I don't care if it's "intelligent", I don't care if it "has a mind". I don't care if it is "really reasoning", I don't care if it "understands". I don't care if it is "sentient" or "conscious".
None of this matters for the practical outcome.
You'd think that this has been understood over the last 4 years, but apparently it keeps circling back to this.
[Edit: I see that it was written back in 2023. Then (2023) should be added in the submission title]
If it generates functional output that works, then it works. And it works. It's not a psychic's con when it outputs Lean-verified proofs. It isn't a con when it can find and exploit zero-days.
The OP is still in the "denial" phase. Most I see are already in "anger" (a blurry fury against everything AI-shaped, from vague reasons piling on all "bad stuff" political reasons they already hated before) or "bargaining" (mathematicians scrambling to come up with a new definition of their job and retcon that it was always the main part anyway). A few are already in "depression" and feel like spectators on the Titanic, and the tiniest sliver is at "acceptance" with some kind of well-informed plan for their future.
> The OP is still in the "denial" phase.
This was written in July 2023. ChatGPT was released November 2022. No matter your views on AI, surely you can't blame the OP for writing this after a few months ChatGPT was released.
Despite the fact that I'm not culturally or geographically connected to them at all and have some differences in taste and aesthetic, I have to conclude that this crowd, including him and Gwern etc. have been much better at understanding and predicting things than the expert takes you find in the media. That includes AI but also things like covid and others.
I’m not seeing anything like a falsifiable prediction that LLMs will write math proofs in that article.
I see a thought experiment about giving GPT-2 “near-infinite training data and [compute]” but that’s not falsifiable. That’s also not how we got to modern GPT models.
The context shows he was simply whining about AGI skeptics back in 2018, and many of the “predictions” he makes in that paragraph (including the one you quoted) are trivially wrong because he phrased them so hyperbolically and categorically.
Anyway, there were plenty of normies who thought images generated by e.g. stable diffusion (c. 2022) was “real art” and equivalent to human artwork.
I don’t think it’s useful to glaze Scott (or any of the LW crowd for that matter) as if he was (or they were) some kind of prophet(s). They got a couple points right, sure, but most of it was them flinging armchair philosophy spaghetti against the wall and seeing who would fund MIRI to let them fling the next batch.
He's pretty clearly saying he beilieves the technology capable of such a feat, at least in theory, which is far more than many would deign to admit even a year ago, nevermind 7. He had the right idea/model of LLM capabilities, which is more than you could say for a lot of people, even in this very thread.
If that’s your standard for what counts as prediction, Asimov beat him to it by seventy-ish years.
EDIT:
> Scott made comments on a specific emerging technology
He was speculating on what would happen if one gave GPT-2 “near-infinite training data and compute.” It’s a thought experiment, not a prediction. Near-infinite amounts of anything is a fantasy.
I acknowledge that he has predicted some things in a falsifiable way and turned out correct, but this isn’t one of them. You’re reading hindsight into the text.
1. Asimov wrote science fiction stories. As far as his robots were concerned, he did not make any comments on the possible future direction/capabilities of any specific technology at the time. This meant he could imagine his robots however he wanted for his fictional world. Scott made comments on a specific emerging technology - You can imagine math proof writing robots but be unconvinced they could emerge from Generative Pre-trained Transformers.
2. The genre is alternatively called speculative fiction for a reason. Yes, some sci-fi works do count as predictions especially when hinged on concrete emerging technologies.
>I acknowledge that he has predicted some things in a falsifiable way and turned out correct, but this isn’t one of them. You’re reading hindsight into the text.
I read that blog years ago. Believe me, my opinions are not hindsight.
>Incorrect. He was speculating on what would happen if one gave GPT-2 “near-infinite training data and compute.” It’s a thought-experiment, not a prediction. Near-infinite amounts of anything is a fantasy.
Thought experiments can generate predicitons. His claim was essentially: If you scale data and compute sufficiently, this technology can learn enough of the underlying structure of mathematics to write proofs.
This is meaningful when others around you are saying this is a dead end and that the technology is fundamentally incapable of this regardless of degree of investment and scaling. It shows a much better calibrated sense of the potential of the architecture than those who said otherwise.
If your objection is that "near infinite" makes it insufficiently quantitative to count as a falsifiable forecast, then fine. But at that point we're mostly arguing over what deserves the label "prediction" rather than whether Scott correctly identified an important capability the architecture could develop.
And i'm not trying to say this makes Scott (or the lesswrong crowd) geniuses.
bonoboTP · · focus · HN ↗
None of this matters for the practical outcome.
You'd think that this has been understood over the last 4 years, but apparently it keeps circling back to this.
[Edit: I see that it was written back in 2023. Then (2023) should be added in the submission title]
If it generates functional output that works, then it works. And it works. It's not a psychic's con when it outputs Lean-verified proofs. It isn't a con when it can find and exploit zero-days.
The OP is still in the "denial" phase. Most I see are already in "anger" (a blurry fury against everything AI-shaped, from vague reasons piling on all "bad stuff" political reasons they already hated before) or "bargaining" (mathematicians scrambling to come up with a new definition of their job and retcon that it was always the main part anyway). A few are already in "depression" and feel like spectators on the Titanic, and the tiniest sliver is at "acceptance" with some kind of well-informed plan for their future.
zkry · · focus · HN ↗
This was written in July 2023. ChatGPT was released November 2022. No matter your views on AI, surely you can't blame the OP for writing this after a few months ChatGPT was released.
bananaflag · · focus · HN ↗
<a href="https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-general-intelligence/" rel="nofollow">https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-g...
Of course people were skeptical:
<a href="https://www.reddit.com/r/slatestarcodex/comments/aslze7/gpt2_as_step_toward_general_intelligence/" rel="nofollow">https://www.reddit.com/r/slatestarcodex/comments/aslze7/gpt2...
bonoboTP · · focus · HN ↗
sheafification · · focus · HN ↗
I see a thought experiment about giving GPT-2 “near-infinite training data and [compute]” but that’s not falsifiable. That’s also not how we got to modern GPT models.
bananaflag · · focus · HN ↗
"If AI can generate images and even stories to a prompt, everyone will agree this is totally different from real art or storytelling."
<a href="https://slatestarcodex.com/2018/02/15/five-more-years/" rel="nofollow">https://slatestarcodex.com/2018/02/15/five-more-years/
sheafification · · focus · HN ↗
Anyway, there were plenty of normies who thought images generated by e.g. stable diffusion (c. 2022) was “real art” and equivalent to human artwork.
I don’t think it’s useful to glaze Scott (or any of the LW crowd for that matter) as if he was (or they were) some kind of prophet(s). They got a couple points right, sure, but most of it was them flinging armchair philosophy spaghetti against the wall and seeing who would fund MIRI to let them fling the next batch.
bananaflag · · focus · HN ↗
famouswaffles · · focus · HN ↗
sheafification · · focus · HN ↗
EDIT:
> Scott made comments on a specific emerging technology
He was speculating on what would happen if one gave GPT-2 “near-infinite training data and compute.” It’s a thought experiment, not a prediction. Near-infinite amounts of anything is a fantasy.
I acknowledge that he has predicted some things in a falsifiable way and turned out correct, but this isn’t one of them. You’re reading hindsight into the text.
famouswaffles · · focus · HN ↗
2. The genre is alternatively called speculative fiction for a reason. Yes, some sci-fi works do count as predictions especially when hinged on concrete emerging technologies.
watwut · · focus · HN ↗
famouswaffles · · focus · HN ↗
I read that blog years ago. Believe me, my opinions are not hindsight.
>Incorrect. He was speculating on what would happen if one gave GPT-2 “near-infinite training data and compute.” It’s a thought-experiment, not a prediction. Near-infinite amounts of anything is a fantasy.
Thought experiments can generate predicitons. His claim was essentially: If you scale data and compute sufficiently, this technology can learn enough of the underlying structure of mathematics to write proofs.
This is meaningful when others around you are saying this is a dead end and that the technology is fundamentally incapable of this regardless of degree of investment and scaling. It shows a much better calibrated sense of the potential of the architecture than those who said otherwise.
If your objection is that "near infinite" makes it insufficiently quantitative to count as a falsifiable forecast, then fine. But at that point we're mostly arguing over what deserves the label "prediction" rather than whether Scott correctly identified an important capability the architecture could develop.
And i'm not trying to say this makes Scott (or the lesswrong crowd) geniuses.