Computer-use AI is at its GPT-3 moment, not its GPT-4
Dwarkesh PatelWhy I don’t think AGI is right around the cornerat 14:00
From the conversation
It took 4 years to get from GPT 2 to GPT 4. Just to clarify, I am not saying that we won’t have really cool computer use demos in 2026 and 2027. GPT-3 was super cool, but it was not that practically useful. I’m saying that these models won’t be capable of end-to-end handling a week long and quite involved project which involves computer use. Ok, and as for the forecast of when AI will be able to learn on the job as easily, organically, seamlessly, and quickly as humans, for any white collar work. For example, if I hired an AI video editor, after six months it would have as much actionable, deep understanding of my preferences, our channel, what works for the audience, as well as a human would. I'd say this would come in 2032. While I don’t see an obvious way to slot in continuous online learning into the kinds of models these LLMs are, 7 years is a really long time! GPT 1 had just come out this time 7 years ago. It doesn’t seem implausible to me that over the next 7 years, we’ll find some way to get these models to actually learn on the job. At this point you might be reacting, "Wait you made this huge fuss about continual learning being such a huge handicap. But then your prediction is that we’re 7 years away from what, at a minimum, looks like a broadly deployed intelligence explosion." And yeah, you’re right.…
Summary
Current computer use AI capabilities are roughly at the level GPT-3 was for language, and it took four years to advance from GPT-2 to GPT-4. Impressive computer use demos in 2026 and 2027 should not be mistaken for genuine capability, as these models will not yet be able to handle end-to-end, week-long complex projects. The harder milestone—AI that learns on the job as organically and quickly as humans across any white-collar work—remains further out still.
Watch the clip on YouTubeStarts at 14:00