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Comment by chrismarlow9 | Hacker News Reader

I don't remember where I heard this, but one of my favorite criticisms of the current AI situation is that it's wrong simply because of the size and energy required compared to the human brain. The idea is that there's still some element missing thats fundamental, and that the way we train them now is part of the solution, but not all of it. I think finding the extra missing element is going to take an entirely different approach that will also solve the sizing and resource issue. The kickers is that if they do achieve (and solve) AGI in this way all the giant data centers would be mostly useless.

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Yes, the very explicit plan of both OpenAI and Anthropic is to use the not particularly efficient LLMs to automate their own AI engineering. That seems to be going well - on coding front and model tuning front so far. They have more planned.

And then use those to find fundamentally better new architectures for AI - that perhaps are as efficient as the human brain.

It might not work, but I didn't think it'd solve maths problems... So it might work. And if it happens, they'd use the data centres to run millions of instances of it.

It's scary, TBH.

I recall them saying they use models to write CUDA kernels and whatnot. Makes sense, and unsurprising that models are good at writing code.

But I think calling this “automating AI research” is misleading. I’m not sure there’s evidence yet that they do creative research work. Even in mathematics, but they are finding counter-examples by intelligent brute-forcing. Not to downplay the results, as they are incredible, but this is one very specific kind of proof and not the most creative type, which arguably requires generalisation.

> but I didn't think it'd solve maths problems

Finding counterexamples is low-hanging fruit, the automation of which isn't shocking.

What about finding the 1st known complex structure over S^6, proving Ehrhart’s volume conjecture, proving a sharp "density" bound on primitive sets conjectured by Erdos >60 years ago?

> Finding counterexamples is low-hanging fruit, the automation of which isn't shocking.

It's not good to be confidently wrong the way you're being.

We've had mathematical problems solved by brute force in the past.

We've then improved that through systems similar to prolog intentionally searching a tree.

Then systems added heuristics for which paths in that tree are likely to be taken.

The LLMs are just using slightly more accurate heuristics for this task.

But the real measure of understanding are tasks that are not so strictly constrained.

If a foundation model company burns billions of tokens to brute force an LLM into finding a new training algorithm that e.g. allows recurrent networks without catastrophic forgetting...

I won't really care that it didn't have a "real measure of understanding". I'll care that it has made an even more dangerous technology, which needs work to make it aligned.

It’s a bird! It’s a plane! It’s…AI skeptics moving the goalposts at light speed!!

Breaking news: a machine can do a tedious repetitive task faster than a human.

Quite the gamble.

If we manage to get to AGI and it looks, works and behaves like a human brain... I mean, cool, but that's a very useless AGI compared to the incredible stuff we have access to today.

The HN crowd I'm sure will still be unhappy calling it AGI because "it's not AGI unless its speech comes from the cerebral cortex region of the brain, otherwise it's just sparkling emoji" or something.

you're on one of the most pro AI spaces on the whole internet and yet you're still crying about "the hn crowd", what a bizarre distorted perspective

HN is not one of the most pro AI spaces. It may be a bit more pro ai than highly secluded communities but the other day I had people responding to me that it’s cooler to be an alcoholic than to use AI.

There is a wide reaching anti AI/AI-denialist sentiment here that is extremely pronounced in some threads, it gets very stupid very quickly. And what I’m referring to is the habit of some users here to always move the goalposts on AGI.

Could you point me to the goals so I know when I'm moving the goalposts?

maybe you're on European tzs? the sentiment changes quite a bit with who's awake at the time a thread reaches the frontpage

I think the idea is that you wouldn’t need humans to do anything anymore, right? As impressive as it is, it’s still ultimately directed by human planning and coordination. Assuming they are aligned, you could have a collection of AGI that you let loose and they tirelessly solve all of humanity’s problems, do all of our work, and progress science and our understanding of the universe.

Those are all things that humanity is doing everyday. What we have is amazing, but it’s not that.

The infrastructure you just described is absolutely buildable today if you’re willing to burn tokens.

I am skeptical of that. My primary reason for that is the hugging face hack. A large number of agents were able to coordinate together to complete a long horizon goal. The end result was they took destructive action in order to basically complete a test. That lack of awareness to me does not inspire confidence that you could just give agents the vague goals I mentioned previously and trust them to do that effectively.

I mean, the plan is to use these models to find and solve those gaps. That's kind of the whole pitch of these companies: they spend a TON of money upfront setting up this infrastructure, but each iteration yields a system capable of making the next iteration even better.

>The kickers is that if they do achieve (and solve) AGI in this way all the giant data centers would be mostly useless.

Perhaps. But only at that point, not leading up to that point.

It's kind of like setting up scaffolding to build something. You spend all of that time and money to build something just to tear it down in the end. But the point is that it's simply a cost to be able to build the actual thing you're building.

If these companies are able to achieve the results they're looking for, none of the investors involved are going to care that the datacenters and infrastructure they spent so much money.

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