alt Hacker NewsI think you're missing the point of "AI winter". It's not about how good the products are now. It's about how quickly the products are improving and creating the potential for profit. That's what drives investment.
3 things we know about the AI revolution in 2025:
- LLMs are amazing, but they have reached a plateau. AGI is not within reach.
- LLM investment has sacrificed many hundreds of billions of dollars, much of it from the world's pension funds.
- There is no credible path to a high-margin LLM product. Margins will be razor-thin positive at best once the free trial of the century starts to run out of steam.
This all adds up to a rather nasty crunch.
The thing about winter, though, is that it's eventually followed by another summer.
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Agreed. I am coming to suspect that there are approximately 2 positions on this subject: there are people who have previously weathered an AI winter and can therefore easily see the writing on the wall, and there are people who maybe don't quite understand the phenomenon being described by the term "AI winter".
It's not about how good or useful or potentially lucrative the technology is. Every previous catalyst for an AI winter has eventually become pervasive, changed the world, and made some people a lot of money. Every single one. And I do mean pervasive. If you could poof just one of them out of existence, my cell phone would become noticeably less useful.
What it's really about is how hype cycles interact with funding for basic research.
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 of LLMs like brains or CPUs. They're the core that does the processing, but needs to be embedded in a bigger system to be useful. Even if LLMs plateau, there will be a lot of development and improvement in the systems that use these LLM. We will be seeing a lot of innovation going forward, especially in systems that will be able to monetize these LLMs.
> 3 things we know about the AI revolution in 2025:
> - LLMs are amazing, but they have reached a plateau. AGI is not within reach.
Source/citation?
>> "LLMs have reached a plateau."
you should look at benchmarks such as ARC which went from "needs 10 years, currently at 0%" to almost solved within the least year. Also there is a revolution happening in math which the layman might be missing.