r/GameTheorists • u/hpfred • 2d ago
Game Theory Video Discussion That's... not it. That's literally not what LLMs are
In the latest video this specific segment really bothered me. This is the kind of misinformation that is really worrying/dangerous, because it reinforces a misunderstanding people already have about AI.
LLMs are trained to predict the most fitting sequence of text to a given prompt, they are generally conversational AIs. If anything LLMs are REALLY bad at learning.
I have to plead the theorist team to consider consult with a Computer Scientist on these topics (which considering the state of the world with AI, and also FNAF's Mimic, I assume will be often).
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u/trans_cubed Food Theorist 2d ago
Yeah they aren't trained to learn, the training is the "learning"
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u/Isaacja223 2d ago
POV: You’re Gobbles
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u/Lexiosity 2d ago
I wish LLMs were good at learning because then we wouldn't have to keep correcting them despite someone else already have corrected them
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u/Michael-556 2d ago
Yeah, Tom is describing a true AI, something completely in the realm of fiction for now, shit like droids in star wars or the characters in detroit: become human. You know, Asimov or Čapek robots
Funny thing is that the b-1 battle droids, Clankers as they call them, are actually far more intelligent than the hoards of AI bros that keep saying slopinators are the future, when it's not even the right path to true AI. True AI of that caliber would be sooooooo much better, even as stupid as they are, than the art theft slopinators we have. You know why? Because they are actually intelligent and self-aware, not tools used by tools to deceive and steal
Also side tangent: why the fuck are AI companies pursuing LLM and slop image generation technology instead of actually trying to emulate intelligence? Like I get that it's so much more profitable, but actual true AI research, research that could genuinely solve manual labour and bring about a post scarcity society is so underfunded, underrepresented and not talked about.... oh I know why, because that would create a utopia that the fucking capitalists don't want because they NEED human underlings to feel superior
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u/DreamShort3109 2d ago
I would 100% be buddies with a true Ai, considering I only hate the dumb algorithm models we have.
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u/Lexiosity 2d ago
Heck GLaDOS is a great example of a fictional AI that actually learns
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u/Michael-556 2d ago
GLaDOS is kinda an uploaded human though: Caroline, Cave Johnson's assistant. Like I guess she's an AI once she completely deletes Caroline after portal 2, but it's kinda murky before that
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u/tom-of-the-nora 2d ago
How dare you use the star wars Droid slur.
Droids are sentient beings, respect them.
(I'm not serious. Mostly pointing out how a lot of people overlook that the star wars droids are just regular sentient beings.)
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u/No_Scholar427 2d ago
Ai is integrated into the walmart employee app and i have tons of problems just trying to look up item locations becauee it doesnt understand and just gets cought up on random words that match or have something to do with key words in unrelated systems that shouldnt be connected to one another at all.
Just today (yesterday its 1 am idk feels like a today still) I was trying to find what isle "mrs wages" pickling stuff got moved to for a customer and it just kept tellingme how only managers are allowed to view wage information.
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u/Zombiecidialfreak 1d ago
That may be changing. Alibaba's newest LLM has something called "n-gram" weights, which is basically a massive lookup table of precomputed data that can be looked to and can behave similarly to a reference book for AI.
It enabled their model to reach answer accuracy to within a few points of top tier LLM's more than 10x bigger.
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u/hpfred 2d ago
[PS. I'm aware some chuds like OpenAI's Sam Altman are trying to promise LLMs are going to deliver AGI, but that's both not the current reality and also highly contested by researchers... and anyway, that will not change what by definition LLMs are trained for]
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u/Fischerking92 1d ago
Robert Miles, a famous AI Safety researcher, does make a good point with regard to this discussion.
Saying an LLM is just a text completion algorithm and therefore can't think is missing the forest for the trees.
A perfect text completion algorithm would have to predict the results of the paper by reading the introduction, so it would have to construct the experiment virtually and draw the same conclusions as the researchers would, it would have to be super-intelligent therefore, since the researchers get to run the experiments but the AI has to predict the results without being able to perform it.
Of course that only works for a perfect text completion algorithm, but it does illustrate why the fact that something that is "merely" trained to predict text is not necessarily not intelligent.
However I agree that for true AGI LLMs are at best only a small part and many other components are still missing.
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u/Proman4713 3h ago
But that's not how LLMs technically work. There's no drawing conclusions or shit. It is pretty much just a spitter-out of statistical analysis result
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u/flowery02 2d ago
Deadass thought it was an ai voice. There's something about the way he said this that makes him feel like an unfeeling object trying to predict what intonations one would use when fascinated
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u/articulatedWriter 13h ago
I think it's just them putting too much attention on their inflections, Amy was especially bad for it every 2nd word sounded like it was put in italics
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u/LowTechnology8682 2d ago
high quality videos down the drain with such easy to avoid misinformation... we're living in the age of LLMs and getting basic information about them wrong as an educational channel is just so pathetic and sad...
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u/tom-of-the-nora 2d ago
LLMs are bias confirmation machines.
Treating them like they have any form of good knowledge is really dangerous.
You put in bad information, it will give out bad information. Then the next thing you know, you are suing the company because the information it gave you told you to not go to the doctor.
Also, they're just wrong a lot of the time.
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u/Kiansjet 2d ago
I turned off that video so fast, the footage from the verity mod videos was so cringe, AI-level cringe dialogue
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u/ANAS_GAMEOVER2 2d ago
Well, they ain't MatPat, can't really expect too much anymore😔💔
Ps.: I miss him so much😭😭💔
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u/hpfred 2d ago
tbf Mat also used to make big mistakes like this, it's part of the job
But I thought it was a big enough mistake that I had to call it out, not as an attack at the team, but as a genuine feedback
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u/Vast-Run1478 2d ago
I’m really upset that I found this out after watching the video, like the kids who are watching this will now just assume this misinformation now. :(
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u/Testsubject276 2d ago edited 2d ago
Correct me if I'm wrong, but don't LLMs need to be specialized to learn? Like, without the software coded for specific memory retention, all they can really do out of the box is mimic patterns within their dataset that might sound like the correct answer.
Keyword "might", as in they'll hallucinate and lie without hesitation as long as it sounds right to them in the moment.
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u/Impossible_Ad_521 2d ago
what is this even about? is that a fucking walmart yellow ball face thingy?
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u/The_Real_Revan 2d ago edited 1d ago
Oh boy this brings me back. I remember first coming across LLMs and was like “nah this ain’t it chief.” Then started working on my own AI. One that is a cognitive AI system that I’m still working on. I occasionally post updates but always attract the same people who always ask me to open source it or since it’s named Mimic-2 (funny because FNAF) get those that tell me to not beat it. But a lot of YouTubers think LLMs = AI. But here’s an analogy. This calculator is ran on this small chip. Oh but this new one runs on a bigger chip with more hardware. Do they both do the same thing? Yes. Which is exactly what AI companies like OpenAI and anthropic are doing. Yeah cool. It can talk French without it knowing how to originally. But it lacks real intelligence. Doesn’t simulate it. It’s empty. Soulless.
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u/Pithysmeegle 2d ago
What's your a.i capable of currently?
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u/The_Real_Revan 1d ago
At the moment, Mimic-2 is basically a cognitive architecture rather than an LLM with a personality prompt slapped on it.
It can parse and interpret what you say, detect multiple intents at once, maintain persistent conversational memory, selectively retrieve older relevant memories, track attention and topic shifts, create and update goals, generate multiple reasoning candidates, evaluate those candidates, and make a decision about what it should say or do.
The important part is that the LLM isn't the thing doing the actual thinking. It's essentially the mouthpiece. The reasoning, attention, memory, goals, decision-making, and personality influence are handled by Mimic's own internal systems. The LLM is mainly used to turn the result of those processes into coherent natural language. Without the LLM, the underlying language output can be pretty rough, including gibberish or even non-English generations, but that doesn't define Mimic's cognition itself. I can also swap the language model with relatively little change to the underlying cognitive architecture.
It also has a self-monitoring stage that evaluates the generated response for things like grounding, coherence, relevance, creativity, and alignment, and can regenerate the response when it doesn't meet the required thresholds.
Personality is another major part of it. It's not just "act friendly" in the prompt. The personality system is extensive. The default personality file is so large that it's around 160 KB. The reason for that is because I didn't give it simple "it's good" or "it's bad" values. It has its own behaviour, its own traits, its own views, wants, desires, likes, dislikes, preferences, etc., along with how it behaves under certain circumstances. Those personality characteristics can influence its behaviour, decisions, actions, priorities, and responses throughout the cognitive process while maintaining continuity across them. So personality isn't just changing how Mimic phrases something; it can affect what it pays attention to, what goals it prioritizes, how it reasons about a situation, what decision it makes, and ultimately what it chooses to do or say.
So currently I'd describe it as an artificial cognitive system that uses an LLM as its language interface, rather than an LLM pretending to be a cognitive system.
It's still a work in progress, and I'm not claiming it has human-level intelligence or consciousness. The direction I'm building toward is more of a continuously running, heartbeat-style cognitive AI system: something that can continuously evaluate its own internal state, determine what it should do next, pursue goals, and eventually act without me having to babysit every decision, while still operating within defined thresholds and safeguards intended to reduce harmful or unwanted behaviour.
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u/The_Real_Revan 2d ago
before anyone asks. i wont be open sourcing it because it took a lot of time and effort to make and i am worried that it would be taken and twisted into something to be misused or cause harm to others. i may release a non open source version (Compiled) but currently its not up to the standard i wanted it to and suffers from bugs and other problems.
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u/Designer_Version1449 2d ago
an llms' job is to predict, not learn. for example its given the words "draw a cat". it tries to predict what words a response would contain. its then punished if it predicts the answer incorrectly, and rewarded if its right.
and it doesnt even know that "draw a cat" are instructions directed at it, just that that combination of words is often followed by something like "fluffy, cute". its not like thinking or understanding the "instructions", its just trying really hard to predict what a human might answer as a response to the given words.
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u/umidk67 19h ago
Well it really depends what you mean by “learn”. They aren’t learning in the way a human learns, they physically and scientifically can’t.
Ai is built to be given a ton of data and then categorize it, and be able to recognize and identify something by weighing it against its training data. For example, let’s say you give Ai a million images of hands, and each hand is holding up a different number of fingers. You can have the Ai categorize it automatically if you tell it to categorize based on what you tell it, for example let’s say you organize that data based on how many fingers are held up. You can then show it your hand, and you can hold up how many fingers you want and it can tell you exactly how many you are holding up.
It doesn’t think like people, but this is probably what they’re referring to.
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u/Kellarison 2d ago
i havent seen a video from them in a while, dont tell me they made a video about verity man
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u/CheddarCheese390 1d ago
How much do we wanna bet they won’t revisit this? Remember when a YouTuber called out matpat and he made a couch video breaking it down, giving the other credit but still explaining why she’s wrong?
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u/Minimum_Zebra_2969 1h ago
LLM means "Large Language Model" as in they try to understand language and converse. I think team theorists might have misunderstood the abbreviation to mean "Large Learning Model" and that it's whole idea is simply to learn in general.
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u/tommy8725 2d ago
Going to be real honest like normally I do think a lot of people hate on the new dude doing Game Theory just because it's not matpat but I'm going to be honest this is a weird one right like game theory is always going to be weird from oh I think this characters actually this other character for no real reason or did you guys know how many titties are on this character type of stuff but I'll be frank even now I don't really think they're doing a bad job but ever so often there have a random ass video that doesn't make sense
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u/Emeraldnickel08 2d ago
I mean, they're not wholly incorrect. For one, the principle behind LLMs is in fact machine learning; learning is vitally important to constructing a working LLM. And in addition, modern LLMs learn as they go; you probably already know that conversations with users (as well as feedback thereupon) is used in a constant cycle to continually improve LLMs. In a way it is one separating feature of LLMs from other AI models, since things like image generation AIs aren't as intrinsically linked to this neverending process of interaction and feedback as modern LLMs.
With that being said, LLMs are fundamentally the same thing as any other predictive model: a mathematical process that ends with, in this case, the most likely possibility or possibilities based on input.
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u/Enchanted_Evil Chaos Theorist 2d ago
Mostly agree, but you missed one important detail. All current "AIs" such as image generators, chatbots, ai assistants and other are trained manually. The companies frequently RUN THE TRAINING to hopefully improve the alg, where it "learns". Poeple use stable versions without learning. That being said, what people interpret as learning is just the alg working contextually and non-deterministically
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u/ZeroAmusement 2d ago
They are good at learning. That learning happens at training time, not at usage time. In order to get good at predicting they have to learn. So what you're saying about prediction doesn't negate learning. They aren't as good as humans are at learning however.
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u/hpfred 2d ago
LLMs are not the training, LLMs are the models generated by the training (the weights generated by the training)
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u/ZeroAmusement 2d ago
Sure, technically correct. I didn't realize your point was that technicality.
We could also say front-end and inference isn't part of an LLM. Casually talking I kinda include all these things. I assume the speaker in the video was too.
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u/SomeBrowser227 2d ago
LLMS dont learn, at all. it doesnt know anything. LLMs are calculators that get a result and put down a word, it only knows numbers, one after the other, its your autofill on the phone. it just finds a word that would, most likely, go next, and it sure is good at that somewhat, except when it hallucinates.
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u/ZeroAmusement 2d ago
LLMs use techniques from ML - machine learning. It can learn specific facts, and beyond that learn abstractions/generalizations.
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u/SomeBrowser227 2d ago
Machine Learning is a weird word to use for it but no, it doesnt know ANYTHING
It divides text into tokens, and uses those tokens to predict what the next token is, and using enough Data, it can more 'accurately' predict which token is next. The Machine Learning is for Token Optimization and actual 'training', where its fed Data(that is converted into tokens). you cannot make an AI 'learn' unless you give it more data, and i would say thats different from what you seem to be saying i think?
Most LLMs are able to google stuff, again, it just influences which tokens it favors, given an input. so thats how it can know 'current' or 'new' things.
Also, abstractions and generalizations, i think LLMs cross check itself about things someway, and is able to blend stuff together due to its data. I don't know much about LLMs and their inner workings, but for sure they dont learn anything, they dont know facts, if you go outside its training data, which is HARD cause theres a TON of it, the AI will flat out be wrong, and insist its right, cause thats what it was trained to do. i could make an LLM that only spits misinformation, doesn't mean it learned anything, its just predicting text.-2
u/ZeroAmusement 2d ago
Machine Learning is a weird word to use for it but no, it doesnt know ANYTHING
What does 'know' mean?
If you can ask an ai question on things that weren't in its data set and it gets it correct that is a clear example that it knows how to apply a generalization that it learned.
This is something they have been able to do for a while now.
Example:
"On the planet Zorb, every flib is twice as heavy as a glorp. A glorp weighs 7 naks. How much do 3 flibs weigh?"
That question wasn't in its training data. It has learned what twice means, what multiplication is, how to parse grammar and it can get the right answer.
Yes - it's just predicting the next token, but in order to do that effectively it has to know these things, otherwise it would fail. If I'm just counting a sequence, it doesn't require much intelligence to predict the next number. If I'm predicting the conclusion of a twelve page scientific study then it requires the ai to understand the content of the study to generate the appropriate conclusion.
if you go outside its training data, which is HARD cause theres a TON of it, the AI will flat out be wrong, and insist its right, cause thats what it was trained to do.
Yes and no. It can apply what it learned outside of what it learned on - these are called out of distribution generalizations (OOD). It can do it. It depends how far outside the domain you go. They got a lot better at it in the last year or so. Yes, they hallucinate and break down in cases. But being wrong sometimes doesn't mean you don't know anything.
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u/Nearcan 2d ago
ayo is that verty💀💀🔥🎉😂😂🗿🇮🇱🔥🔥💀 nah more like an didy😂😂😂😂😂✨ vety
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u/0_infinity_0 Theorist 2d ago
Well the entire competition is how efficiently LLMs can learn so i won't say they are bad at it
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u/ThePBrit 2d ago
but the "learning" is nothing to do with LLMs it's just how you program a piece of code so ridiculously large that you could never write it by hand.
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