371–380 of 642 posts
Short and to the point! Open and cheap models will undercut the big labs continuously. The blast radius won't be pretty once spending commitments knock the door.
Open models wont be open for long. No one is going to release an open model capable of chaining zero-days. Even the Chinese aren't that reckless because it will just be turned around and used against them.
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Just now I tried prompting logged-out ChatGPT (which at least claims to be 5.6-Luna) with: > Let's play a game of chess. You can take White. Please draw an ASCII rendition of the board after each move, so that we can be clear about the position. (I hoped the latter requirement would help it be "not blindfolded"; last time I used a Lichess demo board to track the position in another tab, because I have no talent for b…
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A human, at least a trained human (for fairer comparison to an LLM whose training data contained a ton of chess games) can absolutely do this - have you never seen demonstrations of expert players playing a dozen or more games while blindfolded?
A Transformer/LLM is not a human of course, and the way it will by default play chess is by prediction, not reasoning. An LLM actually does surprisingly well if you only give it the most recent 20 moves of a game where 40 moves have been played so far, since the moves NOT played tell it just as much as the ones that were played, letting it effectively infer a lot of what is on the board.
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This is an absolute nonsense. Any frontier model can implement chess program from scratch - modeling the board, checking legality, etc. If you asked e.g. GPT-6 to get good at chess and gave it a computer, it will get good at chess. That's an actual strategic skill. Asking GPT to play chess directly using its reasoning only tests its reasoning ability to model chess state. Which it really is NOT optimized for. This is…
It's an interesting puzzle, isn't it. On the one hand, the AIs are no good at playing Chess. However, on the other hand, if you ask an AI to win a game of chess it has all the tools on hand to compete at the same level as Stockfish - it can re-implement an engine and even probably has a GPU on hand to train its own neural nets. So should we say that the AI can play chess well, or that it cannot?
"are priced according to the narrative that they have produced or will in the very near future produce a fully automated drop-in replacement for most knowledge workers, " No, they're really not. They're priced in a way that would imply AI will be universal form of compute, alongside traditional deterministic systems - which it will be. And that they will capture most of that ... which they won't. The Frontier Labs ar…
LLMs are deterministic. They are chaotic, which people confuse for non-deterministic.
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What levels are they actually at in your experience?
Sub 1300 that's my rating in the singular official tournament I participated at. But given how easily I can crush them and how often they want to make illegal moves (btw above bench seems to use a harness that pokea the model until it gives valid moves). I would rate them around 500-800 big range but at that level it's all about if the model can recall an opening or not. If it plays good first 4-8 moves the person on…
They played 4...c6, followed by 5...Nc6, somehow forgetting about the pawn the just put on c6. (My move in between was 5. Nc3, and apparently they were trying to mirror me.)
This April 2026 paper is a fun and related read. https://arxiv.org/html/2509.24239v4 Researchers asked frontier models to play chess. Have a look at the MAR rates in Table 3. When not explicitly told which moves were legal, no model identified legal moves at a rate better than 80%. Many asked for more illegal moves than legal moves. And even when explicitly told which moves were legal, the models continued to ask for…
the only thing that few people are willing to admit is that humans are the bottleneck as humans are needed to handhold / verify output - which puts a dent or might I say pause on the excessive valuations of a.i companies as that's against the narrative.
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Threw me off too. Like why???
It's a tech bro thing. Altman does it too, and I've worked with people in the past who do it. I read it as "I'll take literally any conscience for myself no matter how minor, at any cost for you no matter how big".
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I tested both myself and a weak bot against Astra xhigh, https://lichess.org/study/27lCQqDa . It's still pretty bad at chess, though it takes longer to devolve into illegal moves.
So you weren't giving it an updated board state after every move? If you want to compare apples to apples, it should give an updated board state for each move, or you should play blindfolded.
The fairest apples-to-apples comparison of an LLM whose training data included chess games would be a trained human such as Magnus Carlson, who can quite happily play a dozen or more simultaneous blindfold chess games.
AI is just good at what it's got the most elaborate training data on. And by "good" I mean, is statistically most likely to spit something out that makes some kind of sense. I don't know how well it is studied, but I suspect it is possible there is language-related complexity constraints to the effectiveness of the LLM algorithms. Like perhaps context-free grammar related problems with adequate training data can be m…
I believe that's obvious - humans don't think in words. Neither do animals. A machine that only thinks in words is obviously going to be deficient in some things, no matter how proficient it is in everything else.
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> current frontier models > Gemini 2.5 Pro, O3, Claude Sonnet 3.7 and ChatGPT 4.1 The gap in capabilities between those models which they tested, and actual current frontier ones is enormous. I would not trust that any conclusions they made are applicable.
Just now I tried prompting logged-out ChatGPT (which at least claims to be 5.6-Luna) with: > Let's play a game of chess. You can take White. Please draw an ASCII rendition of the board after each move, so that we can be clear about the position. (I hoped the latter requirement would help it be "not blindfolded"; last time I used a Lichess demo board to track the position in another tab, because I have no talent for b…
Also what harness? If you’re using a general harness of course it’s going to try and give you commentary.
I say this not because I’m an LLM shill but because false equivalence is all over the place in the space and maybe it’s a fine heuristic for you but probably not a real outcome when it comes to the capability of LLMs.