Here is my talk at @MIT (after some delay😅) I made this talk last year when I was thinking about a paradigm shift. This delayed posting is timely as we just released o1, which I believe is a new paradigm. It's a good time to zoom out for high level thinking. (1/11)

Fastest CEO I know; Liam ran 100m under 12s. Very bullish

welcome to the team @hwchung27 @_jasonwei and @EdwardSun0909! some may recognize them from various recent livestreams :)

@hwchung27 @EdwardSun0909 @_jasonwei @Meta Let’s go! Welcome to the team 🚀

Excited to share that I recently joined the MSL team! Building personal superintelligence is serious and fun here. Join us!

Old friends, new lab

After a great time at OpenAI, we (@EdwardSun0909, @_jasonwei) recently joined @Meta Superintelligence Labs. The first month has already been so much fun building from a clean slate with a truly talent-dense team! Very excited about the compute and long term focus of the new lab

@Cornell Slides:

@Cornell YouTube video:

This is my lecture from 2 months ago at @Cornell “How do I increase my output?” One natural answer is "I will just work a few more hours." Working longer can help, but eventually you hit a physical limit. A better question is, “How do I increase my output without increasing

Highly recommend this Stanford lecture video with @_jasonwei and @hwchung27 :) It's one of my favorites on scaling laws and the bitter lesson! Also Hyung's "Don't teach. Incentivize" video: https://t.co/KL0dDnYovz https://t.co/AXKkUcqTxq

When we make rapid progress, we tend to double down on the working paradigm. Bitter lessons suggest that this can be risky for deep learning. When trying to make a new paradigm to work at all, it is often necessary to add structures, e.g. clever modeling ideas. These structures

I often hear people say they believe the world will be vastly different in 5 years. Yet, many of them plan life and career as if things won’t change much. Why such discrepancy? Humans have bias towards downplaying major future changes, especially the fast changing ones. Perhaps

What we're seeing in AI will also happen in other technical fields. While AI’s expected impact is undeniably large, that's not unique; there are other hugely valuable areas, e.g. robotics, longevity. What truly differentiates AI is its rate of progress, specifically how it's

We have long been accustomed to planning life around a 30-year career. As our healthspan increases, that assumption is increasingly wrong. What would you do differently if your career were, say, 100 years instead of 30? Which options have you subconsciously given up because you

Woman has lingering sore throat. Doctor tells her to wait it out, ChatGPT suggests an ultrasound, which reveals…aggressive thyroid cancer. I tell all my friends and family - please get a second opinion on medical stuff from AI. It might save your life!

Differences in model quality are magnified with task difficulty. So if you work on harder problems, you benefit more from AI progress. Good forcing function to work on more challenging problems!

@yacineMTB Going back from One to Zero is harder than going from Zero to One.

If you already have plus or pro, it is very easy to try Codex CLI and you get free API credits. Give it a try for our latest codex mini model!

It was a fun (and intense) sprint working on the early versions of our codex (agent) and training the codex (mini-latest) model with @hwchung27 @fouadmatin @rohancalum, optimized for codex (cli)! 😅