If I had to put a number on it, I’d say I’m, I don’t know, maybe 85%–95% sure AI is in a bubble right now. The reason is that capabilities aren’t improving much, scaling the training of models is running into all sorts of problems (pre-training running out of steam, data running out, RL training being super inefficient), and fundamental issues scaling can’t overcome such as data inefficiency, poor generalization, lack of human example data in many domains, severe difficulties with models learning from video data, and a lack of continual learning or online learning.
Timing bubbles or timing the market in general is famously nearly impossible, so it’s hard to put a specific timeline on when I think the bubble will pop, but I reckon it’s gotta be within about 3 years, so by the end of 2028 or maybe a little further, but not much. In theory, a bubble could go on for quite a long time, but this is a huge bubble. The level of investment is immense, as described in the Atlantic article quoted above. It would be hard to sustain this level of investment for very long without delivering financial results, or delivering proxies for financial results like businesses’ pilot projects with AI going well.
I suspect when the AI bubble pops, for some people, suddenly the idea of imminent AGI will shatter like a dropped glass, for some people, it will be as if nothing happened at all, and for many people it will be somewhere in between. I can only hope that as many people as possible take it as an opportunity to return to fundamentals — go back to basics — and re-examine the case for near-term AGI from the ground up.
If I had to put a number on it, I’d say I’m, I don’t know, maybe 85%–95% sure AI is in a bubble right now. The reason is that capabilities aren’t improving much, scaling the training of models is running into all sorts of problems (pre-training running out of steam, data running out, RL training being super inefficient), and fundamental issues scaling can’t overcome such as data inefficiency, poor generalization, lack of human example data in many domains, severe difficulties with models learning from video data, and a lack of continual learning or online learning.
Timing bubbles or timing the market in general is famously nearly impossible, so it’s hard to put a specific timeline on when I think the bubble will pop, but I reckon it’s gotta be within about 3 years, so by the end of 2028 or maybe a little further, but not much. In theory, a bubble could go on for quite a long time, but this is a huge bubble. The level of investment is immense, as described in the Atlantic article quoted above. It would be hard to sustain this level of investment for very long without delivering financial results, or delivering proxies for financial results like businesses’ pilot projects with AI going well.
I suspect when the AI bubble pops, for some people, suddenly the idea of imminent AGI will shatter like a dropped glass, for some people, it will be as if nothing happened at all, and for many people it will be somewhere in between. I can only hope that as many people as possible take it as an opportunity to return to fundamentals — go back to basics — and re-examine the case for near-term AGI from the ground up.