Podcast profile
Dwarkesh Podcast
By Dwarkesh Patel
Deeply researched interviews www.dwarkesh.com
Latest episode
8 Predictions for the Era of Continual Learning
9 min
- Cadence
- Weekly
- Typical length
- 1 hr 38 min
- Latest release
- Aug 7, 2026
- Language
- EN
Topics
Frontier Research
Emerging scientific or technical capabilities and long-horizon ideas.
Policy & Society
Regulation, governance, ethics, and the cultural effects of technology.
Formats
Interview
A host-led conversation with one or more guests.
Explainer & Deep Dive
Structured exploration of one subject in substantial depth.
Audience level
Informed
Basic familiarity helps because industry context and terminology appear.
People behind the show
Current hosts
Listen from the original source
This directory never re-hosts or republishes podcast audio.
Official sources checked
Episode audio and show facts come from the checked-in refresh of the show’s public sources.
From the feed
Latest episodes
Dwarkesh Podcast9 min
8 Predictions for the Era of Continual Learning
Read the essay here. Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe
Dwarkesh Podcast11 min
Why smarter AI models could drive up compute prices 10x
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. 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
Dwarkesh Podcast1 hr 38 min
Adam Brown – A deep but accessible introduction to general relativity
Adam Brown is back! 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 co
Dwarkesh Podcast1 hr 34 min
Grant Sanderson – AI and the future of math
Always so much fun to chat with Grant. 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 mo
Dwarkesh Podcast20 min
The next big breakthrough will be AIs learning on the job
Read it here. 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 inb
Dwarkesh Podcast12 min
The data black hole at the center of AI
Read the transcript here. 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
Dwarkesh Podcast2 hr 8 min
Ada Palmer – Machiavelli is the most misunderstood thinker of all time
Had Ada Palmer back on – this time to talk about Machiavelli, perhaps the most misunderstood thinker of all time. 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 d
Dwarkesh Podcast1 hr 16 min
Alex Imas and Phil Trammell – What remains scarce after AGI?
Economics of AGI episode w Alex Imas and Phil Trammell. 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 w
Dwarkesh Podcast1 hr 21 min
Reiner Pope – Chip design from the bottom up
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. Reiner is CEO of MatX, a new chip startup (full disclosure - I’m an angel investor). He was previously at Google, where he worked
Dwarkesh Podcast2 hr 37 min
Eric Jang – Building AlphaGo from scratch
Eric Jang walks through how to build AlphaGo from scratch, but with modern AI tools. 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 insigh
Dwarkesh Podcast2 hr 13 min
David Reich – Why the Bronze Age was an inflection point in human evolution
David Reich is back. 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
Dwarkesh Podcast2 hr 14 min
Reiner Pope – The math behind how LLMs are trained and served
Did a very different format with Reiner Pope - a blackboard lecture where he walks through how frontier LLMs are trained and served. 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 th
Dwarkesh Podcast1 hr 43 min
Jensen Huang – TPU competition, why we should sell chips to China, & Nvidia’s supply chain moat
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! Watch on YouTube; read the transcript. Sponsors
Dwarkesh Podcast2 hr 3 min
Michael Nielsen – How science actually progresses
Really enjoyed chatting with Michael Nielsen about how we recognize scientific progress. 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 l
Dwarkesh Podcast1 hr 24 min
Terence Tao – Kepler, Newton, and the true nature of mathematical discovery
We begin the episode with the absolutely ingenious and surprising way in which Kepler discovered the laws of planetary motion. 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 sho
Dwarkesh Podcast2 hr 31 min
Dylan Patel — Deep dive on the 3 big bottlenecks to scaling AI compute
Dylan Patel, founder of SemiAnalysis, provides a deep dive into the 3 big bottlenecks to scaling AI compute: logic, memory, and power. 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
Dwarkesh Podcast25 min
The most important question nobody's asking about AI
Read the full essay here: https://www.dwarkesh.com/p/dow-anthropic 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 Get full access to Dwarkesh Pod
Dwarkesh Podcast2 hr 2 min
Why Leonardo was a saboteur, Gutenberg went broke, and Florence was weird – Ada Palmer
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). Some especially fascinating things I learned from the conversation and her excellent book, Inventing the Renaissance: Not only did Gut
Dwarkesh Podcast2 hr 22 min
Dario Amodei — "We are near the end of the exponential"
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 econo
Dwarkesh Podcast2 hr 50 min
Elon Musk — "In 36 months, the cheapest place to put AI will be space”
In this episode, John and I got to do a real deep-dive with Elon. We discuss the economics of orbital data centers, the difficulties of scaling power on Earth, what it would take to manufacture humanoids at high-volume in America, xAI’s business and alignment plans, DOGE, and much more. Watch on YouTube; read the trans
Dwarkesh Podcast1 hr 50 min
Adam Marblestone — AI is missing something fundamental about the brain
Adam Marblestone is CEO of Convergent Research. He’s had a very interesting past life: he was a research scientist at Google Deepmind on their neuroscience team and has worked on everything from brain-computer interfaces to quantum computing to nanotech and even formal mathematics. In this episode, we discuss how the b
Dwarkesh Podcast12 min
Thoughts on AI progress (Dec 2025)
Read the essay here. Timestamps 00:00:00 What are we scaling? 00:03:11 The value of human labor 00:05:04 Economic diffusion lag is cope00:06:34 Goal-post shifting is justified 00:08:23 RL scaling 00:09:18 Broadly deployed intelligence explosion Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe
Dwarkesh Podcast1 hr 55 min
Sarah Paine — Why Russia Lost the Cold War
This is the final episode of the Sarah Paine lecture series, and it’s probably my favorite one. Sarah gives a “tour of the arguments” on what ultimately led to the Soviet Union’s collapse, diving into the role of the US, the Sino-Soviet border conflict, the oil bust, ethnic rebellions and even the Roman Catholic Church
Dwarkesh Podcast1 hr 36 min
Ilya Sutskever — We're moving from the age of scaling to the age of research
Ilya & I discuss SSI’s strategy, the problems with pre-training, how to improve the generalization of AI models, and how to ensure AGI goes well. Watch on YouTube; read the transcript. Sponsors * Gemini 3 is the first model I’ve used that can find connections I haven’t anticipated. I recently wrote a blog post on RL’s
Dwarkesh Podcast1 hr 28 min
Satya Nadella — How Microsoft is preparing for AGI
As part of this interview, Satya Nadella gave Dylan Patel (founder of SemiAnalysis) and me an exclusive first-look at their brand-new Fairwater 2 datacenter. Microsoft is building multiple Fairwaters, each of which has hundreds of thousands of GB200s & GB300s. Between all these interconnected buildings, they’ll have ov