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.

My guess is that they would be even easier to detect.

Sargon II is available:

https://c64online.com/c64-games/sargon-ii-de/

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?

> Will they also be treated as second class citizens?

Yes, along side you robosexuals

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 kind of class distinction, maybe with an without augmentation.

what does this have to do with anything whatsoever

I've built engines from scratch. I don't think that would work at all. It's a whole extra challenge to make an engine feel like a human. The engine has to come up with its best move and then sometimes choose not to play it and play something else for some reason. There are statistical patterns to how humans make mistakes based on their level, what kinds of mistake, how big and how often. Cheat detection is less about knowing the engine and more about statistics.

This is very cool. But yes, totally unsurprising that a megahertz machine with 100MB+ available ram has >2500 ELO.

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.

The turbo button slows the CPU down so old programs that depend on clock speed (e.g. early games) run correctly.

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.

I don't think that real-time, superhuman AI performance is ever gonna happen with <1b parameter models.

Biology had a lot of time, attempts and pressure to make this work but even the most optimized lines (something like a magpie) need more complexity (almost a billion neurons) to get a fraction of superhuman intelligence.

Results with small artificial neural nets are very limited so far, too.

On the other hand, symbolic reasoning easily gets superhuman results in narrow domains. The Robbins Conjecture was proved on hardware like that after 60 years. You could check out this theorem prover benchmark suite that has been maintained for over 30 years https://www.tptp.org/

> 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.

Wonderful work! Just inspiring.

I had a Pentium Pro 200 back in the day, to run 3DSMax 1.0 on Windows NT 3.5.

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.

> 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.

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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)

Yes? Amateur means someone who does a thing for recreation, as opposed to for money.

It seemed to me that in the chess community, average club players are usually considered (much) stronger than the average online player. (Especially because of the much larger number of lower skill players online.)

So if you measure amateurs via club players (=what people might have considered chess amateurs before), that might give you a different result from the average online player (=what people might consider average amateurs today).

It is much easier to imagine the 1600 FIDE OTB player doing 20-40 positional evaluations than the 1200 random chess.com scrub (eg me) doing the same.

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.

Slightly difficult to disentangle is that they might be using the verbalisation as a way to explore depth, rubber-duck style, in a way that they wouldn't over the board.

But you can still verbalize without saying the result of it. But yeah, it's still a question whether they would do so, but I think they do.

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.

Yeah I would like to see where that factoid comes from. Maybe it means they explore as many branches from the root position as an amateur, but they explore each branch way deeper and more accurately

Right, but the GMs you see online are often "super GMs". They are on a category of their own in the ultra tail.

No, I watch plenty of "regular" GMs, as well as some IMs and even FMs who all consider way more moves/positions than I do.

I’m around 1800-1900 and they don’t consider more moves or positions than I do at all. It’s just that their analysis is correct and mine is not even close.

I actually don’t know this for sure, I should say that they don’t verbalise more moves than I think about. It’s plausible and perhaps even likely that they have a lot of moves or positions they do touch on but immediately discard so don’t even verbalise.

I am about 300 points higher and think this is roughly correct. In openings amateurs will actually analyze more since GMs just have hundreds of opening lines memorized many moves deep. Middlegame and endgame there're usually just 1-3 reasonable plans that are immediately obvious to a GM (but not at all obvious to amateurs) with 1-3 initial moves each. So, again, probably about as many as I consider.

The only time when GM will definitely analyze more lines than an amateur is in a highly tactical position but that happens, again, maybe 1-3 times per typical game (tactics themselves will last several moves, but they would be largely calculated through at the beginning of the tactical melee).

an amateur player --> shouldn't an amateur player have an average ELO, i.e. be nearly as bad as me, who never wins at chess when someone even knows their ELO or is a bot above lowest difficulty level.

My rating is negative 1900. I was always bad at chess and never really gave it a chance tbh. I always wondered though where does the pattern matching stop and strategy starts or it's one and the same?

> where does the pattern matching stop and strategy starts or it's one and the same?

It's not one and the same, but strategy patterns are definitely a thing too.

There are:

- tactical patterns (e.g. "back rank checkmate", "pair of pieces that can be forked by a pawn");

- strategy patterns (e.g. "in a same-colour bishop endgame, put your pawns on the colour opposite to the bishops").

There's also calculation ability which also partly relies on patterns one has seen before.

There's an analog in machine chess. According to the research paper from 2017, AlphaZero considered ~10,000 moves per decision, 1,000x fewer than Stockfish at the time. h2h it beat Stockfish pretty badly.

But that's not what it's saying right? The quote says grandmasters and amateurs analyze the same number of moves. I mean it would kind of make more sense how you are interpreting it but is that actually what the quote is saying?

>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

What does this mean exactly? They analyze the same number but the grandmaster analyzes "only the most critical moves."

So does that mean at every given analysis opportunity (each move I guess), they analyze better candidates?

If so I guess these 2 things are totally redundant? "they analyze only the most critical moves and do a better job with that analysis."

Alternatively I wondered if perhaps they actually perform analysis on less moves (perhaps because they already know the lines or remember their previous analysis). But I think that contradicts the claim that they analyze about the same number of moves.

> 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.

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, almost certainly.

No way. The parameter count can't fit on consumer devices, and you're not getting orders of magnitude smarter behavior with smaller models.

In 5 years phones can easily have 1 TB flash

Parameter count is basically storage. Including persistent like flash memory. Which (still) is subject to Moore's law.

That's discounting architectural innovations & improvements which are bound to happen somehow.

I wonder how far back you can go? Could a modern chess engine run on a Cray 1? 386? 68k?

I don't think there's a meaningful difference between the Pentium and the 80386 except speed. You might have to change the compiler options a bit.

And, with more work, that's true of computers in general.

I understand about Turing machines.

For chess though, there are time constraints. The 386 is a lot slower. Is it fast enough?

That's a good question, and I don't know the answer, but I can try to guess.

An 80386 is about 10–13 Dhrystone MIPS, while a 200MHz Pentium Pro is about 90–450, according to https://netlib.org/performance/html/dhrystone.data.col0.html. So we're talking about a further slowdown on the order of 20×. I don't know how to estimate how much that would lower its Elo.

The article says:

> By making a number of adjustments to the algorithm and tuning it to the Pentium, we can increase its Elo to 2846 ± 35 at 1 second per move, 3109 ± 79 at 10 seconds per move, and 3180 ± 80 at 30 seconds per move.

So making it 30× faster would raise its 1-second Elo by about 334 points, and ln(30) is 3.4, so that's about 100 points per factor of e. ln(10) is 2.3, so we'd interpolate a prediction of 230 points gained at 10× faster, reasonably close to the 263 points reported.

If we extrapolate that in the other direction, ln(20) is 3.0, so on the 80386 we'd expect a loss of about 300 Elo points, down from 2846 to 2550 or so. Still enough to wipe the floor with Crafty, but low enough that Kasparov would usually beat it.

But we don't really know if that extrapolation is valid.

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I'm guessing that Nicholas Carlini could give you a much more accurate answer by reporting its Elo with a move limit of 50 milliseconds.

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

> because who would want to buy a Pentium Pro when the better-in-almost-every-way Pentium MMX

Maybe this was satirizing people running after every shiny new thing, but the MMX certainly wasn’t. The Pro was the first P6, a totally new, out-of-order microarchitecture that the Pentium 2 would be based on. The MMX was a standard P5 Pentium with a larger L1 and the MMX vector instruction set which, while the first of its kind in an x86, was ultimately not used much in applications, partly because it was integer-only. In any case, the Pros were expensive and meant for business use, while the MMXs were consumer processors.

Just one caveat: the Pro overlapped in time with people running a lot of 16-bit code, and I think the Pentium MMX was faster for that, or at least that the Pro didn't offer much edge.

The pro did register renaming. But the way it worked, if you wrote to AX (16 bit write) and then read from EAX (32 bit read) it caused a pipeline stall from resyncing the registers.

Great project but I have a nit on the board displays: every board is displayed as <human username> vs Pentium Pro, even when the Pentium is playing White. The normal chess convention is <White name> vs <Black name>.

I spent some time trying to figure out how some of the humans seemed to have trapped the machine out of the opening, because it looked like the human was winning.

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Run some current and still-compiled-for-i686 Linux or *BSD distros on it. See what breaks, save logs & report issues upstream.

A lot of support for old CPUs & platforms they're on goes through emulators like QEMU. Or plain old 'go with specs, disturb code as little as possible, and assume (hope) it still works'. But nothing beats running on actual hardware. Uncommon configurations, specific drivers that may have been broken (sometimes for a looong time before someone notices), spec says A but hardware does B, etc.

Cool exploration, and very much needed because depressingly few people who use these engines actually understand this.

Back in 2021 I got cfish and weiss working on a 386sx, though didn't test it much. cfish was doing 5k nps so some results can be extrapolated. NNUE complicated things due to RAM requirements.

> Throughout this article, when I say "I wrote", what I really mean is "I asked an LLM to write".

I wish disclaimers like that would be at the start and not halfway trough the text.

Why? It's late 2026, everyone is using LLMs to write code in some shape or form. The author is talking about code, not the blog post.

Very cool project. It seems incredible that such a "humble" device for the time would match and beat deep blue. It must be true that software has been living off hardware for a very long time, even if as others comment, the latest developments in software have only been possible after hardware got much much better.

A modern chess engine would definitely have defeated Kasparov in 1996. It would have had a database containing all the games, particularly that strange game against a computer nobody knew anything about, which seemed to be able to anticipate all of Kasparov's moves.

Even without an explicit DB it would have been quite strong, core Stockfish would be enough to beat any human as well. Ofc learnings from strange games would still be compressed somewhere in the eval functions.

Nice post, thanks.

On a kinda similar note i always wander that about indie video games. We have this massive hits like balatro, vampire survivors, that easily could be made in the era of SNES or N64. But somehow we have to wait 30 years to get them.

It clearly wasn't technical side of things that prevented that, but also I don't believe it was lack of creativity.

Some could argue that it is just what art is, we will get every year some new thing, creating all "possible and meaningful" art right now isn't even valid thing to consider, because art isn't about exhausting a finite set of possibilities.

But at the other hand some mechanics, design solutions in the hindsight seem kinda obvious and make me wonder, what things we do not see now, but will look obvious to people 30 years from now.

> We have this massive hits like balatro, vampire survivors, that easily could be made in the era of SNES or N64. But somehow we have to wait 30 years to get them.

> It clearly wasn't technical side of things that prevented that, but also I don't believe it was lack of creativity.

I don't know those specific games, but I think this often happens because, although the thing has been technically possible for decades, it used to be relatively difficult/expensive/obscure, and now it's far more accessible. In those days, writing and publishing a SNES game was something that relatively very few people would have even thought to attempt, let alone had the knowledge and skills and capital to pull off successfully. Nowadays, creating and publishing a SNES-level game is comparatively very easy (at the technical level, that is; making a good original game is of course still hard), and so a large portion of the people with an idea and some motivation can actually go ahead and do it. Lots of them won't be very interesting, but collectively we're exploring the design space much more quickly and efficiently.

Just because a game could graphically have been displayed on an N64 doesn’t mean the game could be built. Vampire Survivors has hundreds of units on screen at a time firing hundreds of projectiles and weapon effects; running those on a memory bandwidth-constrained 93MHz single core processor in 4MB of RAM would be, uh… a challenge.

More opportunity to write games. It is infitenly easier to get into writing games now than back then.

Also, don't underestimate the "juice" that these days is relatively easy to do but would be expenseive back then. Balatro has dozens of very small things going on graphically that make it feel real nice to play that most certainly not be free on SNES hardware.

And like vampire survivors is just Robotron/Smash TV with infinity number of sprites on screen. The limitation is very much hardware in that case.

Makes me wonder if a modern ESP32 could have beaten him.

Of course, “human vs supercomputer” is more exciting to the public than “human vs toaster controller”.

I find the general topic of purely algorithmic progress super interesting.

I just ran Andrej Karpathy's Tiny Stories model on a tiny ESP32. In principle we could probably have done this in the 80's and it would have been so amazing.

Interesting article. Have we just acquired better insights into programming chess? Are ELO ratings guaranteed to predict whether a machine can beat a human or can a human outsmart a higher ELO rated chess program?