Many technologies plateau, but we don't say they all have winters. Terrestrial radio winter? Television winter? Automobile winter? Air travel winter? Nuclear power comes close in terms of its tarnished image and reluctance to reinvest.
I personally believe contemporary AI is over-hyped, but I cannot say with confidence that it is going to lead to a similar winter as the last time. It seems like today's products satisfy enough users to remain as a significant area, even if it doesn't greatly expand...
The only way I could see it fizzling as a product category is if it turns out it is not economically feasible to operate a sustainable service. Will users pay a fair price to keep the LLM datacenters running, without speculative investment subsidies?
The other aspect of the winter is government investment, rather than commercial. What could the next cycle of academic AI research look like? E.g. exploration that needs to happen in grant-funded university labs instead of venture-funded companies?
The federal funding picture seems unclear, but that's true across the board right now for reasons that have nothing to do with AI per se.
I think it's easy to talk past one another on this subject. To be sure, I love Claude code. I wish I could pay for several years in advance at today's prices.
But the consumer's is not the important perspective for the AI hype cycle. It's the investors' perspective. I'm going to guess that well over a trillion dollars has gone into "AI", including the major labs and all the little "agents for XYZ" startups popping up every day. From the investors' perspective, that better pay off several times over in profit, not revenue, in the next few years. Prices will go up, but competition is fierce and nobody will be able to command a high margin. How are they going to make trillions in profit with razor thin margins?
This will make the very mention of "AI" toxic for most investors sooner than later.
> This will make the very mention of "AI" toxic for most investors sooner than later.
I'm not so sure. I agree about the exceptionally off the charts expectations rivaling only the dotcom bubble, but with the current rate of progress I'd expect AI to be pervasive enough to disappear from investor relationship materials not because it's a buzzword, but because it's assumed to be incorporated just like companies don't mention that they're running Linux servers; companies saying that they're doing stuff without AI will be something to watch for.
It may be my academic career bias, but I feel like the real AI Winter was not due to commercial investor perception. It was a deeper collapse of the government grant funding and higher education agenda which throttled a generation of researchers.
I personally believe contemporary AI is over-hyped, but I cannot say with confidence that it is going to lead to a similar winter as the last time. It seems like today's products satisfy enough users to remain as a significant area, even if it doesn't greatly expand...
The only way I could see it fizzling as a product category is if it turns out it is not economically feasible to operate a sustainable service. Will users pay a fair price to keep the LLM datacenters running, without speculative investment subsidies?
The other aspect of the winter is government investment, rather than commercial. What could the next cycle of academic AI research look like? E.g. exploration that needs to happen in grant-funded university labs instead of venture-funded companies?
The federal funding picture seems unclear, but that's true across the board right now for reasons that have nothing to do with AI per se.