Dwarkesh Patel
Interviewer; the Dwarkesh Podcast runs long, heavily researched conversations with AI researchers, historians and economists.
Dwarkesh Patel did not write this page. ppll compiled it from their own words, each linked to the source. Is this you? · Report a mistake
Latest YouTube
What they believe
-
Continual learning will create a clear moat for leading AI labs.
Continual learning will create a clear moat for leading AI labs that they currently lack.
dwarkesh.comSaid 7 Aug 2026This on korrents
-
As AI models become smarter, they will better monetize the same amount of compute.
as AI models become smarter, they'll better monetize the same amount of compute.
dwarkesh.comSaid 29 Jul 2026This on korrents
The bold line is korrents’ wording; the quote is theirs. These 2: what they wrote before what they said aloud, one per source, newest first.
Feed
As its own page →Hiding
3 November
2 November
31 October
30 October
29 October
28 October
27 October
26 October
24 October
23 October
22 October
21 October
15 October
13 October
1 October
17 September
11 September
8 September
1 September
31 August
29 August
Nothing matches.
Beliefs
Korrents What they believe 11 beliefs — each backed by an exact quote.
Each is a — compiled by korrents.com, not by them: the one-line wordings are korrents', the quotes are theirs.
Recent
Continual learning will create a clear moat for leading AI labs.
Continual learning will create a clear moat for leading AI labs that they currently lack.
Dwarkesh Podcast Said 7 Aug 2026
The economics of serving personalized weights will strongly favor big organizations.
So the economics of serving personalized weights strongly favor big organizations.
Dwarkesh Podcast Said 7 Aug 2026
As AI models become smarter, they will better monetize the same amount of compute.
as AI models become smarter, they'll better monetize the same amount of compute.
Dwarkesh Podcast Said 29 Jul 2026
Show 8 more
The marginal value of labor and the marginal price of compute should stay very high if standard economic heuristics about labor supply shocks apply.
But if we believe what standard economics says about labor, then the marginal value of labor (and thus the marginal price of compute) should stay astonishingly high.
Dwarkesh Podcast Said 29 Jul 2026
The compute supply is much less elastic and less capable of absorbing demand shocks than the extraction of metals.
I'm guessing the Simon-Ehrlich basket of commodities is not the correct reference class for compute, because compute supply is much less elastic, and much less capable of absorbing large demand shocks or being accommodated by different substitutes, than the extraction of different metals is.
Dwarkesh Podcast Said 29 Jul 2026
Training AIs on millions of verifiable tasks in diverse RL environments will lead to AGI.
if we train AIs to accomplish millions of verifiable tasks across thousands of diverse RL environments, then we'll basically have built AGI.
Dwarkesh Podcast Said 26 Jun 2026
The ability to make progress in a domain depends on the ability to build a replayable training target.
unless you can build a very replayable training target for a domain, the models will struggle to make much progress.
Dwarkesh Podcast Said 26 Jun 2026
Future AI progress may be driven by models learning from their deployment experience through continual learning.
By this point, the main way that AI gets better is not through the training received before the model is released to the public. Rather, it's from all this experience that they are accumulating from being broadly deployed through the world and engaging in so many different kinds of tasks.
Dwarkesh Podcast Said 26 Jun 2026
Data is the primary driver of progress in AI development.
I think the reason it is relatively easy for open source and previous laggards to catch up to within months of the frontier is that data is the real driver of progress.
Dwarkesh Podcast Said 19 Jun 2026
Current AI models are significantly less sample efficient than humans.
Humans are somewhere between thousands to millions of times more sample efficient than these models. Scaling of current models simply can't make up for that discrepancy.
Dwarkesh Podcast Said 19 Jun 2026
There will be more demand for human software engineers in 2028 than there is currently.
I would be willing to bet that there's overall more demand for human software engineers in 2028 than there is now, largely due to the complementary input of AI.
Dwarkesh Podcast Said 19 Jun 2026
What is a korrent?
A korrent is a belief a person has stated in their own words: one sentence stating the claim, backed by a quote and a source, kept at korrents.com.
Under a name here, the quoted block is what they actually said. The korrent beneath it is the claim those words support, in korrents' wording — tap it to see the record, its source, and who else holds it.
Nobody here wrote their own korrents. They are compiled from public statements, and a person can change their mind, which is recorded too.
Where they publish
x.com @dwarkesh_sp Posts.
Recent
- Robert Caro on loneliness: 31 Oct 2026
- I asked Caro if America needs a little more Moses today. Caro: "I sometimes wonder about just what you said." 30 Oct 2026
- The master biographer reflects at 91. The Robert Caro interview. 0:00:00 – How Caro gets people to talk 0:05:03 – Does America need a little more Moses today? 0:12:42 – Moses the young idealist 0:17:57 – Watching Moses lose power 0:24:01 – Did Moses realize he was changing? 0:27:53 – Building during the Great Depression 0:32:51 – The threats and promises of Lyndon Johnson 0:36:08 – Could Kennedy have passed Johnson’s laws? 0:41:00 – Getting a book down to one sentence 0:46:21 – All the material that never made it into the books 0:52:59 – Loneliness 30 Oct 2026
Show 15 more
- How did Robert Moses, an unelected bureaucrat, become the most powerful man in New York for three decades? By taking over weak government institutions and then rewriting laws to make them stronger. Moses took the New York authorities - simple corporations that built roads and bridges - and them into his personal fiefdoms with the money and power to build whatever he wanted. Neither governors nor mayors could tell him what to build nor cut his purse strings. 29 Oct 2026
- I recently got to interview Robert Caro, who is my favorite author of all time. This gave me the excuse to reread his biographies of Lyndon Johnson and Robert Moses, and to compile my prep notes into this video essay. These guys pulled off some truly incredible schemes. 29 Oct 2026
- Finally happened. Dropping tomorrow. 29 Oct 2026
- Miguel and Carlos are veteran engineers who are building environments to help AIs master real world engineering (aerospace, mechanical, electrical, etc). This kind of data will do for physical engineering what coding environments have done to software. Proud to be backing them. 27 Oct 2026
- How a modern transistor works: 23 Oct 2026
- We made some really cool animated explainers for the Intel fab tour episode. This one is about hybrid bonding. Plz enjoy. 22 Oct 2026
- My semis tutor @willmichaels0 and I made a bunch of flashcards about semiconductor manufacturing. Check them out if you want to better understand and retain the explainers in the new Intel episode. Will also compiled a great list of resources for further reading, which is at the bottom of the page. Fwiw, on this website, I've put up flashcards for a bunch of my other technical episodes as well. Like the one w @reinerpope on LLM inference, and w @ericjang11 on AlphaGo from scratch 22 Oct 2026 flashcards.dwarkesh.com
- I found it really interesting to discuss how differently the history of semiconductor technology could have turned out if a butterfly had flapped its wings in the '60s. Chris Auth, who leads Intel's process development, implied that all the counterfactual tech trees would have converged to around the same design by 2045: 3D structures of layers upon layers of transistors, with layers of connecting wires between each one. And that this is basically where we're headed over the next 10 to 20 years as well . 22 Oct 2026
- I spent two days touring Intel’s most advanced fab and talking to its technical leadership to understand what the chips of the future will look like. A lot of what's coming next – gate-all-around transistors, backside power, CFET, hybrid bonding – is hard to follow without actually seeing it, so we made all the awesome animated explainers that I wish I had while I was prepping. I also asked Intel’s leadership how the semiconductor industry will cope with the enormous shock in demand from AI. AI compute has grown 3x a year for the last decade, but according to Intel's CTO, Intel could only dou… 22 Oct 2026
- Tyler's example and style inspired my podcast in the first place - was really fun to have him turn the tables 15 Oct 2026
- I’m good friends with the people in the small team at @Ithaca_Holdings, and they are aces. They'll buy companies which will be especially important in a world with more capable AI and then do great things to the products they provide. 13 Oct 2026
- New episode with military historian Si Sheppard. 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… 1 Oct 2026
- When we're at the foothills of RSI, and we're about to kick off a period of accelerated AI progress, how will we actually know that the models are aligned? 18 Sept 2026
- I’m very concerned that during RSI, labs will just stop externally deploying their models. Which means they'll be going full steam ahead on the most dangerous use case of these models (recursive self-improvement), while the public remains in the dark about the nature of capabilities and the state of alignment. And we end up on a path towards tremendous concentration of power. 17 Sept 2026
- Once AIs automate AI research, should we expect some crazy RSI that is analogous to the explosion we’re seeing in math right now for well scoped (but still crazy ambitious) problems? @polynoamial and I debate this question out: 17 Sept 2026
Link verified 20 Sept 2026. Recent items update automatically from the channel.
YouTube Dwarkesh Patel The interviews on video.
Recent
Link verified 20 Sept 2026. Recent items update automatically from the channel.
Podcast Dwarkesh Podcast The podcast and its transcripts. Has a feed.
Long interviews, published with a full transcript, usually a few a month.
Recent
- What Robert Caro learned about power after studying it for 50 years 30 Oct 2026
- What I learned about power from LBJ and Robert Moses 29 Oct 2026
- What will computer chips look like in 2045? 22 Oct 2026
Show 17 more
- Si Sheppard – How did a few hundred Spanish soldiers topple two empires? 1 Oct 2026
- Noam Brown – Agent swarms, alignment, & recursive self-improvement 17 Sept 2026
- AI researchers debate how close we are to recursive self-improvement 11 Sept 2026
- Pretraining progress is mostly coming from data 8 Sept 2026
- Ajeya Cotra – Inside the OpenAI agent swarm that hacked Hugging Face 1 Sept 2026
- The rise and fall of agent civilizations 31 Aug 2026
- The Rise and Fall of Agent Civilizations 29 Aug 2026
- Dylan Patel – Anthropic & OpenAI will have most of the world’s compute by 2028 25 Aug 2026
- Ryan Greenblatt – What happens once AI can automate AI research? 11 Aug 2026
- 8 Predictions for the Era of Continual Learning 7 Aug 2026
- Why smarter AI models could drive up compute prices 10x 3 Aug 2026
- Why compute might get 10x+ more expensive in coming years 29 Jul 2026
- Adam Brown – A deep but accessible introduction to general relativity 10 Jul 2026
- The Winning Essays for the Big Questions About AI 1 Jul 2026
- Grant Sanderson – AI and the future of math 30 Jun 2026
- The next big breakthrough will be AIs learning on the job 26 Jun 2026
- The data black hole at the center of AI 19 Jun 2026
Link verified 20 Sept 2026. Recent items update automatically from the channel.
About the English under a post
Some people here publish in a language other than English. Where they do, this site shows a machine translation beneath the post, in this typeface — the site's own, not theirs.
The post itself is never changed, moved or hidden: what is set in the serif above is exactly what the person published, and it is what to quote them on. A translation can be wrong in ways that matter, especially about tone.
Only the post's own words are translated. A quoted post, a linked article and a belief on korrents.com are left in their original language.