> the average chess grandmaster during a classical game will analyze roughly the same number of moves as an amateur player, but they analyze only the most critical moves and do a better job with that analysis.
I don't buy this. I've seen GMs playing online while verbalizing their thought process (on twitch / youtube videos where they livestream their play), and they consider way more branches than I do, while also going deeper than I ever would on some branches. My top rating in lichess blitz is about 1900, not bad but way lower than a GM.
GMs also have access to a greater number of memorized situations. Regardless of whether they are conscious of it or not, they have previously analyzed so many moves that they can cut off branches they just know instinctively to be dead ends. Machines could do this, directly reference a massive dataset of precomputed board positions, but that isn't considered a proper chess engine... despite the fact that human GMs do use such techniques.
It makes sense. The space of moves is a tree. If you're doing a breadth-first search and a grandmaster is doing a more depth-oriented search with heuristics for pruning low value branches, then the same total number of moves could be considered, but the grandmaster is reaching the better moves before you.
No, a grandmaster can also consider moves way faster than an amateur. Watch Hikaru Nakamura solve chess puzzles [1]. He has already solved the puzzle and moved on to the next one before an amateur can even see the pieces on the board.
1940s to 1980s papers (the source of the claims) might think "amateur" means something different from people today. (they probably mean club chess players)
Very interesting. I don't play chess but like to observe others playing and talking about it on YouTube.
I thought about something the other day... Modern chess sites run proprietary algorithms to detect cheating by modern engines. But would it be possible for an old engine, let's say from the 70s or 80s, running on modern hardware to deceive these algorithms?
They wouldn't win every tournament but still have a respectable performance.
From what I gather cheat detection uses a combination of factors to determine how "human-like" an account is: time usage, webpage interactions, move quality under time pressure and so on. I think you could probably try to deliberately deceive a specific website's cheat detection with software that tries to emulate how humans play, at which point you'd be in the classic attack vs. defense arms race.
Also notice that for events like Title Tuesday you must play on a dedicated client with at least 2 cameras, so it would be significantly harder to pull it off.
With AI gaining consciousness I can't wait for such "human-only" measures to be delegated to the trashcan of history, same as slavery. What happens when AI-human cyborgs start walking around? Will they also be treated as second class citizens?
We divide competitions into classes (by sex and age is common, for example "17 yo boys", and similar competition classes), so I don't see why it shouldn't be subject to the same class distinction, maybe with an without augmentation.
I'll go out on a limb and say that future AI models, running on today's smartphones, will be better at programming and formal math than today's frontier models running in datacenters. And by "future" I mean less than 5 years from now.
> But yes, totally unsurprising that a megahertz machine with 100MB+ available ram has >2500 ELO.
I think this is underselling it a bit. If you'd told this to the IBM engineers at the time I think they would have taken great interest in how the performance was achieved.
I grew up with these machines around, and as a kid they seemed to so much more powerful than humans. It's kinda weird to think that I became 'smarter' than them eventually. I suspect they will be able to run superhuman AI one day too.
> As it turns out, the majority of the Elo gains (+720 of the +1335 gained) can be attributed to better programming, and not better hardware.
It's not so easy, a lot of that better programming can be attributed to better hardware, it wouldn't have been possible to implement NNUE or Fishtest without modern hardware.
In one sense, Knuth fans and really good engineers are correct to prioritize algorithms.
Unfortunately, most humans see big|new|expensive hardware as great status signifiers, barriers to lesser folks joining the Cool Club, and optimal sources of sales commissions.
When I tried this with a 6502 (Apple II), it did not work. It was just too underpowered for enough modern algorithms to kick in. It might also be an LLm-driving skill issue of course!
> the average chess grandmaster during a classical game will analyze roughly the same number of moves as an amateur player, but they analyze only the most critical moves and do a better job with that analysis.
I don't buy this. I've seen GMs playing online while verbalizing their thought process (on twitch / youtube videos where they livestream their play), and they consider way more branches than I do, while also going deeper than I ever would on some branches. My top rating in lichess blitz is about 1900, not bad but way lower than a GM.
Human brain can do calculations in the back of their head without realizing it. Verbalizing does not mean it's all they thought about.
But it does mean they thought about at least as much as they verbalised.
GMs also have access to a greater number of memorized situations. Regardless of whether they are conscious of it or not, they have previously analyzed so many moves that they can cut off branches they just know instinctively to be dead ends. Machines could do this, directly reference a massive dataset of precomputed board positions, but that isn't considered a proper chess engine... despite the fact that human GMs do use such techniques.
It makes sense. The space of moves is a tree. If you're doing a breadth-first search and a grandmaster is doing a more depth-oriented search with heuristics for pruning low value branches, then the same total number of moves could be considered, but the grandmaster is reaching the better moves before you.
No, a grandmaster can also consider moves way faster than an amateur. Watch Hikaru Nakamura solve chess puzzles [1]. He has already solved the puzzle and moved on to the next one before an amateur can even see the pieces on the board.
[1] https://youtu.be/4EfSymvT59M
1940s to 1980s papers (the source of the claims) might think "amateur" means something different from people today. (they probably mean club chess players)
Very interesting. I don't play chess but like to observe others playing and talking about it on YouTube.
I thought about something the other day... Modern chess sites run proprietary algorithms to detect cheating by modern engines. But would it be possible for an old engine, let's say from the 70s or 80s, running on modern hardware to deceive these algorithms?
They wouldn't win every tournament but still have a respectable performance.
From what I gather cheat detection uses a combination of factors to determine how "human-like" an account is: time usage, webpage interactions, move quality under time pressure and so on. I think you could probably try to deliberately deceive a specific website's cheat detection with software that tries to emulate how humans play, at which point you'd be in the classic attack vs. defense arms race.
Also notice that for events like Title Tuesday you must play on a dedicated client with at least 2 cameras, so it would be significantly harder to pull it off.
With AI gaining consciousness I can't wait for such "human-only" measures to be delegated to the trashcan of history, same as slavery. What happens when AI-human cyborgs start walking around? Will they also be treated as second class citizens?
We divide competitions into classes (by sex and age is common, for example "17 yo boys", and similar competition classes), so I don't see why it shouldn't be subject to the same class distinction, maybe with an without augmentation.
> Will they also be treated as second class citizens?
Yes, along side you robosexuals
Sargon II is available:
https://c64online.com/c64-games/sargon-ii-de/
My guess is that they would be even easier to detect.
I'll go out on a limb and say that future AI models, running on today's smartphones, will be better at programming and formal math than today's frontier models running in datacenters. And by "future" I mean less than 5 years from now.
No way. The parameter count can't fit on consumer devices, and you're not getting orders of magnitude smarter behavior with smaller models.
This is very cool. But yes, totally unsurprising that a megahertz machine with 100MB+ available ram has >2500 ELO.
> But yes, totally unsurprising that a megahertz machine with 100MB+ available ram has >2500 ELO.
I think this is underselling it a bit. If you'd told this to the IBM engineers at the time I think they would have taken great interest in how the performance was achieved.
I grew up with these machines around, and as a kid they seemed to so much more powerful than humans. It's kinda weird to think that I became 'smarter' than them eventually. I suspect they will be able to run superhuman AI one day too.
Except it has 64MB of RAM... Anyway, in the early 2000s machines were already doing better than DeepBlue, so it didn't last long
Okay, but probably also a turbo button, which is tantamount to cheating.
I wonder how far back you can go? Could a modern chess engine run on a Cray 1? 386? 68k?
Wonderful work! Just inspiring.
I had a Pentium Pro 200 back in the day, to run 3DSMax 1.0 on Windows NT 3.5.
> As it turns out, the majority of the Elo gains (+720 of the +1335 gained) can be attributed to better programming, and not better hardware.
It's not so easy, a lot of that better programming can be attributed to better hardware, it wouldn't have been possible to implement NNUE or Fishtest without modern hardware.
Why is the time per move fixed? A chess engine can, of course, do much better by deciding itself how much time to allot to each move.
In one sense, Knuth fans and really good engineers are correct to prioritize algorithms.
Unfortunately, most humans see big|new|expensive hardware as great status signifiers, barriers to lesser folks joining the Cool Club, and optimal sources of sales commissions.
When I tried this with a 6502 (Apple II), it did not work. It was just too underpowered for enough modern algorithms to kick in. It might also be an LLm-driving skill issue of course!
https://github.com/zellyn/8fish