Deep Reads

AI existential risk probabilities are (still) too unreliable to inform policy

How speculation gets laundered through pseudo-quantification

The AI-as-Normal-Technology view of loss-of-control incidents

A middle ground between the cybersecurity and AI safety communities

AI agents can't yet do open-ended AI research

Early evidence from two case studies

What will be left for us to work on?

My keynote at ICML 2026

OpenRouter: from Seed to Stripe — with OpenRouter’s Alex Atallah & AMP’s Anjney Midha

In 2023 most people doubted that there could be more than 1 or 2 frontier model labs. Now there are dozens.... and Stripe just bought the best known one for $7B.

[AINews] The Future of Latent Space

A quiet day lets us discuss the work behind the scenes - now open for business!

Runway’s WorldPrompt and the Engineering of Real-Time Worlds

GWM Worlds 2 uses persistent context and timed actions to steer a world model generating video and audio in real time.

Foundries vs Navigators: Lowering the Cost of Science

Guest Post: In science, thinking has gotten cheap but doing has not. This asymmetry is reshaping how research companies operate, largely inconspicuously.

Debating RSI, the US-China Gap, and Jaggedness with JS Denain of Epoch AI

Podcast #19

The current balance of power in open models

The expanded form of a testimony I prepared for Congress.

Why I still haven’t bought into true RSI

An “AI moderate’s” view on recent events and the trajectory of frontier models.

Open-Source AI & Open Models Reading List

How to get up to speed on open models and their implications.

The Overhang

Using your deep knowledge, wide knowledge, taste, and agency

Agency and Agents

From the Hugging Face Incident to Twilight Factories

An opinionated guide to which AI to use to do stuff

The Summer 2026 Edition

The twilight of the chatbots

How work changes along the exponential

My friends all hate AI; I just joined an AI startup

Over a decade after co-founding fast.ai, I am returning to the field

I Don’t Want a Learning Dashboard for My Child

What analog and AI education both get wrong

Breaking the Spell of Vibe Coding

Sinister variations on the positive state of flow

How To Use AI for the Ancient Art of Close Reading

Experiments in reading with LLMs

What America has meant to me

Every time I have given up on America, it has been a mistake. And yet, America has never, ever given up on me.

AIE Singapore: The Agentic Nation

i gave a little talk as closing keynote for the first AI Engineer Singapore. burned some bridges but said what i felt.

What you can do in a decade

I turned 40 today. For my 35th I did principles, but for my 40th, I wanted to offer perhaps more useful reflections.

How to Thought Lead (2026)

I first started compiling "How To Thought Lead" in my notes 5 years ago, at first as an ironic parody and then slowly becoming sincere, and never published it, 1) because I don't…

Harness Engineering for Self-Improvement

The concept of recursive self-improvement (RSI) dates back to I. J. Good (1965), where he defined an “ultraintelligent machine” as a system that can surpass humans in all intellectual activities and design better machines to improve itself. Yudkowsky (2008) used the phrase “recur

Scaling Laws, Carefully

Scaling laws are one of the most critical empirical findings in deep learning. The observation is simple in form: the training loss $L$ decreases predictably as we scale up model size $N$, dataset size $D$, and compute $C$, following a power-law curve, which appears as a straight

Why We Think

Special thanks to John Schulman for a lot of super valuable feedback and direct edits on this post. Test time compute (Graves et al. 2016, Ling, et al. 2017, Cobbe et al. 2021) and Chain-of-thought (CoT) (Wei et al. 2022, Nye et al. 2021), have led to significant improvements in

Reward Hacking in Reinforcement Learning

Reward hacking occurs when a reinforcement learning (RL) agent exploits flaws or ambiguities in the reward function to achieve high rewards, without genuinely learning or completing the intended task. Reward hacking exists because RL environments are often imperfect, and it is fu

After Orthogonality: Virtue-Ethical Agency and AI Alignment

Preface This essay argues that rational people don’t have goals, and that rational AIs shouldn’t have goals. Human actions are rational not because we direct them at some final ‘goals,’ but because we align actions to practices[1]: networks of actions, action-dispositions, action

AGI Is Not Multimodal

"In projecting language back as the model for thought, we lose sight of the tacit embodied understanding that undergirds our intelligence." –Terry Winograd The recent successes of generative AI models have convinced some that AGI is imminent. While these models appear to capture

Shape, Symmetries, and Structure: The Changing Role of Mathematics in Machine Learning Research

What is the Role of Mathematics in Modern Machine Learning? The past decade has witnessed a shift in how progress is made in machine learning. Research involving carefully designed and mathematically principled architectures result in only marginal improvements while compute-inte

What's Missing From LLM Chatbots: A Sense of Purpose

LLM-based chatbots’ capabilities have been advancing every month. These improvements are mostly measured by benchmarks like MMLU, HumanEval, and MATH (e.g. sonnet 3.5, gpt-4o). However, as these measures get more and more saturated, is user experience increasing in proportion to

Moving To Substack

I’m freezing this blog and starting to post on my Substack instead. The authoring experience is much more convenient for me there. Please follow me there, and check out The Illustrated DeepSeek R-1 if you haven’t yet. And check out our How Transformer LLMs Work course!

Generative AI and AI Product Moats

Here are eight observations I’ve shared recently on the Cohere blog and videos that go over them.: Article: What’s the big deal with Generative AI? Is it the future or the present? Article: AI is Eating The World

Remaking Old Computer Graphics With AI Image Generation

Can AI Image generation tools make re-imagined, higher-resolution versions of old video game graphics? Over the last few days, I used AI image generation to reproduce one of my childhood nightmares. I wrestled with Stable Diffusion, Dall-E and Midjourney to see how these commerci

The Illustrated Stable Diffusion

Translations: Chinese, Vietnamese. (V2 Nov 2022: Updated images for more precise description of forward diffusion. A few more images in this version) AI image generation is the most recent AI capability blowing people’s minds (mine included). The ability to create striking visua

Common pitfalls when building generative AI applications

As we’re still in the early days of building applications with foundation models, it’s normal to make mistakes. This is a quick note with examples of some of the most common pitfalls that I’ve seen, both from public case studies and from my personal experience. Because these pitf

Agents

Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.” The unpre

Building A Generative AI Platform

After studying how companies deploy generative AI applications, I noticed many similarities in their platforms. This post outlines the common components of a generative AI platform, what they do, and how they are implemented. I try my best to keep the architecture general, but ce

Measuring personal growth

My founder friends constantly think about growth. They think about how to measure their business growth and how to get to the next order of magnitude scale. If they’re making $1M ARR today, they think about how to get to $10M ARR. If they have 1,000 users today, they think about