Fall of the Incas & Aztecs. 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

New episode with Noam Brown. 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 ; listen on Apple Podcasts or Spotify . Sponsors Jane Street has been interested in AI for a lot longer than

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. Watch on YouTube ; listen on Apple Podcasts or Spotify . Sponsors Antithesis helps you trust your code. As agents generate

Breaking down 6 years of pretraining progress into data vs model improvements How much of the rapid progress in AI that we’ve seen over the last few years 1 has come from data versus model improvements? The answer has big implications for the economics of frontier labs and the pace of future progress. We investigate this question at a relatively small scale, and for pretraining specifically, from

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. 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 g

The OpenAI/Hugging Face attack, clearly explained This is a video recording of a post I wrote last week. You can read the original here .

The whole OpenAI/Hugging Face story in plain English Many thanks especially to Oak Hu , who paired with me for most of the writing, and also to Adam Kaufman and Alex Mallen , who paired with me during parts of research. You can watch or listen to me narrate this essay on YouTube , Spotify , and Apple Podcasts . Over the course of three months at OpenAI, three consecutive secret AI civilizations go

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

A debate about recursive self-improvement. Had Ryan Greenblatt 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’v

Locking in AI safety regulation now is a mistake. I have explained elsewhere why I think continual learning is needed. I don’t think you can have AIs that perform whole jobs as competently as humans if they’re forced to just write Markdown files from session to session. To give an illustrative example, imagine if the way students had to learn to play the saxophone is that one student tries to play

The end of cheap compute? 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 its rationale for every choice: I just review, fix a

If a human-level software engineer that could run on an H100 equivalent, at current market rates for software engineers, that H100 should rent for over $250k a year. That’s 15x today’s spot price. I want to experiment with very quick blog post where I time-box writing for 2 hours. I won’t be able to nail down a lot of important sub-questions, but the alternative is just not making any progress on

And why black holes are the ultimate power plants. 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 compellingly that even I could

Abolishing pandemics/ Getting out of the way of AI automation/ Learning from Honk Kong MTR's business model Two months ago, I posted some big questions about AI. We ended up getting over 600 essays submitted for this contest. Below is a bit of information of the 3 winners, followed by all 3 full essays. Thanks to everyone who participated! First Place - Jassi Pannu Jassi Pannu is an Assistant Prof

Watch now (94 mins) | Math is where we’ll see superintelligence first. What will it look like? 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

Labs are throwing away the most valuable data. Here’s the big research bet the labs are making currently : if we train AIs to accomplish millions of verifiable tasks across thousands of diverse RL environments, then we’ll basically have built AGI. Because such training will create these general problem solving skills (like how to make progress on an open ended task for weeks on end in the face of

One definition of intelligence is sample efficiency - that is to say, how much data do you need to see in a given domain in order to operate fluently and competently. It’s not clear that we’ve actually made much progress on training sample efficiency over the last few years - it seems like more so we’ve dramatically widened and improved the data distribution. The main way that AIs have been gettin

"He begged to work for the regime that tortured him." 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 destroying his dearly belov

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 world where inequality doesn’t explode? It might seem like these questions have

Working up from basic logic gates to why GPUs, TPUs, FPGAs, and the human brain each look the way they do. 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 previousl