We are already seeing AI speeding up the development of AI, as it substitutes for human expertise. As the remaining human contribution gets smaller I expect this to compound dramatically, and we’ll see rapid improvement even compared to today.
Which I think is significantly less strong than your summary. Regarding takeoff, the questions of
How close is the whole AI capabilities research community (including AIs) already to knowing enough to build AGI?
How much do current / near-future AIs contribute to the hardest parts of AI capabilities research?
would be informed a lot by “is the current thing already basically weak AGI”.
Agreed that my claim was much stronger than his phrasing, I was making a further claim he could have about why it might not matter, which he might have meant or agree with, or not, but I agree your questions are important to whether the claim is true.
My contention would be that 2026 AI wouldn’t matter without 2026 levels of hardware build out and production trends, so that is the more critical issue. (If you needed the compute to train a frontier model on top 2016 hardware, much less 2006 hardware, you’d need multiple decades to finish. And given architectures, it wouldn’t even work.)
His tweet about that is
Which I think is significantly less strong than your summary. Regarding takeoff, the questions of
How close is the whole AI capabilities research community (including AIs) already to knowing enough to build AGI?
How much do current / near-future AIs contribute to the hardest parts of AI capabilities research?
would be informed a lot by “is the current thing already basically weak AGI”.
Agreed that my claim was much stronger than his phrasing, I was making a further claim he could have about why it might not matter, which he might have meant or agree with, or not, but I agree your questions are important to whether the claim is true.
My contention would be that 2026 AI wouldn’t matter without 2026 levels of hardware build out and production trends, so that is the more critical issue. (If you needed the compute to train a frontier model on top 2016 hardware, much less 2006 hardware, you’d need multiple decades to finish. And given architectures, it wouldn’t even work.)