Advancing AI Benchmarking with Game Arena
(blog.google)89 points by salkahfi 6 hours ago
89 points by salkahfi 6 hours ago
Cool to see core war! I feel it's mostly forgotten by now. My dad is still playing it to this day though and even attends tournaments
Let's add NetHack to the mix!
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).
Isn't this a bit too visual-centric? By this criterion Helen Keller, author of 14 books, would not be generally intelligent.
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).
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
Its the same reason we are asked to write exams without using calculators but the real world does have them.
How you work without calculators is a proxy for real world competency.
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.
are you in favour of children using calculators in exams?
CoT is upstream of building a chess engine.
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.
For reference for anyone who missed it, the 2021 NetHack challenge results: https://nethackchallenge.com/report.html
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.
Gemini tops all benchmarks but when it comes to real world usage it is genuinely unusable
It's legit good at visual stuff. It's not just a great agent and does some weird stuff sometimes.
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?
Oddly in the highlighted game I watched the werewolf simply gives up in the last round and says I'm the werewolf well-done... Vote me.
Bizarre.
confidently and charismatically lying to clueless users has been one of fundaments of AI adoption
Anecdotal data point, but recently I’ve found Gemini to perform better than ChatGPT when it came to intent analysis.
making models target benchmark about being good at lying and getting away with it (werewolf) is certainly an interesting choice
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.
https://codeclash.ai/