This is a good way to benchmark models. We [the SWE-bench team] took the meta-version of this and implemented it as a new benchmark called CodeClash -
We have agents implement agents that play games against each other- so Claude isn't playing against GPT, but an agent written by Claude plays poker against an agent written by GPT, and this really tough task leads to very interesting findings on AI for coding.
I'd really like to see them add a complex open world fully physicalized game like Star Citizen (assuming the game itself is stable) with a single primary goal like accumulating currency as a measure of general autonomy and a proxy for how the model might behave in the real world given access to a bipedal robot.
My personal threshold for AGI is when an AI can 'sit down' - it doesn't need to have robotic hands, but it needs to only use visual and audio inputs to make its moves - and complete a modern RPG or FPS single player game that it hasn't pre-trained on (it can train on older games).
It could have hands that feel but no vision, I think they were getting at that they thought embodiment and playing games in the modality of humans, without thousands of hours of play to reach competency, would be an important milestone.
If AI can program, why does it matter if it can play Chess using CoT when it can program a Chess Engine instead? This applies to other domains as well.
It can write a chess engine because it has read the code of a thousand of chess engines. This benchmark measures a different aspect of intelligence.
And as a poker player, I can say that this game is much more challenging for computers than chess, writing a program that can play poker really well and efficiently is an unsolved problem.
> If AI can program, why does it matter if it can play Chess using CoT when it can program a Chess Engine instead?
Heh, we really did come full circle on this! When chatgpt launched in dec22 one of the first things that people noticed is that it sucked at math. Like basic math 12 + 35 would trip it up. Then people "discovered" tool use, and added a calculator. And everyone was like "well, that's cheating, of course it can use a calculator, but look it can't do the simple addition logic"... And now here we are :)
IMO there's an expectation for baseline intelligence. I don't expect an "AGI" model to beat Magnus Carlsen out of the box but it should be able to do basic grade school level arithmetic and play chess at a complete beginner level without resorting to external tools.
I'm not going to respond to everything but the key to my comment was "This applies to other domains as well." But people are limiting their imagination to the chess engine example given for chess. The tool or program (or even other neural networks that are available) can be literally anything for any task... Use your imagination.
Maybe we should just get rid of tedious benchmarks like chess altogether at this point that is leading people to think of how to limit AI as a way of keeping it a relevant benchmark rather than expanding on what is already there.
They should be allowed to! In fact i think better benchmark would be to invent new games and test the models ability to allocate compute to minmax/alphazero new games in compute constraints
A lot of the insights of math come from knowing how to do things efficiently. That’s why the tests are timed. I don’t know, this is pretty basic pedagogy that you are choosing to grief.
It is a program. I need it to get task X done and I don't care how, whether it is strictly through CoT or with tools. There is no such thing as cheating in real work and no reason to handicap it. Just test the limits of what it can do with whatever means possible.
Trying to solve everything with CoT alone without utilising tools seems futile.
That was a whole half a decade ago, but back then deep learning AIs were defeated very badly by handcrafted scripts. Even the best bot in the neural net category was actual a symbolic script/neural net hybrid.
Poker has very high variance, you'd need several hundred thousand hands to confidently say who's better. Also, you probably want to precompute the GTO-optimal play for benchmarking purposes.
It’s not that bad. I’ve been using 3 Pro for some time now and I’m quite happy with how it works. Best paired with Opus and Codex, like most models, but it’s solid as a full-stack buddy.
Wow. I'm generally in the AI maximalist camp. But adding Werewolf feels dangerous to me. Anyone who's played knows lying, deceipt, and manipulation is often key to winning. We really want models climbing this benchmark?
We have agents implement agents that play games against each other- so Claude isn't playing against GPT, but an agent written by Claude plays poker against an agent written by GPT, and this really tough task leads to very interesting findings on AI for coding.
https://codeclash.ai/
Are you going to share those with the class or?
?
https://kenforthewin.github.io/blog/posts/nethack-agent/
Ultimately I think it's impossible to define AGI. Maybe "I know it when I see it"—except everyone sees it at a different point (evidently).
And as a poker player, I can say that this game is much more challenging for computers than chess, writing a program that can play poker really well and efficiently is an unsolved problem.
It doesn't even need to be one tool but a series of tools.
Heh, we really did come full circle on this! When chatgpt launched in dec22 one of the first things that people noticed is that it sucked at math. Like basic math 12 + 35 would trip it up. Then people "discovered" tool use, and added a calculator. And everyone was like "well, that's cheating, of course it can use a calculator, but look it can't do the simple addition logic"... And now here we are :)
Maybe we should just get rid of tedious benchmarks like chess altogether at this point that is leading people to think of how to limit AI as a way of keeping it a relevant benchmark rather than expanding on what is already there.
How you work without calculators is a proxy for real world competency.
Trying to solve everything with CoT alone without utilising tools seems futile.
Chess engines don’t grow on trees, they’re built by intelligent systems that can think, namely human brains.
Supposedly we want to build machines that can also think, not just regurgitate things created by human brains. That’s why testing CoT is important.
It’s not actually about chess, it’s about thinking and intelligence.
That was a whole half a decade ago, but back then deep learning AIs were defeated very badly by handcrafted scripts. Even the best bot in the neural net category was actual a symbolic script/neural net hybrid.
Bizarre.
AI already has a very creative imagination for role play so this just adds extra to their arsenal.