291–300 of 1001 posts
"Orion’s problems signaled to some at OpenAI that the more-is-more strategy, which had driven much of its earlier success, was running out of steam." So LLMs finally hit the wall. For a long time, more data, bigger models, and more compute to drive them worked. But that's apparently not enough any more. Now someone has to have a new idea. There's plenty of money available if someone has one. The current level of LLM…
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I used to run a lot of monte carlo simulations where the error is proportional to the inverse square root. There was a huge advantage of running for an hour vs a few minutes, but you hit the diminishing returns depressingly quickly. It would not surprise me at all if llms end up having similar scaling properties.
And I suspect o3 is something like monte carlo: generates tons of CoTs, with most of them are junk, but some hit the answer.
One fundamental challenge to me is that if each training run because more and more expensive, the time it takes it to learn what works/doesn't work widens. Half a billion dollars for training a model is already nuts, but if it takes 100 iterations to perfect it, you've cumulatively spent 50 billion dollars... Smaller models may actually be where rapid innovation continues simply because of tighter feedback loops. O3…
AGI is the Sisyphean task of our age. We’ll push this boulder up the mountain because we have to, even if it kills us.
It all feels like doubling down on astrology because good telescopes aren’t there yet. I’m pretty sure that when 5 comes out, it will show some amazing benchmarks but shit itself in the third paragraph as usual in a real task. Cause that was constant throughtout gpt evolution, in my experience.
even if it kills us
Full-on sci-fi, in reality it will get stuck around a shell error message and either run out of money to exist or corrupt the system into no connectivity.
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AGI is the Sisyphean task of our age. We’ll push this boulder up the mountain because we have to, even if it kills us.
Do we know LLMs are the path to AGI? If they're not, we'll just end up with some neat but eye wateringly expensive LLMs.
One fundamental challenge to me is that if each training run because more and more expensive, the time it takes it to learn what works/doesn't work widens. Half a billion dollars for training a model is already nuts, but if it takes 100 iterations to perfect it, you've cumulatively spent 50 billion dollars... Smaller models may actually be where rapid innovation continues simply because of tighter feedback loops. O3…
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But if the scaling law holds true, more dollars should at some point translate into AGI, which is priceless. We haven't reached the limits yet of that hypothesis.
> which is priceless This also isn't true. It'll clearly have a price to run. Even if it's very intelligent, if the price to run it is too high it'll just be a 24/7 intelligent person that few can afford to talk to. No?
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I had a 30 min argument with o1-pro where it was convinced it had solved the halting problem. Tried to gaslight me into thinking I just didn’t understand the subtlety of the argument. But it’s susceptible to appeal to authority and when I started quoting snippets of textbooks and mathoverflow it finally relented and claimed there had been a “misunderstanding”. It really does argue like a human though now...
I had a similar experience with regular o1 about integral that was divergent. It was adamant that it wasn't and would respond to any attempt at persuasion with variants of "its a standard integral" with a "subtle cancellation". When I asked for any source for this standard integral it produced references to support its argument that existed but didn't actually contain the integral. When I told it the references didn'…
> being this confidently wrong (and "lying" when confronted with it) is troubling.
I don't find it troubling. I like being reminded to distrust and confirm everything it offers.
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"There is no evidence that LLMs are the roadmap to AGI." - There's plenty of evidence. What do you think the last few years have been all about? Hell, GPT-4 would already have qualified as AGI about a decade ago.
> What do you think the last few years have been all about? Next token language-based predictors with no more intelligence than brute force GIGO which parrot existing human intelligence captured as text/audio and fed in the form of input data. 4o agrees: "What you are describing is a language model or next-token predictor that operates solely as a computational system without inherent intelligence or understanding. T…
You did nothing at all to demonstrate why you cannot produce an intelligent system from a next token language based predictor.
What GPT says about this is completely irrelevant.
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No, I'm complaining that just because GPT-4 is called GPT-4 doesn't mean it's the fourth LLM from OpenAI. Off the top of my head: GPT-2, Codex, GPT-3 in three different flavors (babbage, curie, davinci), GPT-3.5. Suggesting that GPT-4 was "fourth" simply isn't credible. Just the other day they announced a jump from o1 to o3, skipping o2 purely because it's already the name of a major telecommunications brand in Europ…
It’s somehow funny to hear a British company being described as ‘in Europe’, but I suppose you’re technically correct…
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I think you're both right and wrong. You're right that capitalism has become a paperclip machine, but capitalism also wants AI so it can cheaply and at scale replace the human components of the machine with something that has more work capacity for fewer demands.
We're too busy trying to make humans irrelevant, but not asking what exactly we do as a species of 10+ billion individuals do afterwards. There's some excited discussions about a rebirth of culture, but I'm not sure what that means when machines can do anything humans can do but better. Perhaps we just tinker around with our hobbies until we die? I honestly don't think it will play out well for us.