5 ms·

Meanwhile even the highest ranked models can’t do simple logic tasks. GothamChess on YouTube did some tests where he played against a bunch of the best models a

Meanwhile even the highest ranked models can’t do simple logic tasks. GothamChess on YouTube did some tests where he played against a bunch of the best models and every single one of them failed spectacularly. They’d happily lose a queen to take a pawn. They failed to understand how pieces are even allowed to move, hallucinated the existence of new pieces, repeatedly declared checkmate when it wasn’t, etc. I tried it last night with Gemini 2.5 Pro and it made it 6 turns before it started making illegal moves, and 8 turns before it got so confused about the state of the board before it refused to play with me any longer. I was in the chess club in 3rd grade. One of the top ranked LLMs in the world is vastly dumber than I was in 3rd grade. But we’re going to pour hundreds of billions into this in the hope that it can end my career? Good luck with that, guys.

schindlabua 1y ago
Chess is not exactly a simple logic task. It requires you to keep track of 32 things in a 2d space. I remember being extremely surprised when I could ask GPT3 to rotate a 3d model of a car in it's head and ask it about what I would see when sitting inside, or which doors would refuse to open because they're in contact with the ground. It really depends on how much you want to shift the goalposts on what constitutes "simple".
- yusina 1y ago
  > Chess is not exactly a simple logic task. Compare to what a software engineer is able to do, it is very much a simple logic task. Or the average person having a non-trivial job. Or a beehive organizing its existence, from its amino acids up to hive organization. All those things are magnitudes harder than chess. > I remember being extremely surprised when I could ask GPT3 to rotate a 3d model of a car in it's head and ask it about what I would see when sitting inside, or which doors would refuse to open because they're in contact with the ground. It's not reasoning its way there. Somebody asked something similar some time in the corpus and that corpus also contained the answers. That's why it can answer. After a quite small number of moves, the chess board it unique and you can't fake it. You need to think ahead. A task which computers are traditionally very good at. Even trained chess players are. That LLMs are not goes to show that they are very far from AGI.
famouswaffles 1y ago
LLMs can play chess fine. The best model you can play with is decent for a human - https://github.com/adamkarvonen/chess_gpt_eval https://github.com/adamkarvonen/chess_gpt_eval SOTA models can't play it because these companies don't really care about it.
JFingleton 1y ago
I'm not sure why people are expecting a language model to be great at chess. Remember they are trained on text, which is not the best medium for representing things like a chess board. They are also "general models", with limited training on pretty much everything apart from human language. An Alpha Star type model would wipe the floor at chess.
- actsasbuffoon 1y ago
  This misses the point. LLMs will do things like move a knight by a single square as if it were a pawn. Chess is an extremely well understood game, and the rules about how things move is almost certainly well-represented in the training data. These models cannot even make legal chess moves. That’s incredibly basic logic, and it shows how LLMs are still completely incapable of reasoning or understanding. Many kinds of task are never going to be possible for LLMs unless that changes. Programming is one of those tasks.
  - simonw 1y ago
    Saying programming is a task that is "never going to be possible" for an LLM is a big claim, given how many people have derived huge value from having LLMs write code for them over the past two years. (Unless you're arguing against the idea that LLMs are making programmers obsolete, in which case I fully agree with you.)
    - sceptic123 1y ago
      I think "useful as an assistant for coding" and "being able to program" are two different things. When I was trying to understand what is happening with hallucination GPT gave me this: > It's called hallucinating when LLMs get things wrong because the model generates content that sounds plausible but is factually incorrect or made-up—similar to how a person might "see" or "experience" things that aren't real during a hallucination. From that we can see that they fundamentally don't know what is correct. While they can get better at predicting correct answers, no-one has explained how they are expected to cross the boundary from "sounding plausible" to "knowing they are factually correct". All the attempts so far seem to be about reducing the likelihood of hallucination, not fixing the problem that they fundamentally don't understand what they are saying. Until/unless they are able to understand the output enough to verify the truth then there's a knowledge gap that seems dangerous given how much code we are allowing "AI" to write.
code_biologist 1y ago
Claude can't beat Pokemon Red. Not even close yet: https://arstechnica.com/ai/2025/03/why-anthropics-claude-still-hasnt-beaten-pokemon/ https://arstechnica.com/ai/2025/03/why-anthropics-claude-sti...

schindlabua 1y ago

Chess is not exactly a simple logic task. It requires you to keep track of 32 things in a 2d space. I remember being extremely surprised when I could ask GPT3 to rotate a 3d model of a car in it's head and ask it about what I would see when sitting inside, or which doors would refuse to open because they're in contact with the ground. It really depends on how much you want to shift the goalposts on what constitutes "simple".

yusina 1y ago
> Chess is not exactly a simple logic task. Compare to what a software engineer is able to do, it is very much a simple logic task. Or the average person having a non-trivial job. Or a beehive organizing its existence, from its amino acids up to hive organization. All those things are magnitudes harder than chess. > I remember being extremely surprised when I could ask GPT3 to rotate a 3d model of a car in it's head and ask it about what I would see when sitting inside, or which doors would refuse to open because they're in contact with the ground. It's not reasoning its way there. Somebody asked something similar some time in the corpus and that corpus also contained the answers. That's why it can answer. After a quite small number of moves, the chess board it unique and you can't fake it. You need to think ahead. A task which computers are traditionally very good at. Even trained chess players are. That LLMs are not goes to show that they are very far from AGI.

famouswaffles 1y ago

LLMs can play chess fine. The best model you can play with is decent for a human - https://github.com/adamkarvonen/chess_gpt_eval https://github.com/adamkarvonen/chess_gpt_eval SOTA models can't play it because these companies don't really care about it.

JFingleton 1y ago

I'm not sure why people are expecting a language model to be great at chess. Remember they are trained on text, which is not the best medium for representing things like a chess board. They are also "general models", with limited training on pretty much everything apart from human language. An Alpha Star type model would wipe the floor at chess.

actsasbuffoon 1y ago
This misses the point. LLMs will do things like move a knight by a single square as if it were a pawn. Chess is an extremely well understood game, and the rules about how things move is almost certainly well-represented in the training data. These models cannot even make legal chess moves. That’s incredibly basic logic, and it shows how LLMs are still completely incapable of reasoning or understanding. Many kinds of task are never going to be possible for LLMs unless that changes. Programming is one of those tasks.
- simonw 1y ago
  Saying programming is a task that is "never going to be possible" for an LLM is a big claim, given how many people have derived huge value from having LLMs write code for them over the past two years. (Unless you're arguing against the idea that LLMs are making programmers obsolete, in which case I fully agree with you.)
  - sceptic123 1y ago
    I think "useful as an assistant for coding" and "being able to program" are two different things. When I was trying to understand what is happening with hallucination GPT gave me this: > It's called hallucinating when LLMs get things wrong because the model generates content that sounds plausible but is factually incorrect or made-up—similar to how a person might "see" or "experience" things that aren't real during a hallucination. From that we can see that they fundamentally don't know what is correct. While they can get better at predicting correct answers, no-one has explained how they are expected to cross the boundary from "sounding plausible" to "knowing they are factually correct". All the attempts so far seem to be about reducing the likelihood of hallucination, not fixing the problem that they fundamentally don't understand what they are saying. Until/unless they are able to understand the output enough to verify the truth then there's a knowledge gap that seems dangerous given how much code we are allowing "AI" to write.

code_biologist 1y ago

Claude can't beat Pokemon Red. Not even close yet: https://arstechnica.com/ai/2025/03/why-anthropics-claude-still-hasnt-beaten-pokemon/ https://arstechnica.com/ai/2025/03/why-anthropics-claude-sti...