Seems exactly like the tests at my company where even frontier models are revealed to be very expensive rubber ducks, but completely fails with non experts or anything novel or math heavy.
Ie. they mirror the intellect of the user but give you big dopamine hits that'll lead you astray.
But speaking as a specialist in theorem proving, this result is pretty impressive! It would have likely taken me a lot longer to formalize this result even if it was in my area of specialty.
How did you arrive at "ridiculous"? What we're seeing here is incredible progress over what we had a year ago. Even ARC-AGI-2 is now at over 50%. Given that this sort of process is also being applied to AI development itself, it's really not clear to me that humans would be a valuable component in knowledge work for much longer.
To me that doesn't sound qualitatively different from a PhD student. Are they just cognitive augmentation for their mentor?
In any case, I wasn't trying to argue that this system as-is is AGI, but just that it's no longer "ridiculous", and that this to me looks like a herald of AGI, as the portion being done by humans gets smaller and smaller
>The real world is not composed of rewards and punishments.
Most "AGI advocates" say that AGI is coming, sooner rather than later, and it will fundamentally reshape our world. On its own that's purely descriptive. In my experience, most of the alleged "smiting" comes from the skeptics simply being wrong about this. Rarely there's talk of explicit rewards and punishments.
To me, this sounds like when we first went to the moon, and people were sure we'd be on Mars be the end of the 80's.
> Even ARC-AGI-2 is now at over 50%.
Any measure of "are we close to AGI" is as scientifically meaningful as "are we close to a warp drive" because all anyone has to go on at this point is pure speculation. In my opinion, we should all strive to be better scientists and think more carefully about what an observation is supposed to mean before we tout it as evidence. Despite the name, there is no evidence that ARC-AGI tests for AGI.
Unlike space colonisation, there are immediate economic rewards from producing even modest improvements in AI models. As such, we should expect much faster progress in AI than space colonisation.
But it could still turn out the same way, for all we know. I just think that's unlikely.
I work at an insurance company and I can’t see AI replacing even 10% of the employees here. Too much of what we do is locked up in decades-old proprietary databases that cannot be replaced for legal reasons. We still rely on paper mail for a huge amount of communication with policyholders. The decisions we make on a daily basis can’t be trusted to AI for legal reasons. If AI caused even a 1% increase in false rejections of claims it would be an enormous liability issue.
And regarding your example of an insurance company, I'm not sure about that industry, but seeing the transformation of banking over the last decade to fully digital providers like Revolut, I would expect similar disruption there.
As for a bet, yes, I'd really be happy to put my money where my mouth is, if you're familiar with any long bets platform that accepts pseudonymous users.
[0] https://www.cnbc.com/2025/12/08/waymo-paid-rides-robotaxi-te...
Ai runs on computers. Consider the undecidability of Rices theorem. Where compiled code of non trivial statements may or may not be error free. Even an ai can’t guarantee its compiled code is error free. Not because it wouldn’t write sufficient code that solves a problem, but the code it writes is bounded by other externalities. Undecidability in general makes the dream of generative ai considerably more challenging than how it’s being ‘sold.
You don’t even need AGI for that though, just unbounded investor enthusiasm and a regulatory environment that favors AI providers at the expense of everyone else.
My point is there are number of things that can cause large scale unemployment in the next 20 years and it doesn’t make sense to worry about AGI specifically while ignoring all of the other equally likely root causes (like a western descent into oligarchy and crony capitalism, just to name one).
Recent case:
I have a bar with a number of weights supported on either end:
|---+-+-//-+-+---|
What order and/or arrangement or of removing the weights would cause the least shift in center-of-mass? There is a non-obvious trick that you can pull here to reduce the shift considerably and I was curious if the AI would spot it or not but even after lots of prompting it just circled around the obvious solutions rather than to make a leap outside of that box and come up with a solution that is better in every case.
I wonder what the cause of that kind of blindness is.
There is a starting node (L_0, R_0, {}) and an ending node ({}, {}, W) , with the latter having L=R={}.
I think you're trying to find the path (L_n, R_n, S_n) from the starting node to the ending node that minimises the maximum absolute value of c(L_n, R_n, S_n).
I won't post a solution, as requested.
My guess is: first move the weights to the middle, and only then remove them.
However “weights” and “bar” might confuse both machines and people into thinking that this is related to weight lifting, where there’s two stops on the bar preventing the weights from being moved to the middle.
And no, the problem is not 'not clearly stated'. It is complete as it is and you are wrong about your guess.
And if machines and people think this is related to weight lifting then they're free to ask follow up questions. But even in the weight lifting case the answer is the same.
Yeah, LLMs have a tendency to run with some interpretation of a question without asking follow-up questions. Probably, it's a consequence of RLHFing them in that way.
If you do solve it don't post the answer.
You didn't even label your ASCII art, so I've no clue what you mean, are the bars at the end the supports or weights? Can I only remove one weight at a time? Initially I assumed you mean a weightlifting bar the weights on which can only be removed from its ends. Is that the case or what? What's the double slash in the middle?
Also: "what order and/or arrangement or of removing the weights" this isn't even correct English. Arrangement of removing the weights? State the problem clearly, from first principles, like you were talking to a 5 year old.
The sibling comment is correct, you're clearly picturing something in your mind that you're failing to properly describe. It seems obvious to you, but it's not.
I can successfully interpret total gibberish sometimes, but that’s not a robust approach even with humans let alone machines.
People have wildly different experiences utilising AI because of their own idiosyncrasies more than issues with the tools themselves.
It was pointed out by multiple groups (such as Anthropic) that their tools do a lot better with well organised codebases that are liberally commented.
I’ve worked on codebases where the AIs are just… lost. So are people!
Sure, some people can navigate the spaghetti… sometimes… but the success rate of changes is much lower.
Occasional success is not proof of correctness of approach. Consistent success is.
This hits so true to home. Just today in my field a manager without expertise in a topic gave me an AI solution to something I am an expertise in. The AI was very plainly and painfully wrong, but it comes down to the user prompting really poorly. When I gave a el formulated prompt to the same topic, I got the correct answer on the first go.
"Aristotle integrates three main components: a Lean proof search system, an informal reasoning system that generates and formalizes lemmas, and a dedicated geometry solver"
Not saying it's not an amazing setup, i just don't understand the word "AI" being used like this when it's the setup / system that's brilliant in conjunction with absolute experts.
https://en.wikipedia.org/wiki/Dartmouth_workshop
AI != AGI != neural networks != LLMs
But Tao did mention ChatGPT so i believe LLMs were involved at least partially.
> There seems to be some confusion on this so let me clear this up. No, after the model gave its original response, I then proceeded to ask it if it could solve the problem with C=k/logN arbitrarily large. It then identified for itself what both I and Tao noticed about it throwing away k!, and subsequently repaired its proof. I did not need to provide that observation.
so it was literally "yo, your proof is weak!" - "naah, watch this! [proceeds to give full proof all on its own]"
I'd say that counts