[dingnuts]

>> > Within thirty years, we will have the technological means to create superhuman intelligence.

> Blackwell.

I'm fucking sorry but there is no LLM or "AI" platform that is even real intelligence, today, easily demonstrated by the fact that an LLM cannot be used to create a better LLM. Go on, ask ChatGPT to output a novel model that performs better than any other model. Oh, it doesn't work? That's because IT'S NOT INTELLIGENT. And it's DEFINITELY not "superhuman intelligence." Not even close.

Sometimes accurately regurgitating facts is NOT intelligence. God it's so depressing to see commenters on this hell-site listing current-day tech as ANYTHING approaching AGI.

[frozenseven]

> Oh, it doesn't work? That's because IT'S NOT INTELLIGENT.

Ok, let's run this test of "real intelligence" on you. We eagerly await to see your model. Should be a piece of cake.

[mr_toad]

> an LLM cannot be used to create a better LLM

By that logic most humans are also not intelligent.

[mlyle]

You didn't read him correctly; he's not saying Blackwell is AGI. I believe that he's saying that perhaps Blackwell could be computationally sufficient for AGI if "used correctly."

I don't know where that "computationally sufficient" line is. It'll always be fuzzy (because you could have a very slow, but smart entity). And before we have a working AGI, thinking about how much computation we need always comes down to back of the envelope estimations with radically different assumptions of how much computational work brains do.

But I can't rule out the idea that current architectures have enough processing to do it.

[jart]

I don't use the A word, because it's one of those words that popular culture has poisoned with fear, anger, and magical thinking. I can at least respect Kurzweil though and he says the human brain has 10 petaflops. Blackwell has 20 petaflops. That would seem to make it capable of superhuman intelligence to me. Especially if we consider that it can focus purely on thinking and doesn't have to regulate a body. Imagine having your own video card that does ChatGPT but 40x smarter.

[mlyle]

I think there's a big focus on petaflops and that it may have been a good measure to think about initially, but now we're missing the mark.

If a human brain does its magic with 10 petaflops, and you have 1 petaflop, you should be able to make an equivalent to the human brain that runs at 1/10th of the speed but never sleeps. In other words, once you've reached the same order of magnitude it doesn't matter.

On the other hand, Kurzweil's math really comes down to an argument that the brain is using about 10 petaflops for inference, but it also is changing weights and doing a lot more math and optimization for training (which we don't completely understand). It may (or may not) take considerably more than 10 petaflops to train at the rate humans learn. And remember, humans take years to do anything useful.

Further, 10 petaflops may be enough math, but it doesn't mean you can store enough information or flow enough state between the different parts "of the model."

These are the big questions. If we knew the answers, IMO, we would already have really slow AGI.

[jart]

Yes I agree there's a lot of interesting problems to solve and things to learn when it comes to modeling intelligence. Vernor Vinge was smart in choosing the wording that we'd have the means to create superhuman intelligence by now, since no one's ever going to agree if we've actually achieved it.