8 ms·
Watching o3 model sweat over a Paul Morphy mate-in-2
- awestroke 1y agoO3 is massively underwhelming and is obviously tuned to be sycophantic. Claude reigns supreme.
- omneity 1y agoThis somehow reminds me of Agent-3 from [0]. 0: https://ai-2027.com https://ai-2027.com
- tomduncalf 1y agoDepends on the task I think. O3 is really effective at going off and doing research, try giving it a complex task which involves lots of browsing/searching and watch how it behaves. Claude cannot do anything like that right now. I do find O3’s tone of voice a bit odd
- tough 1y agoI've commited the 03 (zero-three) and not o3 (o-three) typo too, but can we rename it on the title please
- dang 1y agoFixed. Thanks!
- sMarsIntruder 1y agoSo, are we talking about OpenAI o3 model, right?
- alexop 1y agoyes
- bcraven 1y ago>"When I gave OpenAI’s 03 model a tough chess puzzle..." Opening sentence
- monktastic1 1y agoA little annoying that they use zero instead of o, but yeah.
- janaagaard 1y agoI was also confused. It looks like the article has been corrected, and now uses the familiar 'o3' name.
- freediver 1y agoOn a similar note, I just updated LLM Chess Puzzles repo [1] yesterday. The fact that gpt-4.5 gets 85% correctly solved is unexpected and somewhat scary (if model was not trained on this). [1] https://github.com/kagisearch/llm-chess-puzzles https://github.com/kagisearch/llm-chess-puzzles
- alexop 1y agoOh cool, I wonder how good 03 will be. While using 03, I noticed something funny: sometimes I gave it a screenshot without any position data. It ended up using Python and spent 10 minutes just trying to figure out where the figures were exactly.
- Gimpei 1y agoGiven that o3 is trained on the contents of the Internet, and the answers to all these chess problems are almost certainly on the Internet in multiple places, in a sense it has been weakly trained on this content. The question for me becomes: is the LLM doing better on these problems because it’s improving in reasoning, or is it simply improving in information retrieval.
- globnomulous 1y agoAnd then there's the further question of where we draw the line in ourselves. One of my teachers -- a philosopher -- once said that real, actual thought is incredibly rare. He's a world-renowned expert but says he can count on one hand the number of times in his life that he felt he was thinking rather than remembering and reorganizing what he already knew. That's not to say "are you remembering or reasoning" means the same thing when applied to humans vs when it's applied to LLMs.
- bluefirebrand 1y ago> One of my teachers -- a philosopher -- once said that real, actual thought is incredibly rare Probably should listen to psychologists and neuroscientists about this, not philosophers tbh
- ttoinou 1y agoWhere does this obsession over giving binary logic tasks to LLMs come from ? New LLM breakthroughs are about handling blurry logic, non precise requirements and spitting vague human realistic outputs. Who care how well it can add integers or solve chess puzzles ? We have decades of computer science on those topics already
- tgtweak 1y agoI remember reading that got3.5-turbo instruct was oddly good at chess - would be curious what it outputs as a next two moves here.
- deleted 1y ago[deleted]
- Kapura 1y agoSo... it failed to solve the puzzle? That seems distinctly unimpressive, especially for a puzzle with a fixed start state and a limited set of possible moves.
- IanCal 1y ago> That seems distinctly unimpressive I cannot understate how impressive this is to me, having been involved in ai research projects and robotics in years gone by. This is a general purpose model, given an image and human written request that then step by step analyses the image, iterates through various options, tries to write code to solve the problem and then searches the internet for help. It reads multiple results and finds an answer, checks to validate it and then comes back to the user. I had a robot that took ages to learn to plan tic tac toe by example and if the robot moved originally there was a solid chance it thought the entire world had changed and would freak out because it thought it might punch through the table. This is also a chess puzzle marked as very hard that a person who is good at chess should give themselves fifteen minutes to solve. The author of the chess.com blog containing this puzzle only solved about half of them! This is not an image analysis bot, it's not a chess bot, it's a general system I can throw bad english at.
- alexop 1y agoYes, I agree. Like I said, in the end it did what a human would do: google for the answer. Still, it was interesting to see how the reasoning unfolded. Normally, humans train on these kinds of puzzles until they become pure pattern recognition. That's why you can't become a grandmaster if you only start learning chess as an adult — you need to be a kid and see thousands of these problems early on, until recognizing them becomes second nature. It's something humans are naturally very good at.
- kamranjon 1y agoI am a human and I figured this puzzle out in under a minute by just trying the small set of possible moves until I got it correct. I am not a serious chess player. I would have expected it to at least try the possible moves? I think this maybe lends credence to the idea that these models aren’t actually reasoning but are doing a great job of mimicking what we think humans do.
- BXLE_1-1-BitIs1 1y agoNice puzzle with a twist of Zugzwang. Took me about 8 minutes, but it's been decades since I was doing chess.
- bfung 1y agoLLMs are not chess engines, similar to how they don’t really calculate arithmetic. What’s new? carry on.
- triyambakam 1y agoYeah it's rather annoying how people (maybe due to marketing) expect a generalized model to be able to be an expert in every domain.
- foundry27 1y agoI just tried the same puzzle in o3 using the same image input, but tweaked the prompt to say “don’t use the search tool”. Very similar results! It spent the first few minutes analyzing the image and cross-checking various slices of the image to make sure it understood the problem. Then it spent the next 6-7 minutes trying to work through various angles to the problem analytically. It decided this was likely a mate-in-two (part of the training data?), but went down the path that the key to solving the problem would be to convert the position to something more easily solvable first. At that point it started trying to pip install all sorts of chess-related packages, and when it couldn’t get that to work it started writing a simple chess solver in Python by hand (which didn’t work either). At one point it thought the script had found a mate-in-six that turned out to be due to a script bug, but I found it impressive that it didn’t just trust the script’s output - instead it analyzed the proposed solution and determined the nature of the bug in the script that caused it. Then it gave up and tried analyzing a bit more for five more minutes, at which point the thinking got cut off and displayed an internal error. 15 minutes total, didn’t solve the problem, but fascinating! There were several points where if the model were more “intelligent”, I absolutely could see it reasoning it out following the same steps.
- IanCal 1y agoTold that it was a mate in 2 puzzle, and it solved it for me https://chatgpt.com/share/680f4a02-4cc4-8002-8301-59214fca7813 https://chatgpt.com/share/680f4a02-4cc4-8002-8301-59214fca78... It worked through some stuff then decided to try and list all possible moves as there can't be that many. Tried importing stuff that didn't work, then wrote code to create the permutations.
- bko 1y agoClaude gets the right answer but misplaces the pieces in its initial analysis which means the answer is incorrect. Whats going on? Did it just get lucky? Did it memorize the answer but misplace the pieces in its recall? Did it actually compute anything? https://claude.ai/share/d640bc4c-8dd8-4eaa-b10b-cb3f83a6b94b https://claude.ai/share/d640bc4c-8dd8-4eaa-b10b-cb3f83a6b94b This is the board as it sees it (incorrect): https://lichess.org/editor/kb6/pp6/2P5/8/8/3K4/8/R7_w_-_-_0_1?color=white https://lichess.org/editor/kb6/pp6/2P5/8/8/3K4/8/R7_w_-_-_0_...
- bitbasher 1y agoIs this that impressive considering these models have probably been trained on numerous books/texts analyzing thousands of games (including morphy's)?
- CSMastermind 1y agoIt's weird to me that the author says this behavior feels human because it's nothing like how I solve this puzzle. At no point during my process would I be counting pixels in the image. It feels very clearly like a machine that mimics human behavior without understanding where that behavior comes from.
- alexop 1y agoYes, exactly. What I meant is that a human would also try every "tool" available. In the case of o3, the only tools it had were Python and Bing. But you are right. It does not actually understand anything. It is just a next-token predictor that happens to have access to Python and Bing.
- aledalgrande 1y agoOn a sidenote, I tried to get Codex + O3 to make an existing sidebar toggable with Tailwind CSS and it made an abomination full of bugs. This is a classic "boilerplate" task I'd expect it to be able to do. Not sure if I'm doing it wrong but... a little bit more direct instructions to O4-mini and it managed. The cost was astronomical tho compared to Anthropic.
- Shorn 1y agoI asked ChatGPT about playing chess: it says tests have shown it makes an illegal move within 10 - 15 moves, even if prompted to play carefully and not make any illegal moves. It'll fail within the first 3 or 4 if you ask it play reasonably quickly. That means, it can literally never win a chess match, given an intentional illegal move is an immediate loss. It can't beat a human who can't play chess. It literally can't even lose properly. It will disqualify itself every time. -- > It shows clearly where current models shine (problem-solving) Yeh - that's not what's happening. I say that as someone that pays for and uses an LLM pretty much every day. -- Also - I didn't fact check any of the above about playing chess. I choose to believe.
- simonw 1y agoPreventing an LLM from making illegal moves should be very simple: provide it with tool access to something that tells it if a move is legal or not, then watch it iterate in a loop until it finds a move that it is allowed to make. I expect this would dramatically improve the chess playing abilities of the competent tool using models, such as O3.
- toolslive 1y agoor just present it with the list of legal moves and force it to pick from said list.
- simonw 1y agoI imagine there are points in a chess game, especially early on, where that list could have hundreds of moves - could use up a fair amount of tokens.
- toolslive 1y agoNope. The list is very limited. For the starting position: a3, a4, b3,b4,.......h3, h4, Na3, Nc3, Nf3, Nh3 That's 20 moves. the size grows a bit in the early middle game, but then drops again in the endgame. There do exist rather artificial positions with more than 200 legal moves, but the average number of legal moves in a position is around 40.
- qweaesr 1y ago[flagged]
- cess11 1y ago"o3 does not just spit out an answer. It reasons. It struggles. It switches tools. It self-corrects. Sometimes it even cheats, but only after exhausting every other option. That feels very human." I've never met a human player that suddenly says 'OK, I need Python to figure out my next move'. I'm not a good player, usually I just do ten minute matches against the weakest Stockfish settings so as not to be annoying to a human, and I figured this one out in a couple of minutes because there are very few options. Taking with the rook doesn't work, taking with the pawn also doesn't, so it has to be a non-taking move, and the king can't do anything useful so it has to be the rook and typically in these puzzles it's a sacrifice that unlocks the solution. And it was.
- demirbey05 1y agoBecause its trained on human data.
- scotty79 1y agoInteresting. Personally my thought process was like that: - Check obvious, wrong moves. - Ask what I need to have to win the game even if there's just black king left. Answer is I need all 3 pieces to win some day even if there's just black king on the board. - So any moves that makes me lose my pawn or rook result in failure. - So the only thing I can do with the rook is move it vertically. Any horizontal move allows black to take my pawn. King and pawn don't have much options and all result in pawn loss or basically skipping a turn while changing situation a little bit for the worse that makes mate in one move unlikely. - Taking a pawn with rook results in loss of the rook which is just as bad. - Let's look at spot next to the pawn. I'll still protect my pawn, but my rook is in danger. But if black takes rook, I can just move my pawn forward to get a mate. If they don't I can move rook forward and get a mate. Solved. So I skipped trying to run a program and googling part, not because it didn't came to my mind but because I wanted different kind of challenge then challenge of extracting information from the internet or challenge of running a unfamiliar piece of software.
- baby 1y agoBTW can someone tell me how do you who you are here? I'm reading: > Chess Puzzle Checkmate in 2 White does it mean we are white, or does it mean we're trying to checkmate white?
- legerdemain 1y agoYou are playing white. It's your move. Describe a strategy where on your second move you declare checkmate. Your strategy can have decision branches, but no branch is longer than two moves.
- acyou 1y agoMy thought process was, let me try out a few moves that attack Black. There aren't that many, so... Kb8? No, not allowed. Kb7? No, not allowed. Pa7? No, that doesn't really help. Ra7? No, that doesn't lead to anything useful. Ra6? Oh, yeah, that works. But I wasn't thinking in text, I was thinking graphically. I was visualizing the board. It's not beyond the realm of possibility that you can tokenize graphics. When is that coming?
- nightfox1 1y agoThis is cool, I built a AI Chess Coach to analyze games: https://chesscoach.dev/ https://chesscoach.dev/