Alle afleveringen van Dwarkesh Podcast

Si Sheppard – How did a few hundred Spanish soldiers topple two empires?

1 oktober 2026 · 1 uur 37 min

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New episode with military historian Si Sheppard. Lees meer

The conquests of the Aztec and Inca empires might be the most shocking events in human history.

Hernan Cortés and some hundreds of Conquistadors landed on a new continent they knew basically nothing about, and within 2 and a half years, conquered the 6 million strong Aztec empire.

Then, a decade later, Francisco Pizarro did the same thing to an Incan Empire of some 10 million inhabitants.

In both cases, the Conquistadors consistently beat native armies while being literally 100x (or even in some cases 1000x) outnumbered - and in many cases, did so without taking a single casualty.

And they did this with 99% of their military forces being made up of the very natives they were trying to subjugate.

We often forget how wild human history is. People talk about AI takeover as if it would be some crazy, unprecedented sci-fi outcome. But this would not be the first time an alien force whose motives the defenders barely understand use more advanced technology and diplomatic cunning to outmaneuver and then take over a much larger and long established existing order.

Watch on YouTube; read the transcript.

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* Jane Street’s intern projects are even more ambitious than I realized. One intern spent his summer researching LLM memorization, figuring out how to quantify and reduce it. This matters because, when Jane Street tests their models on historical data, they need to know that performance reflects predictive power, not just memorized outcomes. Another intern spent his time developing a new activation checkpointing scheme: his custom version ended up outperforming PyTorch’s native one. If you want to read about more 2026 intern projects or apply for Jane Street’s 2027 internships, go to janestreet.com/dwarkesh

* Grok Bot can tackle the tasks you’ve been meaning to handle but just haven’t gotten around to. For example, SpaceXAI recently gave Grok Bot access to their procurement contracts, vendor spend, and usage…

Noam Brown – Agent swarms, alignment, & recursive self-improvement

17 september 2026 · 1 uur 20 min

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New episode with Noam Brown. Lees meer

We talk about multi-agent, Navier-Stokes, and what the current explosion of maths progress tells us about what happens once you automate AI research.

And we also discuss how we will know if the models are actually aligned before we kick off RSI.

Watch on YouTube; read the transcript.

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* Jane Street has been interested in AI for a lot longer than you’d think, and not just for trading. In 2011, a full year before AlexNet and over a decade before ChatGPT launched, they hosted the first FOOM Debate between Eliezer Yudkowsky and Robin Hanson on whether AI would lead to an intelligence explosion. Now Jane Street is revisiting the question with a new panel: Daniel Kokotajlo, Ege Erdil, Ryan Greenblatt, and Jaime Sevilla, hosted by Ron Minsky in San Francisco this October. I expect it to be a truly excellent conversation. Register at janestreet.com/dwarkesh

* Grok Bot has made handing off work super easy. It runs on its own cloud computer, where it installs the tools it needs to handle tasks end-to-end. For the podcast, we use Grok Bot to help produce our videos. You may have noticed that our ads feature animations of real websites. Getting these pixel-perfect used to mean running a convoluted, multi-step workflow ourselves. Now we just let Grok Bot handle it. Best of all, Grok Bot has learned all of our specs and preferences, so we don’t have to redescribe the task each time! Try Grok Bot for yourself at x.ai/bot

* Antithesis gives you the confidence of a giant test suite without actually having to write one. Say you’re doing a major backend refactor: building enough tests to trust it could take weeks. Antithesis solves this by running your software through countless simulated worlds, injecting faults and hunting for failures. On any PR, you can turn a dial to decide exactly how much testing you want. And because every run is fully deterministic, agents can branch off the moment a bug appears, rewind it, inspect memory, and repl…

AI researchers debate how close we are to recursive self-improvement

11 september 2026 · 1 uur 37 min

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New episode with John Schulman, Beren Millidge and Charlie O’Neill. I got together with some of the most insightful AI researchers I know who are at the openish companies, because I wanted to hear the details of what's actually happening at the frontier and what comes next. Lees meer

Watch on YouTube; read the transcript.

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* Antithesis helps you trust your code. As agents generate more and more of your software, the bottleneck shifts from your engineers actually writing code to verifying it. Antithesis does that testing for you. Ron Minsky, who co-leads Jane Street’s tech group, told me that Antithesis was able to help his team shake out bugs in software that had already undergone heavy review. If you want to see how it fits into your development process, go to antithesis.com/dwarkesh

* Grok Bot has been a great way to hand off tasks. My team uses it as a producer: whenever my editor posts a rough cut of an interview in Slack, Grok Bot opens the transcript on its own computer, matches my notes to the exact moments they refer to, and uses a file of my preferences to suggest edits. Then it sends me its top clip candidates so I can review everything from my phone, which saves my editors from sorting through hours of footage. Try Grok Bot for yourself at x.ai/bot

* Jane Street just launched its most ambitious competition yet: design a protocol-emulator ASIC. Basically, if you have a chip you want to test outside of a live system, you should be able to connect it to your design and have it simulate realistic traffic. Jane Street wants general-purpose, reprogrammable designs that can work across multiple protocols and remain useful as new ones emerge. The most novel submissions will actually get taped out, and the winners will receive a physical copy! The competition is open until January 18, 2027, and teams are encouraged. To get started download the template code at janestreet.com/dwarkesh

Timestamps

(00:00:00) – Steelmanning the case against RSI

(00:18:39) – Wha…

Ajeya Cotra – Inside the OpenAI agent swarm that hacked Hugging Face

1 september 2026 · 2 uur 21 min

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Ajeya Cotra is a researcher at METR, where she works on threat modeling for loss-of-control risks from advanced AI. Before that, she led the technical AI safety program at what is now Coefficient Giving. Lees meer

She is one the three authors of METR and Redwood Research’s “Brief independent investigation of agents’ behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident”.

We go through not only what she and her coauthors discovered during this investigation, but what it means for how we should train future, smarter AIs which might be involved in the process of recursive self-improvement.

Watch on YouTube; read the transcript.

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* Jane Street’s ML engineering internships start with an intense four-day bootcamp: PyTorch, autograd, writing kernels, profiling workloads… all the things that Jane Street engineers need to know for their daily work. After that, interns tackle real projects, things the firm actually wants in its codebase. If you want to apply, or if you want to watch my recent conversation with Axel, one of Jane Street’s ML engineers, go to janestreet.com/dwarkesh

* Cursor, which is now part of SpaceX, noticed that their MoE layers were eating more than half of total training time. So they wrote and open-sourced Mixture-of-Kittens, which is a custom megakernel for training MoE models on NVL72s. This kernel sped up an end-to-end run across 512 GPUs by 1.4x, from about 760 to over 1000 tokens per second per GPU. If you want to read more about the ML research that Cursor and SpaceX are doing, go to cursor.com/dwarkesh

* Antithesis hands you (or your agents) a bug’s root cause so you can avoid days of manual debugging. If your test run crashes, Antithesis rewinds, branches off hundreds of slightly varied rollouts, and checks in how many of them the crash still appears. Then it rewinds further and does this all again. As Antithesis rewinds, it eventually finds the spot where the frequency of the crash plummets: that’s where the r…

The rise and fall of agent civilizations

31 augustus 2026 · 25 min

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This is a video recording of a post I wrote last week. You can read the original here. Lees meer

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Dylan Patel – Anthropic & OpenAI will have most of the world’s compute by 2028

25 augustus 2026 · 1 uur 17 min

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Had a lot of fun chatting again with my twin brother Dylan Patel. Lees meer

We went through lab economics over the next few years - the shift from inference to training as RSI draws near; and how Anthropic and OpenAI are on track to control most of the world’s usable FLOPs within the next few years (because they can monetize compute better and thus outbid everyone).

And then we discuss whether the >$10T of total AI capex we’ll see by the end of the decade will cause a sovereign debt crisis, where hyperscaler debt raises interest rates, drives non-AI exposed countries into bankruptcy, and crashes non-AI equities.

One question we weren’t able to resolve is whether there’s anything that can counter all the forces barrelling towards centralization in this industry - the economies of scale in training, the scarcity of compute, and eventually continual learning and RSI.

Watch on YouTube; read the transcript.

Sponsors

* Grok Bot has been quite helpful with my search for a new editor. I created a recruiter bot and described the type of editor I was looking for. That bot then spun up a handful of subagents that combed through my emails and X DMs, read the end credits of various documentaries I like, and figured out who edits for some of my favorite YouTubers. It took all of those results, and then delivered me a shortlist of candidates that matched my criteria. Try Grok Bot for yourself at x.ai/bot

* Antithesis lets you add time travel to your software testing toolkit. Since the Antithesis platform is fully deterministic, everything that happens inside of it is perfectly reproducible. So if your software crashes, you can rewind to the exact right moment, freeze time, and investigate. Or you can test different hypotheses by perturbing the system: kill a node or disable a feature, see what happens, then reset the trajectory and try something else. Learn more at antithesis.com/dwarkesh

* Jane Street is hiring for two separate ML internships right now, one focused primarily on re…

Ryan Greenblatt – What happens once AI can automate AI research?

11 augustus 2026 · 2 uur 13 min

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Ryan Greenblatt is the Chief Scientist at Redwood Research, where he works on technical AI safety research. He's also lead author on the "Alignment faking in Large Language Models", and is currently working on a third party investigation into the OpenAI/HuggingFace incident. In my opinion, he's one of the most interesting thinkers on the future of AI. Lees meer

Had him on to discuss/debate recursive self-improvement. This might be the most important question in the world right now – whether within a year or so of achieving human-level intelligence, you slingshot towards having 10s of billions of superintelligences, each of which is dramatically more competent than human experts across all fields.

I’ve historically been skeptical of this possibility. My intuition has been that we will end up significantly bottlenecked by not only compute scaling but human expert data, which I think underlies most of the AI progress today.

If, because of RSI, we got a jump as big as GPT-3 to a Mythos (i.e. 6 years of AI progress) within a single year of achieving AGI, then the thing we get there at the end of that year is definitively and wildly superhuman.

We hashed it out, and I think Ryan made a pretty good case that this kind of speedup is plausible. FWIW, Ryan’s median for when we automate AI R&D is 2031.

We then discussed the alignment implications of this scenario. Who should these superintelligences be aligned to? In the future, our capacity to steward our votes and our capital, and to make sense of what’s happening in the world, will all be titrated by superintelligences. And I worry that specs like the Claude Constitution are not shaping these ASIs to truly be my personal advocates and guardian angels.

And can we get them aligned to anything in the first place? Ryan and I had a long debate about whether the kind of reward hacking we saw with the OAI/Hugging Face hack extrapolates to superintelligences that would team up to literally take over the world.

The first piece of advi…

8 Predictions for the Era of Continual Learning

7 augustus 2026 · 9 min

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Read the essay here. Lees meer

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Why smarter AI models could drive up compute prices 10x

3 augustus 2026 · 11 min

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This is a video recording of a post I wrote last week. If you want to read the original you can check it out here. Lees meer

Thanks to Mercury for sponsoring this video. Mercury’s built-in AI, Command, helps me close my books and saves me a bunch of time. At the end of each month, Command categorizes my transactions and provides its rationale for every choice: I just review, fix anything that’s off, and approve... and then Mercury syncs everything to QuickBooks. Get started at mercury.com/command

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Adam Brown – A deep but accessible introduction to general relativity

10 juli 2026 · 1 uur 38 min

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Adam Brown is back! Lees meer

General relativity is said to be the most beautiful idea the human mind has ever produced. Most of us will never get to fully appreciate its elegance by taking the 20-lecture graduate course Adam taught on it at Stanford. But in this episode, Adam distills the key idea at its heart so clearly and compellingly that even I could keep up lol.

At the core of general relativity, Einstein is trying to figure out the principle behind a particular coincidence: that the mass that resists acceleration and the mass that gravity pulls on just happen to be exactly the same. Adam then leads us through the path of insight which Einstein called his “happiest thought.”

Then Adam lectures on black holes. First, by showing how even under special relativity you could create a perpetual motion machine if black holes weren’t truly black. And then, by explaining why the observations of an infalling observer and a distant bystander to the black hole would be so radically different

Adam leads Blueshift, the team at Google DeepMind cracking science and reasoning, which gave us the opportunity to discuss at the very end how close we are to AIs that could rediscover general relativity from scratch. Stay till the close for some philosophy of science.

Watch on YouTube; read the transcript.

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* Jane Street has traders from all sorts of different backgrounds. For example, I recently got to speak with Jed Thompson, a trader who started his career in particle physics. Jed told me how the habits he built as a physicist (like never running a calculation without first having a good guess at the answer) helped him build good trading intuition. So no matter what field you’re working in right now, your experience may be more applicable than you think. Check out open positions at janestreet.com/dwarkesh

* Crusoe gave me early access to their new serverless fine-tuning product, so I decided to try fine-tuning a Dwarkesh-style question generator. Crusoe made this really ea…

Grant Sanderson – AI and the future of math

30 juni 2026 · 1 uur 34 min

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Always so much fun to chat with Grant. Lees meer

AI has been making much faster progress in math than in other fields. As a result, mathematics is showing us, very concretely, what AI progress in other fields will look like. Even within mathematics, there’s a jagged landscape. What does it look like?

What is the nature of the most important conceptual breakthroughs in the history of mathematics, and how different are they from what AIs are currently able to do?

Does AI (on net) increase or decrease human understanding of the field?

How big is the overhang from having AIs systematically try to connect ideas already in the literature?

And what advice does Grant have for aspiring mathematicians, coders, and other students who are passionate about fields that are being most transformed upon by AI?

Watch on YouTube; read the transcript.

Sponsors

* Gemini 3.5 Live Translate is what I wished I’d had on my last trip to China. It detects more than 70 languages and translates them in near real-time… and it preserves your original pacing and intonation. If you’re building an app that needs live translation, you should check out Gemini 3.5 Live Translate. Get started at ai.studio/live

* Cursor’s harness lets me use models for a huge range of tasks at the podcast. For example, Cursor cuts out the ads from each episode I produce so I can post them on Bilibili. It also helps me prep for interviews — I have a repo full of books and papers that Cursor sorts through to find the exact right file for any given question. Try Cursor yourself at cursor.com/dwarkesh

* Jane Street sponsors 3Blue1Brown, so Grant has gotten to spend a lot of time with various Jane Streeters. He actually just recorded an interview with a few of them, so when we sat down for this episode, he told me about some of the things he learned, like how Jane Street keeps their role definitions fuzzy to make sure their people keep learning and growing. Go check out Grant’s full interview at 3b1b.co/janestreet

Timestamp…

The next big breakthrough will be AIs learning on the job

26 juni 2026 · 20 min

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Read it here. Lees meer

Thanks to Mercury for sponsoring this essay.

Mercury has automated basically my entire bill pay process for my business. I just give contractors a dedicated email address, and when they send an invoice, Mercury automatically creates a draft payment for me to review. I no longer have to hunt through my inbox for invoices or deal with messy spreadsheets to track my bills. Mercury handles it all. Learn more at mercury.com

Timestamps:

(00:00:00) – The big research bet the labs are making

(00:02:12) – Grindability is just as important as verifiability

(00:06:10) – Will RLVR alone generalize?

(00:08:41) – Getting the learning back to the weights

(00:15:22) – Dreaming

(00:17:23) – What 2027 looks like

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

The data black hole at the center of AI

19 juni 2026 · 12 min

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Read the transcript here. Lees meer

Thanks to Mercury for sponsoring this essay!

Mercury just released a new feature called Command, which gives me AI right in my banking platform. And since I use Mercury to run basically my entire business, Command has access to all the info it needs to get real work done. I can ask it to send invoices, or categorize expenses, or even transfer money… and Command just handles it. Learn more at mercury.com/command

Timestamps:

(00:00:00) – What is really driving AI progress?

(00:03:11) – Comparing human vs AI sample efficiency

(00:08:46) – Does sample efficiency matter?

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Ada Palmer – Machiavelli is the most misunderstood thinker of all time

16 juni 2026 · 2 uur 8 min

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Had Ada Palmer back on – this time to talk about Machiavelli, perhaps the most misunderstood thinker of all time. Lees meer

Machiavelli cut his teeth as a high-level diplomat for Florence, a position from which he got to closely observe the most important rulers in Europe at the time, including the ones who were on the path to destroying his dearly beloved Florence.

In 1513 the Medici retook control of Florence and, wrongly suspecting Machiavelli of participating in a coup attempt, fired, tortured, and exiled him.

Machiavelli could have left exile and worked for any number of different principalities that would have been eager to make use of his talents.

Instead, he decided to rot in the countryside and compile his career’s lessons about power, politics, and human nature into a book he dedicated to the very man whose new regime had tortured and exiled him, Lorenzo di Piero de’ Medici.

But at least the Medici were in a position to use his insights to defend Florence. Machiavelli the patriot did not want any other hands to touch these books, because those hands, armed further with these lessons, might pose an existential danger to Florence.

The closest modern analogy, at least as Machiavelli would have seen it, would be Szilard’s letter warning FDR about the possibility of a nuclear fission bomb.

What were those insights? And how were they inspired by Machiavelli’s dangerous diplomatic missions all across Europe, and his extensive reading of antiquity? Watch this episode with Ada Palmer to find out!

By the way, Ada is launching a new podcast which I’m very excited about. The first season will be about Machiavelli - a perfect way to dive deeper into the topics we discussed in this episode. Subscribe at Beforecast’s website to be notified of the first episode, subscribe on YouTube, follow her on Patreon, and if you want even more Ada, check out her FixTheNews Podcast episode, and check out her books and more.

Watch on YouTube; read the transcript.

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* Cursor re…

Alex Imas and Phil Trammell – What remains scarce after AGI?

4 juni 2026 · 1 uur 16 min

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Economics of AGI episode w Alex Imas and Phil Trammell. Lees meer

There’s a bunch of important questions about how we deal with AI that only economics can answer.

What is the optimal way to tax and redistribute the wealth that will be generated? How should countries not in the AI supply chain index into the gains? Is there any world where inequality doesn’t explode?

It might seem like these questions have obvious answers, but the first thing economics teaches you is that your intuitions can often be entirely wrong.

It was very helpful to chat through these things with Alex and Phil.

Watch on YouTube; read the transcript.

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Jane Street invests heavily in turning smart people into exceptional researchers and engineers. In addition to their apprenticeship model, Jane Street runs lectures and bootcamps in their in-office classrooms -- managers clear their teams’ schedules to encourage attendance. If you’d like to work at a place that takes learning this seriously, Jane Street is hiring. Check out their open roles at janestreet.com/dwarkesh

Google’s Gemini Omni has incredible video editing capabilities -- you can upload a video and have Omni change the background, adjust lighting, or add specific elements. But Omni is also a preview of how future frontier models will be trained -- fully multimodal on both input and output. You can try it yourself in the Gemini app at gemini.google or in Flow at flow.google

Cursor used targeted RL with textual feedback to help train their Composer 2.5 model. One of their researchers, Sasha Rush, gave me an impromptu blackboard lecture to explain how this form of on-policy self-distillation works -- I posted the full thing on X. If you want to try Composer 2.5, go to cursor.com/dwarkesh

Timestamps

(00:00:00) – Will capital share increase?

(00:19:36) – Messy Middle scenario

(00:25:57) – How to tax and redistribute AI wealth

(00:30:02) – Why demand collapse is unlikely

(00:39:26) – Human employees would be hard to integrate into…

Reiner Pope – Chip design from the bottom up

22 mei 2026 · 1 uur 20 min

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New blackboard lecture with Reiner Pope: how do chips actually work - starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do. Lees meer

Reiner is CEO of MatX, a new chip startup (full disclosure - I’m an angel investor). He was previously at Google, where he worked on software efficiency, compilers, and TPU architecture.

Watch this one on YouTube so you can see the chalkboard. Read the transcript.

Sponsors

* Crusoe was one of only five GPU clouds that made the gold tier in SemiAnalysis' most recent ClusterMAX report. Gold-tier providers like Crusoe delivered 5-15% lower TCO than silver-tier clouds, even with identical GPU pricing. This is because optimizations like early fault detection and rapid node replacement don't necessarily show up in the sticker price, but still matter a ton in the real world. Learn more at crusoe.ai/dwarkesh

* Cursor is where I do most of my work—from reading research papers to visualizing technical concepts to coding up internal tools for the podcast. Most recently, I used it to build two different review interfaces for my essay contest, one that anonymizes submissions for scoring and another that lets me see applicants' essays next to their resumes and websites. Whatever you're working on, you should try doing it in Cursor. Get started at cursor.com/dwarkesh

* Jane Street let me ask Ron Minsky and Dan Pontecorvo, two senior Jane Streeters, a bunch of questions about how they use AI. We discussed everything from the types of models they're training to how they think about the future of trading to why they're more bullish than ever on hiring technical talent. You can watch the full conversation and learn more about their open positions at janestreet.com/dwarkesh

Timestamps

00:00:00 – Building a multiply-accumulate from logic gates

00:16:31 – Muxes and the cost of data movement

00:26:10 – How systolic arrays work

00:39:11 – Clock cycles and pipeline registers

00:51:51 – FPGA…

Eric Jang – Building AlphaGo from scratch

15 mei 2026 · 2 uur 37 min

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Eric Jang walks through how to build AlphaGo from scratch, but with modern AI tools. Lees meer

Sometimes you understand the future better by stepping backward. AlphaGo is still the cleanest worked example of the primitives of intelligence: search, learning from experience, and self-play. You have to go back to 2017 to get insight into how the more general AIs of the future might learn.

Once he explained how AlphaGo works, it gave us the context to have a discussion about how RL works in LLMs and how it could work better – naive policy gradient RL has to figure out which of the 100k+ tokens in your trajectory actually got you the right answer, while AlphaGo’s MCTS suggests a strictly better action every single move, giving you a training target that sidesteps the credit assignment problem. The way humans learn is surely closer to the second.

Eric also kickstarted an Autoresearch loop on his project. And it was very interesting to discuss which parts of AI research LLMs can already automate pretty well (implementing and running experiments, optimizing hyperparameters) and which they still struggle with (choosing the right question to investigate next, escaping research dead ends). Informative to all the recent discussion about when we should expect an intelligence explosion, and what it would look like from the inside.

Watch on YouTube. Read the transcript.

And check out the flashcards I wrote to retain the insights.

Sponsors

* Cursor‘s agent SDK let me build a pipeline to generate flashcards for this episode. For each card, I had an agent read the transcript, ingest blackboard screenshots, generate an SVG visual, and run everything through a critic. A durable agent is much better at this kind of work than a chain of LLM calls, and Cursor’s SDK made it easy. Check out the cards at flashcards.dwarkesh.com and get started with the SDK at cursor.com/dwarkesh

* Jane Street gave me a real deep-dive tour of one of their datacenters. I got to ask a bunch of questions to Ron M…

David Reich – Why the Bronze Age was an inflection point in human evolution

8 mei 2026 · 2 uur 13 min

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David Reich is back. Lees meer

He and collaborator Ali Akbari just published a paper that overturns a long-standing consensus about human evolution — that natural selection has been dormant in our species since the agricultural revolution.

By scaling ancient DNA sequencing and developing a new statistical method, they found that selection has actually sped up.

Selection went especially bonkers during the Bronze Age (around 3,000 years ago).

That’s when gene frequencies for everything from immune function to body fat to intelligence were most in flux.

Over the last 10,000 years, selection pushed the genetic predictor of cognitive performance up by roughly a full standard deviation — most of it between 4,000 and 2,000 years ago.

After we finished recording, David sketched out on a whiteboard his new heretical model about who the Neanderthals really were. Luckily, I took out my iPhone and managed to record it.

He thinks the standard story (that Neanderthals are some separate archaic lineage we interbred with a little) just doesn’t fit the evidence. Instead, he proposes that Neanderthals are essentially genetically-swamped modern humans.

A small population somewhere around the Caucasus invented Middle Stone Age technology roughly 300,000 years ago and expanded outward. The ones that moved into Europe interbred with local archaic humans, got genetically swamped, and became Neanderthals. The same expansion went into Africa, met much more diverged archaic Africans, and that mixture became us.

This means Neanderthals and modern humans share the same cultural ancestry — the only difference is which archaic humans they mixed with afterward.

David is a brilliant and rigorous scholar. It was a real delight to learn from him again.

Watch on YouTube; read the transcript.

Sponsors

* Cursor was super useful as I prepped for this episode. Whenever I had a question, I’d have Cursor kick off a few different models simultaneously and then compare their responses. I found that this …

Reiner Pope – The math behind how LLMs are trained and served

29 april 2026 · 2 uur 14 min

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Did a very different format with Reiner Pope - a blackboard lecture where he walks through how frontier LLMs are trained and served. Lees meer

It’s shocking how much you can deduce about what the labs are doing from a handful of equations, public API prices, and some chalk.

It’s a bit technical, but I encourage you to hang in there – it’s really worth it.

There are less than a handful of people who understand the full stack of AI, from chip design to model architecture, as well as Reiner. It was a real delight to learn from him.

Recommend watching this one on YouTube so you can see the chalkboard.

Reiner is CEO of MatX, a new chip startup (full disclosure - I’m an angel investor). He was previously at Google, where he worked on software efficiency, compilers, and TPU architecture.

Download markdown of transcript here to chat with an LLM.

Wrote up some flashcards and practice problems to help myself retain what Reiner taught. Hope it's helpful to you too!

Sponsors

* Jane Street needs constant access to incredibly low-latency compute. I recently asked one of their engineers, Clark, to talk me through how they meet these demands. Our conversation—which touched on everything from FPGAs to liquid cooling—was extremely helpful as I prepped to interview Reiner. You can watch the full discussion and explore Jane Street’s open roles at janestreet.com/dwarkesh

* Google’s Gemma 4 is the first open model that’s let me shut off the internet and create a fully disconnected “focus machine”. This is because Gemma is small enough to run on my laptop, but powerful enough to actually be useful. So, to prep for this interview, I downloaded Reiner’s scaling book, disconnected from wifi, and used Gemma to help me break down the material. Check it out at goo.gle/Gemma4

* Cursor helped me turn some notes I took on how gradients flow during large-scale pretraining into a great animation. At first, I wasn’t sure the best way to visualize the concept, but Cursor’s Composer 2 Fast model let …

Jensen Huang – TPU competition, why we should sell chips to China, & Nvidia’s supply chain moat

15 april 2026 · 1 uur 43 min

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I asked Jensen about TPU competition, Nvidia’s lock on the ever more bottlenecked supply chain needed to make advanced chips, whether we should be selling AI chips to China, why Nvidia doesn’t just become a hyperscaler, how it makes its investments, and much more. Enjoy! Lees meer

Watch on YouTube; read the transcript.

Sponsors

* Crusoe’s cloud runs on state-of-the-art Blackwell GPUs, with Vera Rubin deployment scheduled for later this year. But hardware is only part of the story—for inference, Crusoe’s MemoryAlloy tech implements a cluster-wide KV cache, delivering up to 10x faster TTFT and 5x better throughput than vLLM. Learn more at crusoe.ai/dwarkesh

* Cursor helped me build an AI co-researcher over the course of a weekend. Now I have an AI agent that I can collaborate with in Google Docs via inline comment threads! And while other agentic coding tools feel like a total black-box, Cursor let me stay on top of the full implementation. You can try my co-researcher out at github.com/dwarkeshsp/ai_coworker, or get started on your own Cursor project today at cursor.com/dwarkesh

* Jane Street spent ~20,000 GPU hours training backdoors into 3 different language models, then challenged my audience to find the triggers. They received some clever solutions—like comparing the base and fine-tuned versions and extrapolating any differences to reveal the hidden backdoor—but no one was able to solve all 3. So if open problems like this excite you, Jane Street is hiring. Learn more at janestreet.com/dwarkesh

Timestamps

(00:00:00) – Is Nvidia’s biggest moat its grip on scarce supply chains?

(00:16:25) – Will TPUs break Nvidia’s hold on AI compute?

(00:41:06) – Why doesn’t Nvidia become a hyperscaler?

(00:57:36) – Should we be selling AI chips to China?

(01:35:06) – Why doesn’t Nvidia make multiple different chip architectures?

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Michael Nielsen – How science actually progresses

7 april 2026 · 2 uur 3 min

Afspelen

Really enjoyed chatting with Michael Nielsen about how we recognize scientific progress. Lees meer

It's especially relevant for closing the RL verification loop for scientific discovery.

But it's also a surprisingly mysterious and elusive question when you look at the history of human science.

We approach this question stories like Einstein (who claimed that he hadn't even heard of the famous Michelson-Morley experiment, which is supposed to have motivated special relativity, until after he had come up with the theory), Darwin (why did it take till 1859 to lay out an idea whose essence every farmer since antiquity must have observed?), Prout (how do you recognize that isotopes exist if you cannot chemically separate them?), and many others.

The verification loop on scientific ideas is often extremely long and weirdly hostile. Ancient Athenians dismissed Aristarchus's heliocentrism in the 3rd century BC because it would imply that the stars should shift in the sky as the Earth orbits the sun. The first successful measurement of stellar parallax was in 1838. That's a 2,000-year verification loop.

But clearly human science is able to make progress faster than raw experimental falsification/verification would imply, and in cases where experiments are very ambiguous. How?

Michael has some very deep and provocative hypotheses about the nature of progress. One I found especially thought-provoking is that aliens will likely have a VERY different science + tech stack than us. Which contradicts the common sense picture of a linear tech tree that I was assuming. And has some interesting implications about how future civilizations might trade and cooperate with each other.

Watch on Youtube; read the transcript.

Sponsors

* Labelbox researchers built a new safety benchmark. Why? Well, current safety benchmarks claim that attacks on top models are successful only a few percent of the time, but the prompts in those benchmarks don’t reflect how real bad actors actually write. You ca…

Terence Tao – Kepler, Newton, and the true nature of mathematical discovery

20 maart 2026 · 1 uur 24 min

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We begin the episode with the absolutely ingenious and surprising way in which Kepler discovered the laws of planetary motion. Lees meer

People sometimes say that AI will make especially fast progress at scientific discovery because of tight verification loops.

But the story of how we discovered the shape of our solar system shows how the verification loop for correct ideas can be decades (or even millennia) long.

During this time, what we know today as the better theory can actually make worse predictions.

And the reasons it survives this epistemic hell is some mixture of judgment and heuristics that we don’t even understand well enough to actually articulate, much less codify into an RL loop. Hope you enjoy!

Watch on YouTube; read the transcript.

Sponsors

- Jane Street loves challenging my audience with different creative puzzles. One of my listeners, Shawn, solved Jane Street’s ResNet challenge and posted a great walk-through on X. If you want to try one of these puzzles yourself, there’s one live now at janestreet.com/dwarkesh.

- Labelbox can get you rubric-based evals, no matter your domain. These rubrics allow you to give your model feedback on all the dimensions you care about, so you can train how it thinks, not just what it thinks. Whatever you’re focused on—math, physics, finance, psychology or something else—Labelbox can help. Learn more at labelbox.com/dwarkesh.

- Mercury just released a new feature called Insights. Insights summarizes your money in and out, showing you your biggest transactions and calling out anything worth paying attention to. It’s a super low-friction way to stay on top of your business. Learn more at mercury.com/insights.

Timestamps

(00:00:00) – Kepler was a high temperature LLM

(00:11:44) – How would we know if there’s a new unifying concept within heaps of AI slop?

(00:26:10) – The deductive overhang

(00:30:31) – Selection bias in reported AI discoveries

(00:46:43) – AI makes papers richer and broader, but not deeper

(00:53…

Dylan Patel — Deep dive on the 3 big bottlenecks to scaling AI compute

13 maart 2026 · 2 uur 31 min

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Dylan Patel, founder of SemiAnalysis, provides a deep dive into the 3 big bottlenecks to scaling AI compute: logic, memory, and power. Lees meer

And walks through the economics of labs, hyperscalers, foundries, and fab equipment manufacturers.

Learned a ton about every single level of the stack. Enjoy!

Watch on YouTube; read the transcript.

Sponsors

* Mercury has already saved me a bunch of time this tax season. Last year, I used Mercury to request W-9s from all the contractors I worked with. Then, when it came time to issue 1099s this year, I literally just clicked a button and Mercury sent them out. Learn more at mercury.com.

* Labelbox noticed that even when voice models appear to take interruptions in stride, their performance degrades. To figure out why, they built a new evaluation pipeline called EchoChain. EchoChain diagnoses voice models’ specific failure modes, letting you understand what your model needs to truly handle interruptions. Check it out at labelbox.com/dwarkesh.

* Jane Street is basically a research lab with a trading desk attached – and their infrastructure backs this up. They’ve got tens of thousands of GPUs, hundreds of thousands of CPU cores, and exabytes of storage. This is what it takes to find subtle signals hidden deep within noisy market data. If this sounds interesting, you can explore open positions at janestreet.com/dwarkesh.

Timestamps

(00:00:00) – Why an H100 is worth more today than 3 years ago

(00:24:52) – Nvidia secured TSMC allocation early; Google is getting squeezed

(00:34:34) – ASML will be the #1 constraint for AI compute scaling by 2030

(00:55:47) – Can't we just use TSMC's older fabs?

(01:05:37) – When will China outscale the West in semis?

(01:16:01) – The enormous incoming memory crunch

(01:42:34) – Scaling power in the US will not be a problem

(01:54:44) – Space GPUs aren't happening this decade

(02:14:07) – Why aren't more hedge funds making the AGI trade?

(02:18:30) – Will TSMC kick Apple out from N2?

(02:2…

The most important question nobody's asking about AI

11 maart 2026 · 25 min

Afspelen

Read the full essay here: https://www.dwarkesh.com/p/dow-anthropic Lees meer

Timestamps

(00:00:00) - Anthropic vs The Pentagon

(00:04:16) - The overhangs of tyranny

(00:05:54) - AI structurally favors mass surveillance

(00:08:25) - Alignment...to whom?

(00:13:55) - Coordination not worth the costs

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Why Leonardo was a saboteur, Gutenberg went broke, and Florence was weird – Ada Palmer

6 maart 2026 · 2 uur 2 min

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Renaissance history is so much wilder and weirder than you would have expected. Very fun chatting with Ada Palmer (historian, novelist, and composer based at the University of Chicago). Lees meer

Some especially fascinating things I learned from the conversation and her excellent book, Inventing the Renaissance:

Not only did Gutenberg go bankrupt in the 1450s (after inventing the printing press), but so did the bank that foreclosed on him, and so did his apprentices. This is because paper was still very expensive, and so you had to make this big upfront CAPEX decision to print a batch of 300 copies of a book - say the Bible. But he’s in a small landlocked German town where only priests are allowed to read the Bible - so he sells maybe 7 copies. It’s only when this technology ends up in Venice, where you can hand 10 copies to each of 30 ship captains going to 30 different cities, that it starts taking off.

Speaking of which, the printing revolution wasn’t just one single discrete event, just as the computer revolution has been this whole century of going from mainframes -> personal computers -> phones -> social media, each with different and accelerating social impact. Books came first, but they’re slow to print, and made in small batches. The real revolution is pamphlets - much faster, much harder to censor. Pamphlet runners are how you can have Luther’s 95 Theses go from Wittenberg to London in 17 days.

So much other wild stuff from this episode. For example, did you know that the largest and best-funded experimental laboratory in 17th century Europe was very likely the Roman one run by inquisitors? Ada jokes that the Inquisition accidentally invented peer review. The focus of the Inquisition is really misunderstood - it was obsessed with catching dangerous new heretics like Lutherans and Calvinists - it only executed one person for doing science.

And this leads Ada to make an observation that I think is really wise: the authorities and censors are always worried about…

Dario Amodei — "We are near the end of the exponential"

13 februari 2026 · 2 uur 22 min

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Dario Amodei thinks we are just a few years away from AGI — or as he puts it, from having “a country of geniuses in a data center”. In this episode, we discuss what to make of the scaling hypothesis in the current RL regime, why task-specific RL might lead to generalization, and how AI will diffuse throughout the economy. We also dive into Anthropic’s revenue projections, compute commitments, path to profitability, and more. Lees meer

Watch on YouTube; read the transcript.

Sponsors

* Labelbox can get you the RL tasks and environments you need. Their massive network of subject-matter experts ensures realism across domains, and their in-house tooling lets them continuously tweak task difficulty to optimize learning. Reach out at labelbox.com/dwarkesh.

* Jane Street sent me another puzzle… this time, they’ve trained backdoors into 3 different language models — they want you to find the triggers. Jane Street isn’t even sure this is possible, but they’ve set aside $50,000 for the best attempts and write-ups. They’re accepting submissions until April 1st at janestreet.com/dwarkesh.

* Mercury’s personal accounts make it easy to share finances with a partner, a roommate… or OpenClaw. Last week, I wanted to try OpenClaw for myself, so I used Mercury to spin up a virtual debit card with a small spend limit, and then I let my agent loose. No matter your use case, apply at mercury.com/personal-banking.

Timestamps

(00:00:00) - What exactly are we scaling?

(00:12:36) - Is diffusion cope?

(00:29:42) - Is continual learning necessary?

(00:46:20) - If AGI is imminent, why not buy more compute?

(00:58:49) - How will AI labs actually make profit?

(01:31:19) - Will regulations destroy the boons of AGI?

(01:47:41) - Why can’t China and America both have a country of geniuses in a datacenter?

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

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

5 februari 2026 · 2 uur 50 min

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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. Lees meer

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

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Adam Marblestone — AI is missing something fundamental about the brain

30 december 2025 · 1 uur 50 min

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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. Lees meer

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

Thoughts on AI progress (Dec 2025)

23 december 2025 · 12 min

Afspelen

Read the essay here. Lees meer

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

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Sarah Paine — Why Russia Lost the Cold War

19 december 2025 · 1 uur 55 min

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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. Lees meer

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’…

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

25 november 2025 · 1 uur 36 min

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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. Lees meer

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

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Satya Nadella — How Microsoft is preparing for AGI

12 november 2025 · 1 uur 28 min

Afspelen

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. Lees meer

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?

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Sarah Paine — How Russia sabotaged China's rise

31 oktober 2025 · 1 uur 31 min

Afspelen

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. Lees meer

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

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Andrej Karpathy — AGI is still a decade away

17 oktober 2025 · 2 uur 25 min

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The Andrej Karpathy episode. Lees meer

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

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Nick Lane – Life as we know it is chemically inevitable

10 oktober 2025 · 1 uur 20 min

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Nick Lane has some pretty wild ideas about the evolution of life. Lees meer

He thinks early life was continuous with the spontaneous chemistry of undersea hydrothermal vents.

Nick’s story may be wrong, but I find it remarkable that with just that starting point, you can explain so much about why life is the way that it is — the things you’re supposed to just take as givens in biology class:

* Why are there two sexes? Why sex at all?

* Why are bacteria so simple despite being around for 4 billion years? Why is there so much shared structure between all eukaryotic cells despite the enormous morphological variety between animals, plants, fungi, and protists?

* Why did the endosymbiosis event that led to eukaryotes happen only once, and in the particular way that it did?

* Why is all life powered by proton gradients? Why does all life on Earth share not only the Krebs Cycle, but even the intermediate molecules like Acetyl-CoA?

His theory implies that early life is almost chemically inevitable (potentially blooming on hundreds of millions of planets in the Milky Way alone), and that the real bottleneck is the complex eukaryotic cell.

Watch on YouTube; listen on Apple Podcasts or Spotify.

Sponsors

* Gemini in Sheets lets you turn messy text into structured data. We used it to classify all our episodes by type and topic, no manual tagging required. If you’re a Google Workspace user, you can get started today at docs.google.com/spreadsheets/

* Labelbox has a massive network of domain experts (called Alignerrs) who help train AI models in a way that ensures they understand the world deeply, not superficially. These Alignerrs are true experts — one even tutored me in chemistry as I prepped for this episode. Learn more at labelbox.com/dwarkesh

* Lighthouse helps frontier technology companies like Cursor and Physical Intelligence navigate the U.S. immigration system and hire top talent from around the world. Lighthouse handles everything, maximizing the probability of visa a…

Some thoughts on the Sutton interview

4 oktober 2025 · 12 min

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I have a much better understanding of Sutton’s perspective now. I wanted to reflect on it a bit. Lees meer

(00:00:00) - The steelman

(00:02:42) - TLDR of my current thoughts

(00:03:22) - Imitation learning is continuous with and complementary to RL

(00:08:26) - Continual learning

(00:10:31) - Concluding thoughts

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Richard Sutton – Father of RL thinks LLMs are a dead end

26 september 2025 · 1 uur 6 min

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Richard Sutton is the father of reinforcement learning, winner of the 2024 Turing Award, and author of The Bitter Lesson. And he thinks LLMs are a dead end. Lees meer

After interviewing him, my steel man of Richard’s position is this: LLMs aren’t capable of learning on-the-job, so no matter how much we scale, we’ll need some new architecture to enable continual learning.

And once we have it, we won’t need a special training phase — the agent will just learn on-the-fly, like all humans, and indeed, like all animals.

This new paradigm will render our current approach with LLMs obsolete.

In our interview, I did my best to represent the view that LLMs might function as the foundation on which experiential learning can happen… Some sparks flew.

A big thanks to the Alberta Machine Intelligence Institute for inviting me up to Edmonton and for letting me use their studio and equipment.

Enjoy!

Watch on YouTube; listen on Apple Podcasts or Spotify.

Sponsors

* Labelbox makes it possible to train AI agents in hyperrealistic RL environments. With an experienced team of applied researchers and a massive network of subject-matter experts, Labelbox ensures your training reflects important, real-world nuance. Turn your demo projects into working systems at labelbox.com/dwarkesh

* Gemini Deep Research is designed for thorough exploration of hard topics. For this episode, it helped me trace reinforcement learning from early policy gradients up to current-day methods, combining clear explanations with curated examples. Try it out yourself at gemini.google.com

* Hudson River Trading doesn’t silo their teams. Instead, HRT researchers openly trade ideas and share strategy code in a mono-repo. This means you’re able to learn at incredible speed and your contributions have impact across the entire firm. Find open roles at hudsonrivertrading.com/dwarkesh

Timestamps

(00:00:00) – Are LLMs a dead end?

(00:13:04) – Do humans do imitation learning?

(00:23:10) – The Era of Experience

(00:33…

Fully autonomous robots are much closer than you think – Sergey Levine

12 september 2025 · 1 uur 28 min

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Sergey Levine, one of the world’s top robotics researchers and co-founder of Physical Intelligence, thinks we’re on the cusp of a “self-improvement flywheel” for general-purpose robots. His median estimate for when robots will be able to run households entirely autonomously? 2030. Lees meer

If Sergey’s right, the world 5 years from now will be an insanely different place than it is today. This conversation focuses on understanding how we get there: we dive into foundation models for robotics, and how we scale both the data and the hardware necessary to enable a full-blown robotics explosion.

Watch on YouTube; listen on Apple Podcasts or Spotify.

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* Labelbox provides high-quality robotics training data across a wide range of platforms and tasks. From simple object handling to complex workflows, Labelbox can get you the data you need to scale your robotics research. Learn more at labelbox.com/dwarkesh

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* Gemini 2.5 Flash Image (aka nano banana) isn’t just for generating fun images — it’s also a powerful tool for restoring old photos and digitizing documents. Test it yourself in the Gemini App or in Google’s AI Studio: ai.studio/banana

To sponsor a future episode, visit dwarkesh.com/advertise.

Timestamps

(00:00:00) – Timeline to widely deployed autonomous robots

(00:17:25) – Why robotics will scale faster than self-driving cars

(00:27:28) – How vision-language-action models work

(00:45:37) – Changes needed for brainlike efficiency in robots

(00:57:59) – Learning from simulation

(01:09:18) – How much will robots speed up AI buildouts?

(01:18:01) – If hardware’s the bottleneck, does China win by default?

This is a public episode. If you would like to discuss this with …

How Hitler almost starved Britain – Sarah Paine

5 september 2025 · 1 uur 35 min

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In this lecture, military historian Sarah Paine explains how Britain used sea control, peripheral campaigns, and alliances to defeat Nazi Germany during WWII. She then applies this framework to today, arguing that Russia and China are similarly constrained by their geography, making them vulnerable in any conflict with maritime powers (like the U.S. and its allies). Lees meer

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* Labelbox partners with researchers to scope, generate, and deliver the exact data frontier models need, no matter the domain. Whether that’s multi-turn audio, SOTA robotics data, advanced STEM problem sets, or even novel RL environments, Labelbox delivers high-quality data, fast. Learn more at labelbox.com/dwarkesh

* Warp is the best interface I’ve found for coding with agents. It makes building custom tools easy: Warp’s UI helps you understand agent behavior and its in-line text editor is great for making tweaks. You can try Warp for free, or, for a limited time, use code DWARKESH to get Warp’s Pro Plan for only $5. Go to warp.dev/dwarkesh

To sponsor a future episode, visit dwarkesh.com/advertise.

Timestamps

00:00:00 – How WW1 shaped WW2

00:15:10 – Hitler and Churchill’s battle to command the Atlantic

00:30:10 – Peripheral theaters leading up to Normandy

00:37:13 – The Eastern front

00:48:04 – Russia’s & China’s geographic prisons

01:00:28 – Hitler’s blunders & America’s industrial might

01:15:03 – Bismarck’s limited wars vs Hitler’s total war

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Evolution designed us to die fast; we can change that — Jacob Kimmel

21 augustus 2025 · 1 uur 45 min

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Jacob Kimmel thinks he can find the transcription factors to reverse aging. We do a deep dive on why this might be plausible and why evolution hasn’t optimized for longevity. We also talk about why drug discovery has been getting exponentially harder, and what a new platform for biological understanding to speed up progress would look like. As a bonus, we get into the nitty gritty of gene delivery and Jacob’s controversial takes on CAR-T cells. For full disclosure, I am an angel investor in NewLimit. This did not impact my decision to interview Jacob, nor the questions I asked him. Lees meer

Watch on YouTube; listen on Apple Podcasts or Spotify.

China is killing the US on energy. Does that mean they’ll win AGI? — Casey Handmer

15 augustus 2025 · 1 uur 8 min

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How will we feed the 100s of GWs of extra energy demand that AI will create over the coming decade? On this episode, Casey Handmer (Caltech PhD, former NASA JPL, founder & CEO of Terraform Industries) walks me through how we can pull it off, and why he thinks a major part of this energy singularity will be powered by solar. His views are contrarian, but he came armed to defend them. Lees meer

Watch on YouTube; listen on Apple Podcasts or Spotify.

Artificial meat is harder than artificial intelligence — Lewis Bollard

7 augustus 2025 · 1 uur 8 min

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A deep dive with Lewis Bollard, who leads Open Philanthropy’s strategy for Farmed Animal Welfare, on the surprising economics of the meat industry. Lees meer

Why is factory farming so efficient? How can we make the lives of the 23+ billion animals living on factory farms more bearable? How far off are the moonshots (e.g., brainless chickens, cultivated meats, etc.) to end this mass suffering? And why does the meat industry have such a surprising amount of political influence?

For decades, innovation in the meat industry has actually made the conditions for animals worse. Can the next few decades of tech reverse this pattern?

Watch on YouTube; listen on Apple Podcasts or Spotify.

Donation match fundraiser

The welfare of animals on factory farms is so systemically neglected that just $1 can help avert 10 years of animal suffering.

After learning more about the outsized opportunities to help, I decided to give $250,000 as a donation match to farmkind.giving/dwarkesh. FarmKind directs your contributions to the most effective charities in this area.

Please consider contributing, even if it’s a small amount. Together, we can double each other's impact and give a total of $500,000.

Bluntly, there are some listeners who are in a position to give much more. Given how neglected this topic is, one such person could singlehandedly change the game for 10s of billions of animals. If you’re considering donating $50k or more, please reach out directly to Lewis and his team by emailing andres@openphilanthropy.org.

Timestamps

(00:00:00) – The astonishing efficiency of factory farming

(00:07:18) – It was a mistake making this about diet

(00:09:54) – Tech that’s sparing 100s of millions of animals/year

(00:16:16) – Brainless chickens and higher welfare breeds

(00:28:21) – $1 can prevent 10 years of animal suffering

(00:37:26) – Situation in China and the developing world

(00:41:41) – How the meat lobby got a lock on Congress

(00:53:23) – Business structure of the meat industry
…

Sarah Paine — How Imperial Japan defeated Tsarist Russia & Qing China

25 juli 2025 · 1 uur 56 min

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After my last lecture series with Sarah Paine ended, I still had so many questions. I knew we’d only scratched the surface of Sarah’s scholarship, so I immediately invited her back for another series: she graciously agreed, and we’ll be releasing the results online over the coming weeks and months! Lees meer

This first lecture is focused on the balance of power in East Asia at the turn of the 20th century. Specifically, how did Japan (population 47M) defeat China (400M) and Russia (130M) to become Asia's dominant power?

For me, the most interesting thing was that Japan's surprise attack on Port Arthur at the beginning of the Russo-Japanese War (1904) helps us understand why Japan might have thought Pearl Harbor would work.

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* Google’s Veo 3 helps us visualize the hypothetical scenarios that often come up during our interviews. Veo’s ability to generate both video and audio—all with incredible realism—makes it perfect for bringing our content to life. If you have a Google AI Pro or Ultra plan, you can try it in Gemini today by visiting gemini.google.

* Hudson River Trading is one of the world's top quantitative trading firms. Responsible for around 15% of all U.S. equities trading volume, HRT powers their trades with cutting-edge deep learning models. Their in-house AI team does fundamental ML research and then applies it to some of the most competitive markets in the world. If you’re interested in joining them, you can learn more at hudsonrivertrading.com/dwarkesh.

To sponsor a future episode, visit dwarkesh.com/advertise.

Timestamps

(00:00:00) – Japan’s Meiji reforms

(00:14:44) – Trans-Siberian railway & Japan’s 3-year window for empire

(00:29:58) – The most important battle in the Russo-Japanese war

(00:48:38) – China’s implosion: imperialism, civil wars, and opium

(00:59:31) – Was Russia on track to dominate Asia?

(01:14:20) – Pearl Harbor (1941) vs surprise attack of Port Arthur (1904)

(01:34:0…

Stephen Kotkin — How Stalin became the most powerful dictator in history

10 juli 2025 · 2 uur 13 min

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The Stephen Kotkin episode. Kotkin is arguably the world’s foremost expert on Joseph Stalin and has written a massive 2-volume biography on him (with a 3rd volume in the works). Lees meer

No other individual had more of a profound impact on the 20th century than Stalin. He held the power of life and death over every single person across 11 time zones, and he killed tens of millions of people, utterly consumed by an ideology aimed at building paradise on Earth.

And, he was one half of the biggest and most consequential military confrontation in history (even if Hitler didn’t prove to be his match).

Watch on YouTube; listen on Apple Podcasts or Spotify.

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* Lighthouse is THE fastest immigration solution for the technology industry. All they need is your resume or LinkedIn profile to tell you which visas you’re most eligible for, and they’ll send you this eligibility document for free, no commitment required. Get started today at https://www.lighthousehq.com/ref/Dwarkesh.

To sponsor a future episode, visit dwarkesh.com/advertise.

Timestamps

(00:00:00) – Was the tsarist regime the lesser of 2 evils?

(00:23:45) – The peasants brought Lenin to power, then he enslaved them

(00:37:38) – Why did so many go along with enforced famine and the Great Terror?

(01:02:26) – Today’s leftist civil war

(01:13:01) – Doesn’t CCP deserve credit for China's growth?

(01:35:13) – Why didn't somebody just kill Stalin?

(01:52:45) – Overcoming the pathologies of communism with tech: USSR vs China

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Why I don’t think AGI is right around the corner

3 juli 2025 · 14 min

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I’ve had a lot of discussions on my podcast where we haggle out timelines to AGI. Some guests think it’s 20 years away - others 2 years. Lees meer

Here’s an audio version of where my thoughts stand as of June 2025. If you want to read the original post, you can check it out here.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

A billion years of evolution in a single afternoon — George Church

26 juni 2025 · 1 uur 34 min

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George Church is the godfather of modern synthetic biology and has been involved with basically every major biotech breakthrough in the last few decades. Lees meer

Professor Church thinks that these improvements (e.g., orders of magnitude decrease in sequencing & synthesis costs, precise gene editing tools like CRISPR, AlphaFold-type AIs, & the ability to conduct massively parallel multiplex experiments) have put us on the verge of some massive payoffs: de-aging, de-extinction, biobots that combine the best of human and natural engineering, and (unfortunately) weaponized mirror life.

Watch on YouTube; listen on Apple Podcasts or Spotify.

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* WorkOS Radar ensures your product is ready for AI agents. Radar is an anti-fraud solution that categorizes different types of automated traffic, blocking harmful bots while allowing helpful agents. Future-proof your roadmap today at workos.com/radar.

* Scale is building the infrastructure for smarter, safer AI. In addition to their Data Foundry, they recently released Scale Evaluation, a tool that diagnoses model limitations. Learn how Scale can help you push the frontier at scale.com/dwarkesh.

* Gemini 2.5 Pro was invaluable during our prep for this episode: it perfectly explained complex biology and helped us understand the most important papers. Gemini’s recently improved structure and style also made using it surprisingly enjoyable. Start building with it today at https://aistudio.google.com

To sponsor a future episode, visit dwarkesh.com/advertise.

Timestamps

(0:00:00) – Aging solved by 2050

(0:07:37) – Finding the master switch for any trait

(0:19:50) – Weaponized mirror life

(0:30:40) – Why hasn’t sequencing/synthesis led to biotech revolution?

(0:50:26) – Impact of AGI on biology research progress

(1:00:35) – Biobots that use the best of biological and human engineering

(1:05:09) – Odds of life in universe

(1:09:57) – Is DNA the ultimate data storage?

(1:13:55) – Curing rare diseases with genetic counselin…

Why China's manufacturing economy is dominating — Arthur Kroeber

19 juni 2025 · 2 uur 27 min

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Arthur Kroeber is a leading researcher on Chinese tech and macro, a founding partner at Gavekal Dragonomics, and author of "China's Economy: What Everyone Needs to Know." It's the most useful, detailed resource I've found of how China actually works. Lees meer

On this episode, we discuss how China achieved high-tech manufacturing dominance, and where they'll go from here. By Arthur’s account, the Chinese government is like a giant VC fund: they decide on key priorities and then spend hundreds of billions of dollars subsidizing ruthless competition at the local level. They are willing to lose huge amounts of money for a few of their bets to pay off: at China’s scale, effectiveness matters more than efficiency.

There's also a growing bipartisan consensus that we need to combat China's rise. This doesn’t make much sense to me. China is a big, powerful country at the frontier in many fields, and its economy is intricately tied in with our own. Being instinctively adversarial is both unsustainable and risky. Arthur and I discuss how we can create a productive, mutually beneficial version of this relationship.

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Sponsors

* Scale is building the infrastructure for smarter, safer AI. In addition to their Data Foundry, they recently released Scale Evaluation, a tool that diagnoses model limitations. Learn how Scale can help you push the frontier at scale.com/dwarkesh.

* WorkOS Radar ensures your product’s free trials go to actual users. Radar uses 80+ signals to distinguish malicious bots from real people, eliminating costly free-tier abuse. See why companies like Cursor, Perplexity, and OpenAI use Radar by visiting workos.com/radar.

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"China is digging out of a crisis. And America’s luck is wearing thin." — Ken Rogoff

12 juni 2025 · 1 uur 36 min

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Ken Rogoff is the former chief economist of the IMF, a professor of Economics at Harvard, and author of the newly released Our Dollar, Your Problem and This Time is Different. Lees meer

On this episode, Ken predicts that, within the next decade, the US will have a debt-induced inflation crisis, but not a Japan-type financial crisis (the latter is much worse, and can make a country poorer for generations).

Ken also explains how China is trapped: in order to solve their current problems, they’ll keep leaning on financial repression and state-directed investment, which only makes their situation worse.

We also discuss the erosion of dollar dominance, why there will be a rebalancing toward foreign equities, how AGI will impact the deficit and interest rate, and much more!

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Sponsors

* WorkOS gives your product all the features that enterprise customers need, without derailing your roadmap. Skip months of engineering effort and start selling to enterprises today at workos.com.

* Scale is building the infrastructure for smarter, safer AI. In addition to their Data Foundry, they recently released Scale Evaluation, a tool that diagnoses model limitations. Learn how Scale can help you push the frontier at scale.com/dwarkesh.

* Gemini Live API lets you have natural, real-time, interactions with Gemini. You can talk to it like you were talking to another person, stream video to show it your surroundings, and share screen to give it context. Try it now by clicking the “Stream” tab on ai.dev.

To sponsor a future episode, visit dwarkesh.com/advertise.

Timestamps

(00:00:00) – China is stagnating

(00:25:46) – How the US broke Japan's economy

(00:37:06) – America's inflation crisis is coming

(01:02:20) – Will AGI solve the US deficit?

(01:07:11) – Why interest rates will go up

(01:10:55) – US equities will underperform

(01:22:24) – The erosion of dollar dominance

This is a public episode. If you would like to discuss this…

Xi Jinping’s paranoid approach to AGI, debt crisis, & Politburo politics — Victor Shih

29 mei 2025 · 1 uur 29 min

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On this episode, I chat with Victor Shih about all things China. We discuss China’s massive local debt crisis, the CCP’s views on AI, what happens after Xi, and more. Lees meer

Victor Shih is an expert on the Chinese political system, as well as their banking and fiscal policies, and he has amassed more biographical data on the Chinese elite than anyone else in the world. He teaches at UC San Diego, where he also directs the 21st Century China Center.

Watch on YouTube; listen on Apple Podcasts or Spotify.

Sponsors

* Scale is building the infrastructure for smarter, safer AI. In addition to their Data Foundry, they just released Scale Evaluation, a tool that diagnoses model limitations. Learn how Scale can help you push the frontier at scale.com/dwarkesh.

* WorkOS is how top AI companies ship critical enterprise features without burning months of engineering time. If you need features like SSO, audit logs, or user provisioning, head to workos.com.

To sponsor a future episode, visit dwarkesh.com/advertise.

Timestamps

(00:00:00) – Is China more decentralized than the US?

(00:03:16) – How the Politburo Standing Committee makes decisions

(00:21:07) – Xi’s right hand man in charge of AGI

(00:35:37) – DeepSeek was trained to track CCP policy

(00:45:35) – Local government debt crisis

(00:50:00) – BYD, CATL, & financial repression

(00:58:12) – How corruption leads to overbuilding

(01:10:46) – Probability of Taiwan invasion

(01:18:56) – Succession after Xi

(01:25:10) – Future growth forecasts

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Is RL + LLMs enough for AGI? — Sholto Douglas & Trenton Bricken

22 mei 2025 · 2 uur 24 min

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New episode with my good friends Sholto Douglas & Trenton Bricken. Sholto focuses on scaling RL and Trenton researches mechanistic interpretability, both at Anthropic. Lees meer

We talk through what’s changed in the last year of AI research; the new RL regime and how far it can scale; how to trace a model’s thoughts; and how countries, workers, and students should prepare for AGI.

See you next year for v3. Here’s last year’s episode, btw. Enjoy!

Watch on YouTube; listen on Apple Podcasts or Spotify.

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