[__loam]

I think you're right, but I don't think "AI" as we see it today is really the thing we should be looking at when we come out of this bubble. What's really exciting is that we're building an enormous parallel computing infrastructure that's going to revolutionize scientific computing. We're already seeing some glimmers of this stuff like with what deepmind did with protein folding. Once the charletans die off I hope we see a massive acceleration in research in all kinds of fields.

[lxgr]

That's a good way to put it.

That said, I do think that LLMs, while not the "final form of AI" by any means, are already somewhat of a revolution in human-machine interfaces. Being able to look up facts (or make up convincing lies) is neat, but to me, their real power lies in how good they are in summarizing and translating.

Remember when Siri and Google Assistant were having a very hard time understanding even the simplest commands if they weren't formulated in the exact way they understood, and the "aboutness" problem seemed unsurmountable without AGI?

Now we're suddenly way past that (without any AGI). Even if AI completely plateaus out with LLMs at their present-day strength, I think we could spend years, if not decades, of getting good at meaningfully integrating them into previously very manual workflows. Even an "AI winter" of that shape feels significantly more disruptive than many of the more optimistic crypto scenarios.

[otabdeveloper4]

> we're building an enormous parallel computing infrastructure that's going to revolutionize scientific computing

We're doing an absolute shit job of it and basing our foundations on piles of sand. We're gonna have to throw it all away and do it right the second time if we ever decide to do something useful.

[smackeyacky]

I don’t think that matters. Out of the Dotcom rubble, we got a lot of useful ideas for tools even though the actual tools all got thrown away. It was the ideas and the “hey, look at what is possible” that survived i.e. Linux came of age properly and now the world runs on it.

AI will quickly pollute itself, but the infrastructure will survive. That most of it will be thrown away is perfectly ok, the ideas will live on.

[otabdeveloper4]

> but the infrastructure will survive

What infrastructure? Massively inefficient corporate rent-seeking attempts aren't infrastructure.

There is no AI "Linux" in 2024, all AI tools are closed-source and proprietary.

[__loam]

I'm not sure I agree with that and I'm one of the biggest ai pessimists here. The gpus getting created to do this shit aren't just gonna get thrown out (maybe sold in a fire sale), and they're pretty general purpose. Tons of science needs massive compute.

[otabdeveloper4]

Using GPUs for neural network inference is inefficient and makes no sense, unless there's some hype bubble propping it all up.

Maybe sometime in the future a commodity manufacturer of massively parallel CPUs for stupidly parallel tasks appears, but Nvidia ain't it.

[happymellon]

How many cores/threads would you need to challenge the GPU?

Ampere has 320 core chips as a dual socket, although a 4090 might still be cheaper.

[otabdeveloper4]

80% of the effort and cost of a GPU is various bullshit related to rendering DirectX games on Windows.