Each LLM is given the same 1000 chess puzzles to solve. See puzzles.csv. Benchmarked on Mar 25, 2024.
| Model | Solved | Solved % | Illegal Moves | Illegal Moves % | Adjusted Elo |
|---|---|---|---|---|---|
| gpt-4-turbo-preview | 229 | 22.9% | 163 | 16.3% | 1144 |
| gpt-4 | 195 | 19.5% | 183 | 18.3% | 1047 |
| claude-3-opus-20240229 | 72 | 7.2% | 464 | 46.4% | 521 |
| claude-3-haiku-20240307 | 38 | 3.8% | 590 | 59.0% | 363 |
| claude-3-sonnet-20240229 | 23 | 2.3% | 663 | 66.3% | 286 |
| gpt-3.5-turbo | 23 | 2.3% | 683 | 68.3% | 269 |
| claude-instant-1.2 | 10 | 1.0% | 707 | 66.3% | 245 |
| mistral-large-latest | 4 | 0.4% | 813 | 81.3% | 149 |
| mixtral-8x7b | 9 | 0.9% | 832 | 83.2% | 136 |
| gemini-1.5-pro-latest* | FAIL | - | - | - | - |
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Of course they are bad at solving problems. The I in LLM stands for intelligence.
(Credit: https://daniel.haxx.se/blog/2024/01/02/the-i-in-llm-stands-for-intelligence/)
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People thinking LLMs should be even serviceable at chess didn’t understand LLMs. They really aren’t problem solving applications. They’re optimized for making responses to questions that look like what a response should look like, not for being accurate. That’s really clear if you ask them for mathematical proofs. They will generate proofs that look like the right sort of thing, but they won’t be correct unless they have the specific proof in their training data.
This is obvious for people who understand the basics of LLM. However, people are fooled by how intelligent these LLM sounds, so they mistake it for actually being intelligent. So, even if this is an open door, I still think it’s good someone is kicking it in to make it clear that llms are not generally intelligent.
Agreed, it’s good to have these kinds of articles so people get a better feel for what tools like this are and aren’t.
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Are you going to share any of your wisdom here? Or rebut misinformation?
Not well, apparently.
I wonder how many of the ones they “solved” were just because they’d seen it discussed somewhere in the data set, considering the puzzles are apparently from a public resource.
Yeah, I don’t know why anyone knowledgeable would expect them to be good at chess. LLMs don’t generalise, reason or spot patterns, so unless they read a chess book where the problems came from…
Likely close to 100%. If you read the (rather good) article, a little further down they test whether the LLM can play an extremely simplistic “Connect 4” game they devise, as a way of narrowing down on specifically reasoning capabilities.
It cannot.
Chess puzzles, in particular, are frequently shared and discussed in online chess spaces, so the LLM will have a significant amount of material to work with when it tries to predict the best response to give to the prompt.
I didn’t figure. I’m sure they could be taught to be much better, but normal computing can already play chess more or less perfectly. There really isn’t much any room left to be gained.
This has more to do with how much chess data was fed into the model than any kind of reasoning ability. A 50M model can learn to play at 1500 elo with enough training: https://adamkarvonen.github.io/machine_learning/2024/01/03/chess-world-models.html
I’m actually a bit surprised they got any of them right. Maybe the ones they solved correctly had exact matches in their training data . . . ?
This to me shows that LLM simply isn’t trustworthy, it’s one thing it can’t solve a puzzle, fair enough. But that it uses illegal moves is kind of alarming.
This is a relatively simple task, so this proves that LLM isn’t trustworthy even for simple tasks.
That said, I still think LLM is an impressive technology, but I’d be very careful relying on it for anything. The fact that some companies already use them for customer support gives me horror goosebumps.I wonder why gpt-4 is so good at chess.
If I tried to make an illegal move 20% of the time, would you also say I am good at chess?
Depends on circumstances, obviously.
Okay. What if the circumstance is because I’m just recalling a bunch of chess puzzle solutions I’ve seen before and regurgitating the one I think is the correct solution for this particular pizzle without really understanding the rules of chess?
That’s another thing I’m wondering about, but so is anyone. I’d still want to know why GPT-4 does so much better than the others.
