest-quality training data possible from those environments. Learn more at labelbox.com/dwarkesh To sponsor a future episode, visit dwarkesh.com/advertise. Timestamps (00:00:00) – The brain’s secret sauce is the reward functions, not the architecture (00:22:20) – Amortized inference and what the genome actually stores (00:42:42) – Model-based vs model-free RL in the brain (00:50:31) – Is biological hardware a limitation or an advantage? (01:03:59) – Why a map of the human brain is important (01:23:28) – What value will automating math have? (01:38:18) – Architecture of the brain Further reading Intro to Brain-Like-AGI Safety - Steven Byrnes’s theory of the learning vs steering subsystem; referenced throughout the episode. A Brief History of Intelligence - Great book by Max Bennett on connections between neuroscience and AI Adam’s blog, and Convergent Research’s blog on essential technologies. A Tutorial on Energy-Based Learning by Yann LeCun What Does It Mean to Understand a Neural Network? - Kording & Lillicrap E11 Bio and their brain connectomics approach Sam Gershman on what dopamine is doing in the brain Gwern’s proposal on training models on the brain’s hidden states Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    1 小時 50 分鐘
  3. An audio version of my blog post, Thoughts on AI progress (Dec 2025)

    23/12/2025

    An audio version of my blog post, Thoughts on AI progress (Dec 2025)

    Read the essay here. Timestamps 00:00:00 What are we scaling? 00:03:11 The value of human labor 00:05:04 Economic diffusion lag is cope00:06:34 Goal-post shifting is justified 00:08:23 RL scaling 00:09:18 Broadly deployed intelligence explosion Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    12 分鐘
  4. Sarah Paine – Why Russia Lost the Cold War

    19/12/2025

    Sarah Paine – Why Russia Lost the Cold War

    This is the final episode of the Sarah Paine lecture series, and it’s probably my favorite one. Sarah gives a “tour of the arguments” on what ultimately led to the Soviet Union’s collapse, diving into the role of the US, the Sino-Soviet border conflict, the oil bust, ethnic rebellions and even the Roman Catholic Church. As she points out, this is all particularly interesting as we find ourselves potentially at the beginning of another Cold War. As we wrap up this lecture series, I want to take a moment to thank Sarah for doing this with me. It has been such a pleasure. If you want more of her scholarship, I highly recommend checking out the books she’s written. You can find them here. Watch on YouTube; read the transcript. Sponsors * Labelbox can get you the training data you need, no matter the domain. Their Alignerr network includes the STEM PhDs and coding experts you’d expect, but it also has experienced cinematographers and talented voice actors to help train frontier video and audio models. Learn more at labelbox.com/dwarkesh. * Sardine doesn’t just assess customer risk for banking & retail. Their AI risk management platform is also extremely good at detecting fraudulent job applications, which I’ve found useful for my own hiring process. If you need help with hiring risk—or any other type of fraud prevention—go to sardine.ai/dwarkesh. * Gemini’s Nano Banana Pro helped us make many of the visuals in this episode. For example, we used it to turn dense tables into clear charts so that’d it be easier to quickly understand the trends that Sarah discusses. You can try Nano Banana Pro now in the Gemini app. Go to gemini.google.com. Timestamps (00:00:00) – Did Reagan single-handedly win the Cold War? (00:15:53) – Eastern Bloc uprisings & oil crisis (00:30:37) – Gorbachev’s mistakes (00:37:33) – German unification and NATO expansion (00:48:31) – The Gulf War and the Cold War endgame (00:56:10) – How central planning survived so long (01:14:46) – Sarah’s life in the USSR in 1988 Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    1 小時 55 分鐘
  5. Ilya Sutskever – We're moving from the age of scaling to the age of research

    25/11/2025

    Ilya Sutskever – We're moving from the age of scaling to the age of research

    Ilya & I discuss SSI’s strategy, the problems with pre-training, how to improve the generalization of AI models, and how to ensure AGI goes well. Watch on YouTube; read the transcript. Sponsors * Gemini 3 is the first model I’ve used that can find connections I haven’t anticipated. I recently wrote a blog post on RL’s information efficiency, and Gemini 3 helped me think it all through. It also generated the relevant charts and ran toy ML experiments for me with zero bugs. Try Gemini 3 today at gemini.google * Labelbox helped me create a tool to transcribe our episodes! I’ve struggled with transcription in the past because I don’t just want verbatim transcripts, I want transcripts reworded to read like essays. Labelbox helped me generate the exact data I needed for this. If you want to learn how Labelbox can help you (or if you want to try out the transcriber tool yourself), go to labelbox.com/dwarkesh * Sardine is an AI risk management platform that brings together thousands of device, behavior, and identity signals to help you assess a user’s risk of fraud & abuse. Sardine also offers a suite of agents to automate investigations so that as fraudsters use AI to scale their attacks, you can use AI to scale your defenses. Learn more at sardine.ai/dwarkesh To sponsor a future episode, visit dwarkesh.com/advertise. Timestamps (00:00:00) – Explaining model jaggedness (00:09:39) - Emotions and value functions (00:18:49) – What are we scaling? (00:25:13) – Why humans generalize better than models (00:35:45) – SSI’s plan to straight-shot superintelligence (00:46:47) – SSI’s model will learn from deployment (00:55:07) – How to think about powerful AGIs (01:18:13) – “We are squarely an age of research company” (01:20:23) – Self-play and multi-agent (01:32:42) – Research taste Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    1 小時 36 分鐘
  6. Satya Nadella — How Microsoft is preparing for AGI

    12/11/2025

    Satya Nadella — How Microsoft is preparing for AGI

    As part of this interview, Satya Nadella gave Dylan Patel (founder of SemiAnalysis) and me an exclusive first-look at their brand-new Fairwater 2 datacenter. Microsoft is building multiple Fairwaters, each of which has hundreds of thousands of GB200s & GB300s. Between all these interconnected buildings, they’ll have over 2 GW of total capacity. Just to give a frame of reference, even a single one of these Fairwater buildings is more powerful than any other AI datacenter that currently exists. Satya then answered a bunch of questions about how Microsoft is preparing for AGI across all layers of the stack. Watch on YouTube; read the transcript. Sponsors * Labelbox produces high-quality data at massive scale, powering any capability you want your model to have. Whether you’re building a voice agent, a coding assistant, or a robotics model, Labelbox gets you the exact data you need, fast. Reach out at labelbox.com/dwarkesh * CodeRabbit automatically reviews and summarizes PRs so you can understand changes and catch bugs in half the time. This is helpful whether you’re coding solo, collaborating with agents, or leading a full team. To learn how CodeRabbit integrates directly into your workflow, go to coderabbit.ai To sponsor a future episode, visit dwarkesh.com/advertise. Timestamps (00:00:00) - Fairwater 2 (00:03:20) - Business models for AGI (00:12:48) - Copilot (00:20:02) - Whose margins will expand most? (00:36:17) - MAI (00:47:47) - The hyperscale business (01:02:44) - In-house chip & OpenAI partnership (01:09:35) - The CAPEX explosion (01:15:07) - Will the world trust US companies to lead AI? Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    1 小時 28 分鐘
  7. Sarah Paine – How Russia sabotaged China's rise

    31/10/2025

    Sarah Paine – How Russia sabotaged China's rise

    In this lecture, military historian Sarah Paine explains how Russia—and specifically Stalin—completely derailed China’s rise, slowing them down for over a century. This lecture was particularly interesting to me because, in my opinion, the Chinese Civil War is 1 of the top 3 most important events of the 20th century. And to understand why it transpired as it did, you need to understand Stalin’s role in the whole thing. Watch on YouTube; read the transcript. Sponsors Mercury helps you run your business better. It’s the banking platform we use for the podcast — we love that we can see our cash balance, AR, and AP all in one place. Join us (and over 200,000 other entrepreneurs) at mercury.com Labelbox scrutinizes public benchmarks at the single data-row level to probe what’s really being evaluated. Using this knowledge, they can generate custom training data for hill climbing existing benchmarks, or design new benchmarks from scratch. Learn more at labelbox.com/dwarkesh To sponsor a future episode, visit dwarkesh.com/advertise. Timestamps (00:00:00) – How Russia took advantage of China’s weakness (00:22:58) – After Stalin, China’s rise (00:33:52) – Russian imperialism (00:45:23) – China’s and Russia’s existential problems (01:04:55) – Q&A: Sino-Soviet Split (01:22:44) – Stalin’s lessons from WW2 Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    1 小時 31 分鐘
  8. Andrej Karpathy — AGI is still a decade away

    17/10/2025

    Andrej Karpathy — AGI is still a decade away

    The Andrej Karpathy episode. During this interview, Andrej explains why reinforcement learning is terrible (but everything else is much worse), why AGI will just blend into the previous ~2.5 centuries of 2% GDP growth, why self driving took so long to crack, and what he sees as the future of education. It was a pleasure chatting with him. Watch on YouTube; read the transcript. Sponsors * Labelbox helps you get data that is more detailed, more accurate, and higher signal than you could get by default, no matter your domain or training paradigm. Reach out today at labelbox.com/dwarkesh * Mercury helps you run your business better. It’s the banking platform we use for the podcast — we love that we can see our accounts, cash flows, AR, and AP all in one place. Apply online in minutes at mercury.com * Google’s Veo 3.1 update is a notable improvement to an already great model. Veo 3.1’s generations are more coherent and the audio is even higher-quality. If you have a Google AI Pro or Ultra plan, you can try it in Gemini today by visiting https://gemini.google Timestamps (00:00:00) – AGI is still a decade away (00:29:45) – LLM cognitive deficits (00:40:05) – RL is terrible (00:49:38) – How do humans learn? (01:06:25) – AGI will blend into 2% GDP growth (01:17:36) – ASI (01:32:50) – Evolution of intelligence & culture (01:42:55) - Why self driving took so long (01:56:20) - Future of education Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

    2 小時 25 分鐘
查看全部 (116)

主持人與嘉賓

關於

Deeply researched interviews www.dwarkesh.com

資料

  • 創作者
    Dwarkesh Patel
  • 活躍年份
    2020年 - 2026年
  • 單集
    116
  • 分級
    兒童適宜
  • 版權
    © Dwarkesh Patel
  • 節目網站
    Dwarkesh Podcast

你可能也會喜歡