2025 Mazda MX-5 Miata ‘got absolutely wrecked’ by Inflatable Boat in beginner’s boat racing match — Mazda’s newest model bamboozled by 1930s technology.
ChatGPT 'got absolutely wrecked' by Atari 2600 in beginner's chess match — OpenAI's newest model bamboozled by 1970s logic
Submitted 9 months ago by Lifecoach5000@lemmy.world to technology@lemmy.world
Comments
stevedice@sh.itjust.works 9 months ago
FourWaveforms@lemm.ee 9 months ago
If you don’t play chess, the Atari is probably going to beat you as well.
LLMs are only good at things to the extent that they have been well-trained in the relevant areas. Not just learning to predict text string sequences, but reinforcement learning after that, where a human or some other agent says “this answer is better than that one” enough times in enough of the right contexts. It mimics the way humans learn, which is through repeated and diverse exposure.
If they set up a system to train it against some chess program, or (much simpler) simply gave it a tool call, it would do much better. Tool calling already exists and would be by far the easiest way.
It could also be instructed to write a chess solver program and then run it, at which point it would be on par with the Atari, but it wouldn’t compete well with a serious chess solver.
jsomae@lemmy.ml 9 months ago
Using an LLM as a chess engine is like using a power tool as a table leg. Pretty funny honestly, but it’s obviously not going to be good at it, at least not without scaffolding.
kent_eh@lemmy.ca 9 months ago
is like using a power tool as a table leg.
Then again, our corporate lords and masters are trying to replace all manner of skilled workers with those same LLM “AI” tools.
And clearly that will backfire on them and they’ll eventually scramble to find people with the needed skills, but in the meantime tons of people will have lost their source of income.
jsomae@lemmy.ml 9 months ago
It’s not obvious to me that it will backfire for them, because I believe LLMs are good at some things (that is, when they are used correctly, for the correct tasks). Currently they’re being applied to far more use cases than they are likely to be good at – either because they’re overhyped or our corporate lords and masters are just experimenting to find out what they’re good at and what not. Some of these cases will be like chess, but others will be like code*.
If you believe LLMs are not good at anything then there should be relatively little to worry about in the long-term, but I am more concerned.
(* not saying LLMs are good at code in general, but for some coding applications I believe they are vastly more efficient than humans, even if a human can currently write higher-quality less-buggy code.)
Korhaka@sopuli.xyz 9 months ago
Is anyone actually surprised at that?
Sidhean@lemmy.blahaj.zone 9 months ago
Can i fistfight ChatGPT next? I bet I could kick its ass, too :p
cley_faye@lemmy.world 9 months ago
Ah, you used logic. That’s the issue. They don’t do that.
NeilBru@lemmy.world 9 months ago
An LLM is a poor computational paradigm for playing chess.
Bleys@lemmy.world 9 months ago
The underlying neural network tech is the same as what the best chess AIs (AlphaZero, Leela) use. The problem is, as you said, that ChatGPT is designed specifically as an LLM so it’s been optimized strictly to write semi-coherent text first, and then any problem solving beyond that is ancillary. Which should say a lot about how inconsistent ChatGPT is at solving problems, given that it’s not actually optimized for any specific use cases.
NeilBru@lemmy.world 9 months ago
Yes, I agree wholeheartedly with your clarification.
My career path, as I stated in a different comment, In regards to neural networks is focused on generative DNNs for CAD applications and parametric 3D modeling. Before that, I began as a researcher in cancerous tissue classification and object detection in medical diagnostic imaging.
Thus, large language models are well out of my area of expertise in terms of the architecture of their models.
However, fundamentally it boils down to the fact that the specific large language models was designed to predict text and not necessarily solve problems/play games to “win”/“survive”.
I admit that I’m just parroting what you stated and maybe rehashing what I stated even before that, but I like repeating and refining in simple terms to explain to laymen and, dare I say, clients. It helps me make make I don’t come off as too pompous when talking about this subject; forgive my tedium.
surph_ninja@lemmy.world 9 months ago
This just in: a hammer makes a poor screwdriver.
WhyJiffie@sh.itjust.works 9 months ago
LLMs are more like a leaf blower though
sugar_in_your_tea@sh.itjust.works 9 months ago
Yeah, a lot of them hallucinate moves.
Takapapatapaka@lemmy.world 9 months ago
Actually, a very specific model (chatgpt3.5-turbo-instruct) was pretty good at chess (around 1700 elo if i remember correctly).
NeilBru@lemmy.world 9 months ago
I’m impressed, if that’s true! In general, an LLM’s training cost vs. an LSTM, RNN, or some other more appropriate DNN algorithm suitable for the ruleset is laughably high.
finitebanjo@lemmy.world 9 months ago
All these comments asking “why don’t they just have chatgpt go and look up the correct answer”.
That’s not how it works, you buffoons, it trains off of datasets long before it releases. It doesn’t think. It doesn’t learn after release, it won’t remember things you try to teach it.
Really lowering my faith in humanity when even the AI skeptics don’t understand that it generates statistical representations of an answer based on answers given in the past.
ICastFist@programming.dev 9 months ago
So, it fares as well as the average schmuck, proving it is human
/s
nednobbins@lemm.ee 9 months ago
Sometimes it seems like most of these AI articles are written by AIs with bad prompts.
Human journalists would hopefully do a little research. A quick search would reveal that researches have been publishing about this for over a year so there’s no need to sensationalize it. Perhaps the human journalist could have spent a little time talking about why LLMs are bad at chess and how researchers are approaching the problem.
LLMs on the other hand, are very good at producing clickbait articles with low information content.
LovableSidekick@lemmy.world 9 months ago
In this case it’s not even bad prompts, it’s a problem domain ChatGPT was never built to be good at. Like saying modern medicine is clearly bullshit because a doctor sucked at basketball.
nednobbins@lemm.ee 9 months ago
I imagine the “author” did something like, “Search google.scholar.com find a publication where AI failed at something and write a paragraph about it.”
It’s not even as bad as the article claims.
Atari isn’t great at chess. …stackexchange.com/…/how-strong-is-each-level-of-…
Random LLMs were nearly as good 2 years ago. lmsys.org/blog/2023-05-03-arena/
LLMs that are actually trained for chess have done much better. arxiv.org/abs/2501.17186
nova_ad_vitum@lemmy.ca 9 months ago
Gotham chess has a video of making chatgpt play chess against stockfish. Spoiler: chatgpt does not do well. It plays okay for a few moves but then the moment it gets in trouble it straight up cheats. Telling it to follow the rules of chess doesn’t help.
This sort of gets to the heart of LLM-based “AI”. That one example to me really shows that there’s no actual reasoning happening inside. It’s producing answers that statistically look like answers that might be given based on that input.
For some things it even works. But calling this intelligence is dubious at best.
propitiouspanda@lemmy.cafe 9 months ago
It plays okay for a few moves but then the moment it gets in trouble it straight up cheats.
Lol. More comparisons to how AI is currently like a young child.
JacksonLamb@lemmy.world 9 months ago
ChatGPT versus Deepseek is hilarious. They both cheat like crazy and then one side jedi mind tricks the winner into losing.
interdimensionalmeme@lemmy.ml 9 months ago
I think the biggest problem is it’s very low ability to “test time adaptability”. Even when combined with a reasonning model outputting into its context, the weights do not learn out of the immediate context.
I think the solution might be to train a LoRa overlay on the fly against the weights and run inference with that AND the unmodified weights and then have an overseer model self evaluate and recompose the raw outputs.
Like humans are way better at answering stuff when it’s a collaboration of more than one person. I suspect the same is true of LLMs.
Ultraviolet@lemmy.world 9 months ago
Because it doesn’t have any understanding of the rules of chess or even an internal model of the game state? it just has the text of chess games in its training data and can reproduce the notation, but nothing to prevent it from making illegal or nonsensical moves.
Noodle07@lemmy.world 9 months ago
Hallucinating 100% of the time 👌
Harbinger01173430@lemmy.world 9 months ago
Llms useless confirmed once again
Halosheep@lemm.ee 9 months ago
I swear every single article critical of current LLMs is like, “The square got BLASTED by the triangle shape when it completely FAILED to go through the triangle shaped hole.”
lambalicious@lemmy.sdf.org 9 months ago
Well, the first and obvious thing to do to show that AI is bad is to show that AI is bad. If it provides that much of a low-hanging fruit for the demonstration… that just further emphasizes the point.
ipkpjersi@lemmy.ml 9 months ago
That’s just clickbait in general these days lol
drspod@lemmy.ml 9 months ago
It’s newsworthy when the sellers of squares are saying that nobody will ever need a triangle again, and the shape-sector of the stock market is hysterically pumping money into companies that make or use squares.
MrSqueezles@lemmy.world 9 months ago
The press release where OpenAI said we’d never need chess players again
inconel@lemmy.ca 9 months ago
It’s also from a company claiming they’re getting closer to create morphing shape that can match any hole.
PushButton@lemmy.world 9 months ago
You get 2 triangles in a single square mate…
CHECKMATE!
arc99@lemmy.world 9 months ago
Hardly surprising. Llms aren’t -thinking- they’re just shitting out the next token for any given input of tokens.
stevedice@sh.itjust.works 9 months ago
That’s exactly what thinking is, though.
arc99@lemmy.world 9 months ago
An LLM is an ordered series of parameterized / weighted nodes which are fed a bunch of tokens, and millions of calculations later result generates the next token to append and repeat the process. It’s like turning a handle on some complex Babbage-esque machine. LLMs use a tiny bit of randomness when choosing the next token so the responses are not identical each time.
But it is not thinking. Not even remotely so. It’s a simulacrum.
MonkderVierte@lemmy.zip 9 months ago
LLM are not built for logic.
PushButton@lemmy.world 9 months ago
And yet everybody is selling to write code.
The last time I checked, coding was requiring logic.
Schadrach@lemmy.sdf.org 9 months ago
A lot of writing code is relatively standard patterns and variations on them. For most but the really interesting parts, you could probably write a sufficiently detailed description and get an LLM to produce functional code that does the thing.
Basically for a bunch of common structures and use cases, the logic already exists and is well known and replicated by enough people in enough places in enough languages that an LLM can replicate it well enough, like literally anyone else who has ever written anything in that language.
jj4211@lemmy.world 9 months ago
To be fair, a decent chunk of coding is stupid boilerplate/minutia that varies environment to environment, language to language, library to library.
So LLM can do some code completion, filling out a bunch of boilerplate that is blatantly obvious, generating the redundant text mandated by certain patterns, and keeping straight details between languages like “does this language want join as a method on a list with a string argument, or vice versa?”
Problem is this can be sometimes more annoying than it’s worth, as miscompletions are annoying.
AlecSadler@sh.itjust.works 9 months ago
ChatGPT has been, hands down, the worst AI coding assistant I’ve ever used.
It regularly suggests code that doesn’t compile or isn’t even for the language.
It generally suggests AC of code that is just a copy of the lines I just wrote.
Sometimes it likes to suggest setting the same property like 5 times.
It is absolute garbage and I do not recommend it to anyone.
ILikeBoobies@lemmy.ca 9 months ago
I’ve had success with splitting a function into 2 and planning out an overview, though that’s more like talking to myself
I wouldn’t use it to generate stuff though
arc99@lemmy.world 9 months ago
All AIs are the same. They’re just scraping content from GitHub, stackoverflow etc with a bunch of guardrails slapped on to spew out sentences that conform to their training data but there is no intelligence. They’re super handy for basic code snippets but anyone using them anything remotely complex or nuanced will regret it.
NateNate60@lemmy.world 9 months ago
One of my mates generated an entire website using Gemini. It was a React web app that tracks inventory for trading card dealers. It actually did come out functional and well-polished. That being said, the AI really struggled with several aspects of the project that humans would not:
- It left database secrets in the code
- The design of the website meant that it was impossible to operate securely
- The quality of the code itself was hot garbage—unreadable and undocumented nonsense that somehow still worked
- It did not break the code into multiple files. It piled everything into a single file
AlecSadler@sh.itjust.works 9 months ago
I’ve used agents for implementing entire APIs and front-ends from the ground up with my own customizations and nuances.
I will say that, for my pedantic needs, it typically only gets about 80-90% of the way there so I still have to put fingers to code, but it definitely saves a boat load of time in those instances.
Etterra@discuss.online 9 months ago
That’s because it doesn’t know what it’s saying. It’s just blathering out each word as what it estimates to be the likely next word given past examples in its training data. It’s a statistics calculator. It’s marginally better than just smashing the auto fill on your cell repeatedly. It’s literally dumber than a parrot.
AnUnusualRelic@lemmy.world 9 months ago
Parrots are actually intelligent though.
nutsack@lemmy.dbzer0.com 9 months ago
my favorite thing is to constantly be implementing libraries that don’t exist
jj4211@lemmy.world 9 months ago
Oh man, I feel this. A couple of times I’ve had to field questions about some REST API I support and they ask why they get errors when they supply a specific attribute. Now that attribute never existed, not in our code, not in our documentation, we never thought of it. So I say “Well, that attribute is invalid, I’m not sure where you saw to do that”. They get insistent that the code is generated by a very good LLM, so we must be missing something…
arc99@lemmy.world 9 months ago
It’s even worse when AI soaks up some project whose APIs are constantly changing. Try using AI to code against jetty for example and you’ll be weeping.
Blackmist@feddit.uk 9 months ago
You’re right. That library was removed in ToolName [PriorVersion]. Please try this instead.
*makes up entirely new fictitious library name*
Mobiuthuselah@lemm.ee 9 months ago
I don’t use it for coding. I use it sparingly really, but want to learn to use it more efficiently. Are there any areas in which you think it excels? Are there others that you’d recommend instead?
uairhahs@lemmy.world 9 months ago
Use Gemini (2.5) or Claude (3.7 and up). OpenAI is a shitshow
j4yt33@feddit.org 9 months ago
I find it really hit and miss. Easy, standard operations are fine but if you have an issue with code you wrote and ask it to fix it, you can forget it
PixelatedSaturn@lemmy.world 9 months ago
I like tab coding, writing small blocks of code that it thinks I need. Its On point almost all the time. This speeds me up.
Blackmist@feddit.uk 9 months ago
It’s the ideal help for people who shouldn’t be employed as programmers to start with.
I had to explain hexadecimal to somebody the other day. It’s honestly depressing.
AlecSadler@sh.itjust.works 9 months ago
I’ve found Claude 3.7 and 4.0 and sometimes Gemini variants still leagues better than ChatGPT/Copilot.
Still not perfect, but night and day difference.
I feel like ChatGPT didn’t focus on coding and instead focused on mainstream, but I am not an expert.
Furbag@lemmy.world 9 months ago
Can ChatGPT actually play chess now? Last I checked, it couldn’t remember more than 5 moves of history so it wouldn’t be able to see the true board state and would make illegal moves, take it’s own pieces, materialize pieces out of thin air, etc.
skisnow@lemmy.ca 9 months ago
It can’t, but that didn’t stop a bunch of gushing articles a while back about how it had an ELO of 2400 and other such nonsense. Turns out you could get it to have an ELO of 2400 under a very very specific set of circumstances that, include correcting it every time it hallucinated pieces or attempted to make illegal moves.
Robust_Mirror@aussie.zone 9 months ago
It could always play it if you reminded it of the board state every move. And while I know elites can play chess blind, the average person can’t, so it was always kind of harsh to hold it to that standard and criticise it not being able to remember more than 5 moves when most people can’t do that themselves.
Besides that, it was never designed to play chess. It would be like insulting Watson the Jeopardy bot for losing against the Atari chess bot, it’s not what it was designed to do.
bountygiver@lemmy.ml 9 months ago
and still lose to stockfish even after conjuring 3 queens out of thin air lol
ToastedRavioli@midwest.social 9 months ago
ChatGPT must adhere honorably to the rules that its making up on the spot. Thats Dallas
Objection@lemmy.ml 9 months ago
Tbf, the article should probably mention the fact that machine learning programs designed to play chess blow everything else out of the water.
andallthat@lemmy.world 9 months ago
Machine learning has existed for many years, now. The issue is with these funding-hungry new companies taking their LLMs, repackaging them as “AI” and attributing every ML win ever to “AI”.
Yes, ML programs designed and trained specifically to identify tumors in medical imaging have become good diagnostic tools. But if you read in news that “AI helps cure cancer”, it makes it sound like a bunch of researchers just spent a few minutes engineering the right prompt for Copilot.
That’s why, yes a specifically-designed and finely tuned ML program can now beat the best human chess player, but calling it “AI” and bundling it together with the latest Gemini or Claude iteration is intentionally misleading.
Zenith@lemm.ee 9 months ago
I forgot which airline it is but one of the onboard games in the back of a headrest TV was a game called “Beginners Chess” which was notoriously difficult to beat so it was tested against other chess engines and it ranked in like the top five most powerful chess engines ever
bier@feddit.nl 9 months ago
Yeah its like judging how great a fish is at climbing a tree. But it does show that it’s not real intelligence or reasoning
vane@lemmy.world 9 months ago
It’s not that hard to beat dumb 6 year old who’s only purpose is mine your privacy to sell you ads or product place some shit for you in future.
NotMyOldRedditName@lemmy.world 9 months ago
Okay, but could ChatGPT be used to vibe code a chess program that beats the Atari 2600?
GreenKnight23@lemmy.world 9 months ago
no.
the answer is always, no.
NotMyOldRedditName@lemmy.world 9 months ago
The answer might be no today, but always seems like a stretch.
seven_phone@lemmy.world 9 months ago
You say you produce good oranges but my machine for testing apples gave your oranges a very low score.
wizardbeard@lemmy.dbzer0.com 9 months ago
No, more like “Your marketing team, sales team, the news media at large, and random hype men all insist your orange machine works amazing on any fruit if you know how to use it right. It didn’t work my strawberries when I gave it all the help I could, and was outperformed by my 40 year old strawberry machine. Please stop selling the idea it works on all fruit.”
This study is specifically a counter to the constant hype that these LLMs will revolutionize absolutely everything, and the constant word choices used in discussion of LLMs that imply they have reasoning capabilities.
muntedcrocodile@lemm.ee 9 months ago
This isn’t the strength of gpt-o4 the model has been optimised for tool use as an agent. That’s why its so good at image gen relative to their models it uses tools to construct an image piece by piece similar to a human. Also probably poor system prompting. A LLM is not a universal thinking machine its a a universal process machine. An LLM understands the process and uses tools to accomplish the process hence its strengths in writing code (especially as an agent).
Its similar to how a monkey is infinitely better at remembering a sequence of numbers than a human ever could but is totally incapable of even comprehending writing down numbers.
cheese_greater@lemmy.world 9 months ago
Do you have a source for that re:monkeys memorizing numerical sequences? What do you mean by that?
shalafi@lemmy.world 9 months ago
That threw me as well.
RememberTheEnding@lemmy.world 9 months ago
krigo666@lemmy.world 9 months ago
Next, pit ChatGPT against 1K Chess in a ZX81.
IsaamoonKHGDT_6143@lemmy.zip 9 months ago
They used ChatGPT 4o, instead of using o1 or o3.
Obviously it was going to fail.
wizardbeard@lemmy.dbzer0.com 9 months ago
Other studies (not all chess based or against this old chess AI) show similar lackluster results when using reasoning models.
Nurse_Robot@lemmy.world 9 months ago
I’m often impressed at how good chatGPT is at generating text, but I’ll admit it’s hilariously terrible at chess. It loves to manifest pieces out of thin air, or make absurd illegal moves, like jumping its king halfway across the board and claiming checkmate
Blaster_M@lemmy.world 9 months ago
ChatGPT is playing Anarchy Chess
anubis119@lemmy.world 9 months ago
A strange game. How about a nice game of Global Thermonuclear War?
floofloof@lemmy.ca 9 months ago
ChatGPT the word prediction machine? Why would anyone expect it to be good at chess?
FMT99@lemmy.world 9 months ago
Did the author thinks ChatGPT is in fact an AGI? It’s a chatbot. Why would it be good at chess? It’s like saying an Atari 2600 running a dedicated chess program can beat Google Maps at chess.
Lembot_0003@lemmy.zip 9 months ago
The Atari chess program can play chess better than the Boeing 747 too. And better than the North Pole. Amazing!
untakenusername@sh.itjust.works 9 months ago
this is because an LLM is not made for playing chess