The end of the winters - of AI
Unbridled optimism, unlimited funding, and the promise of unprecedented returns: the perfect recipe for a tech bubble. But I'm not talking about 2025. Throughout AI history, researchers have been predicting the arrival of artificial general intelligence (AGI) in just a few years. And yet, it never comes.
There have already been two major crashes of this kind, giving birth to a new term: the "AI winter."
Today, some experts worry we might be heading into another winter if the current "bubble" bursts. It's a valid concern, but after thinking it through, I believe the framing is off. Even in the worst-case scenario, we'd only be facing an "AI autumn."
1. Is there a bubble?
I do believe there is a stock market valuation bubble: company valuations are out of sync with current profits. And what about future profits? Hard to say, but I still do think valuations are inflated.
Still, the current situation isn't comparable to past ones. Everyone brings up the dot-com bubble or the infamous tulip mania. Back in 2000, absurd valuations evaporated for things like social networks for dogs: cash-grabs with zero real utility.
Today, both the hardware infrastructure and the models themselves have intrinsic value. A friend of mine compared this moment to the American railroad bubble, and I think it's a great analogy. Even if some companies vanish, the infrastructure remains, and regular people will benefit once the market resets.
In fact, if the crazy demand for GPUs cools down, suppliers might be forced to lower prices, which would help consumers. The correction may even be a good thing, as we'll see.
2. What caused the last AI winters?
They came about because big promises of future marvels fell flat. When those promises weren't fulfilled, researchers were left with empty hands and mostly useless models.
But today's models are a different story. Even if they were not to improve a single inch over the next decade, they're already incredibly useful and valuable.
Qwen, Mistral, Deepseek, Gemini, ChatGPT... their usefulness is higher than zero and they won't vanish. Even if AGI never happens, even if these models never improve, not even by 1%, they already work, they already deliver value, and they can keep doing so for decades.
3. What would a bubble burst look like?
Previous winters brought a sharp halt to AI investment. Research groups were gutted, companies collapsed, and progress froze for years.
But today, we don't need massive funding to keep moving forward. Sure, it helps to build data centers and train larger, stronger models. But as I argue in this post (in Spanish), that might not even be the best direction.
If capital dried up, researchers would shift to optimizing what we already have, building smaller models with the same power. They'd explore alternative, more efficient architectures, because let's face it: using a language model to reason is like using a cannon to swat a fly. There's a lot of ground left to cover here.
This scenario, honestly, might be better. Though Silicon Valley might disagree... and maybe they're right.
Conclusion
The idea of a "new AI winter" as we've known it seems pretty much impossible. AI has put on a sweater, it's never going back to the cold. The field has matured and passed the minimum threshold of utility.
So I'd like to coin a new term: the AI autumn. It's a much better fit for the kind of future we might see, and I suggest we start using it!
Tags: AI