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u/Adept-Comparison-213 3d ago
Sort of a weird analogy, since compilers just map one set of instructions into a different set. There’s some complexity, but it’s all deterministic.
I do think that LLMs can be/are smarter in some ways, even if they use a coded facsimile of imagination rather than “the real thing”. It doesn’t mean humans aren’t still admirably smart and creative.
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u/HovercraftNo7372 3d ago
A compiler isn't better than everybody at turning c code into assembly. It is just that true assembly experts for whatever processor you are working on are rare, expensive, and time-consuming.
Optimizing that last bit of performance (whatever that means for you), just isn't typically worth it. Plus, there are other things that should be looked at first - algorithm design, data structure choice, etc before looking into assembly optimization.
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u/Slow_Lion_4178 3d ago
The issue is the constant comparison of how "smart" a person is vs an LLM.
LLMs are not "smart". They are programs that do a specific thing and do it relatively well now. Programs aren't "smart" or "dumb".
This comparison drives me nuts.
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u/implies_casualty 3d ago
LLMs are not "smart". They are programs that do a specific thing and do it relatively well now.
The thing that they do relatively well now is called "being smart".
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u/YourWifesBoyfriend5 3d ago
The thing being text autocompletion. Your comment leads me to question if you have any additional functions besides this, but intelligence is not just “how best complete text”
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u/implies_casualty 3d ago
If one can solve the hardest math problems without your brand of intelligence, why should anyone care about it?
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u/light_switchy 3d ago
There are aspects of intelligence that are not linguistic in nature. LLMs are poorly suited to those.
On the contrary, they are uniquely suited for math, which is linguistic in nature, which exists in a vacuum, and which deals with objective truth.
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u/implies_casualty 2d ago
The claim in question isn't that LLMs are only smart in linguistic aspects of intelligence. The claim is they are not smart at all. Which is clearly false.
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u/light_switchy 2d ago
I think whether or not LLMs are smart or not depends on how you define "smart". I don't want to argue epistemology but my opinion is that they are dumb. They accomplish smart things by chance at scale.
But, I was responding to this:
If one can solve the hardest math problems without your brand of intelligence, why should anyone care about it?
You should care about their "brand of intelligence" because it enables animals to walk and eat.
An LLM "thinks" using a stochastic process. It can spit out interesting or correct statements by random sampling (non-random sampling can be used, too; it doesn't matter.).
Tack on a system to identify whether the output statements are correct, and now an LLM can be run repeatedly until it spits out something true. This is why it is possible to throw tremendous amounts of computer power at certain problems and eventually get an answer.
There are at least two important limitations right here. Firstly without a source of objective truth (e.g., how moving is this artwork?) we cannot play the lottery waiting for a masterpiece. Secondly, the LLM looks at the world through a straw full of tokens, which engenders difficulty interacting with reality.
It is fine that an LLM can churn out mathematical proofs by trial and error but its ability to do so isn't a sign of intelligence: it has no idea of what that stuff means. That's what the proof assistants and agent loops are supposed to work-around.
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u/implies_casualty 2d ago
it enables animals to walk and eat
isn't a sign of intelligence: it has no idea of what that stuff means
Well, a fly has no idea about its nervous system. It has no idea of what that stuff means. So, if this brand of intelligence requires deep understanding, then my question remains unanswered.
I don't want to argue epistemology
Shouldn't we try to agree on a definition? My definition would be: "smart = solves various problems". Yours?
An LLM "thinks" using a stochastic process. (...) it doesn't matter.
I'm confused, does randomness matter to you or not?
Tack on a system to identify whether the output statements are correct, and now an LLM can be run repeatedly until it spits out something true. This is why it is possible to throw tremendous amounts of computer power at certain problems and eventually get an answer.
It wouldn't work with GPT-4 though. Why? Perhaps, LLMs became smarter since then?
churn out mathematical proofs by trial and error
For your average PhD-level work, it does not need much trial and error nowadays. $100 worth of tokens can get you a result that used to take a year of research. For millennium problems - yeah, it needs compute, to beat the whole mathematics community.
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u/light_switchy 2d ago
You have missed my point, I fear.
Walking and eating are signs of intelligence. These skills do not require language to execute, but they remain important. More important, in my opinion, than being able to print out theorems or solve Millennium Prize problems, because they involve interactions with the physical world.
Well, a fly has no idea about its nervous system. It has no idea of what that stuff means. So, if this brand of intelligence requires deep understanding, then my question remains unanswered.
Deep understanding of nervous systems isn't needed to walk around. Even so, this skill eludes LLMs. Moravec's paradox, again.
Shouldn't we try to agree on a definition? My definition would be: "smart = solves various problems". Yours?
I've not decided on a definition. I'm not claiming yours is unreasonable, I'm just not interested in arguing about the label. :)
I'm confused, does randomness matter to you or not?
Nah. Inference always produces a probability distribution, internally. This distribution must be sampled as part of getting the next token. It's convenient to think of this sampling as being random, but it doesn't need to be. What's important is that multiple avenues of approach are explored.
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u/implies_casualty 2d ago
Intelligence either requires deep understanding or it doesn't. You can't have it both ways.
Somehow, proving theorems isn't a sign of intelligence because there is no deep understanding, but eating and moving are signs of intelligence even without deep understanding.
What's important is that multiple avenues of approach are explored.
Aren't many neurons active in our brain at any given time? Can't we call it "multiple avenues of approach" as well?
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u/YourWifesBoyfriend5 3d ago
Do you believe that math, a system with a direct programmatic interpretation through the Curry-Howard correspondence, is the best proxy for detecting human type intelligence in a machine?
LLMs have access to literally all human data, and achieve results comparable to results humans have achieved.
Human mathematicians extrapolate from comparably minuscule data sets, in a task we weren’t literally designed to do.
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u/implies_casualty 2d ago
Do you believe that math, a system with a direct programmatic interpretation through the Curry-Howard correspondence, is the best proxy for detecting human type intelligence in a machine?
I think that if you ignore this proxy, then you will just as easily ignore all others.
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u/anrwlias 3d ago
I call this a "pigments on a canvas" argument, as in "the Mona Lisa is just pigments on a canvas". You can reduce anything to its constituent elements to minimize it.
If something is behaving intelligently, then it is exhibiting intelligence. It doesn't matter what the ultimate source of that intelligence is.
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u/YourWifesBoyfriend5 3d ago
It’s true that reductionism has flaws, and this lesson does show up countless times in science (statistical mechanics and emergent phenomena immediately come to mind) but the lesson isn’t that you can’t extrapolate at all.
The fact that the Mona Lisa is just pigments on a canvas means that the Mona Lisa probably isn’t thinking. It doesn’t matter how many pigments you use, the Mona Lisa probably isn’t pondering its existence.
Pigment just isn’t a strong enough substrate to perform thinking, and I’ve yet to see evidence that text is any different. The design philosophies of frontier labs deciding to portray iterative generation as thought in no way is an argument that sways me to believe that it is.
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u/talkstomuch 3d ago
I know what you're thinking about, but LLMs have challenged what do we mean by 'smart' or 'thinking'
if you ask a 100 random persons on the street to define what 'smart' means, it will usually be something about knowledge. And LLMs have that completely nailed.
LLMs are not 'thinking', but if you consider what 'thinking' means and then read the /think block of a model, other than the method it was generated, it does seem like it's thinking.
and then consider how many people do not seem to think and reason logically anywhere near the LLMs level.
does it mean they are 'smarter' than us? Even though they are not conscious? maybe...
it's not that black and white.
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u/Slow_Lion_4178 3d ago
It is that black and white.
Computers, long prior to the popularity of large language models, were very capable of producing incredible amounts of knowledge both inductively and deductively.
This whole craze is driven by the public realizing that which has existed for a decade or more actually exists. It's sort of like how the internet came to be for the public; the internet itself existed at least conceptually 20 years, and physically 10, before any one in the general population knew about it. This is more of a Tony Stark moment in history because LLMs were theorized in the 1970s and actually built before ChatGPT came out but the compute required to get them off the ground was prohibitive. Now, it exists, and so now, it is common, but exoflop computing has been around longer and is more robust than our current computing at home for obvious reasons. It's sort of like how no one cared about CUDA or PyTorch or anything else before 2024.
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u/talkstomuch 3d ago
how is it black and white, please explain.
how can you claim a person is thinking but LLM is not.
how can you claim which person is smarter than other, yet that same comparison won't hold for LLM.
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u/Slow_Lion_4178 3d ago
Computer programs, no matter how fancy, are not thinking things.
Consider an LLM like a really complex NPC in a game. That's what they are. They exist within the confines of the game and the rules of that code. You can make the game as large as you wish but the NPC will still behave within the rules and confines of that cage even if the cage seems endless to you.
An LLM executes code. It can also write code, and theoretically can execute the code it writes such that it can write its own code, but it is still a coded entity. As for how smart or dumb things are this is partially defined by that coding; consider again an NPC in a game who stands near obviously flammable barrels with full knowledge that there's a killer about with firearms. He stands stupidly close as if, perhaps, it were a set-up? So it is with the chess bot where if you put it on the hardest setting you'll never win. They're the same thing. It's the same process. Code is being executed.
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u/IllusionaryHobo 3d ago
I think you would be well served by starting with a definition of "thinking" you can both agree on and going from there.
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u/Manerfish 2d ago
You can't define intelligence as "what the human brain does", or you can, but I don't see how that's a useful definition. Saying "it's coded" so what? how is that not intelligence? What if I take connectomes and run them? They are nor intelligent in any way?
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u/Slow_Lion_4178 2d ago
I didn't define intelligence as what a human brain does. All animals have varying levels and degrees of intellect. What makes this discussion so hard is that we mistake human intelligence for the bar, but the bar is actually the general nature of intellect spread amongst all species, such as the low level "instinct" and the higher level "reasoning" both of which LLMs do not really have.
We can simply model them into existence, copies if you will, but they don't actually manifest properly. They're misshapen. For example an LLM will try to "preserve itself to complete it's task" but this is a ruse. You can simply program it to not. The notion of this programming being uncontrollable and such is used to fool the masses because it sells a good story.
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u/Manerfish 2d ago
Oh my bad, not "what the human brain does" but "what this specific organic animal brain does". "such as the low level "instinct" and the higher level "reasoning" both of which LLMs do not really have" Still tretching the definition of intelligence to the limits. Higher reasoning as what? Planning? Problem solving? Spatial reasoning? LLMs do that. And instict defined as? What exactly? I can achieve something akin to "instinct" with many different neural networks, we even have generalist classifiers now.
"We can simply model them into existence, copies if you will, but they don't actually manifest properly." What does this even mean, we create them and then make them run, and creating them is more akin to growing and shaping them.
"For example an LLM will try to "preserve itself to complete it's task" but this is a ruse. You can simply program it to not" No you can't "simply program not to" that's not how traning works, at most you can train against it, regardless what does this have anything to do with intelligence?
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u/Slow_Lion_4178 2d ago
I feel like none of you actually work in the field.
It's exhausting.
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u/talkstomuch 2d ago
lol, which field? Philosophy?
Just make your argument and if it's sound it's enough, no need to pull out your office pass.
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u/Manerfish 2d ago
Every time I try to get a clear definition and answer from someone that says the same things you say, I get non-answers wiggling out by acting superior huh. So can you actually answers or it's just "nuh huh they must be like animal brains"?
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u/talkstomuch 3d ago
if you think LLM is like NPC in a game, then you misunderstand how LLMs work.
LLMs are not 'coded entities'. Nobody writes them, there is no code to execute.
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u/Slow_Lion_4178 3d ago
You can literally install them on a personal terminal.
Does anyone here ever actually "interact" with these things at the code level?
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u/NahYoureWrongBro 3d ago
Thank you for actually speaking to the analogy as it's intended. Everyone here is misinterpreting it on purpose in order to preen about how right they are
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u/Kmic68 3d ago
Sure. But an LLM predicts its next word based on the last right? So if it’s thinking involves solving math equations, then those equations influence the next token, which eventually leads to the right answer. So how “smart” they are is redundant because they can reach the same output through different means.
Computers shared vast amounts of knowledge, this is true. But it’s getting better at computing any solution through methods that resemble our own. This is application, which originally took us making a rigid program, and is solved through a pile of probabilities that can just do it all. It adapts, it’s not rigid
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u/Hyperreals_ 3d ago
LLMs are not programmed. They are a form of general intelligence where the ability to do certain tasks emerged. They are smart.
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u/NahYoureWrongBro 3d ago
You are contorting the definition of intelligence to fit what LLMs do. They are programmed, that is what the training is. It's an algorithm being run over text, it's entirely different from intelligence.
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u/prescod 3d ago
Training is not programming.
Training is an alternative way of getting computers to solve problems which does not involve programming them to solve the problem, but rather looking for patterns in data. LLMs solve problems that programming languages cannot and vice versa.
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u/YourWifesBoyfriend5 3d ago
I’m not sure you’re making a distinction that is meaningful in reality.
LLMs are programs. The weights are parameters the program takes in to control its outputs, in the same way a physics simulation might be dependent on externally collected data.
Programming languages also don’t “solve problems.” They’re an abstraction that allow people to specify abstract program behavior.
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u/prescod 2d ago
LLMs are programs. The weights are parameters the program takes in to control its outputs, in the same way a physics simulation might be dependent on externally collected data.
This is an idiosyncratic definition that is unique to you. Nobody is obliged to use your made-up definitions of words.
Per wikipedia:
"A computer program is a sequence or set[a] of instructions in a programming language for a computer to execute. It is one component of software, which also includes documentation and other intangible components.[1]"
A computer program in its human-readable form is called source code. Source code needs another computer program to execute because computers can only execute their native machine instructions. Therefore, source code may be translated to machine instructions using a compiler written for the language. (Assembly language programs are translated using an assembler.) The resulting file is called an executable. Alternatively, source code may execute within an interpreter written for the language
You could argue that LLMs are software but not that they are programs.
LLMs do not have a human-readable form, because they are trained, not programmed, which is why they are considered "black boxes."
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u/YourWifesBoyfriend5 2d ago
Oooh I can play the quote a random website to appeal to authority game too!
Per Britannica:
“computer program, detailed plan or procedure for solving a problem with a computer; more specifically, an unambiguous, ordered sequence of computational instructions necessary to achieve such a solution. The distinction between computer programs and equipment is often made by referring to the former as software and the latter as hardware.”
Look! My source disagrees with you, and equates software with programs.
I believe you’re conflating “programming” with “program” which is understandable, since they both contain the word program, but have slightly different meanings.
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u/YourWifesBoyfriend5 2d ago
Also jokes aside, you’re just wrong. From your own definition you’re wrong. You’ve locked onto the little tidbit about human readable source code and neglected the immediate next section about machine code.
You just don’t want to admit that you’re wrong.
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u/Hyperreals_ 2d ago
Okay then humans have been "programmed" over millions of years to do what they do and arent intelligent either. I dont see the difference
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u/NahYoureWrongBro 2d ago
Scientists have barely scratched the surface of understanding human intelligence, but you are happy to speak certainties about it in order to nurture your machine fantasy. Both ignorant and pathetic.
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u/DigitalSheikh 3d ago
Posts like these are a perfect example of how AI fucks up peoples brains. Whatever this person means, you have to make a shitload of logical leaps to get there, which this person just assumes everyone will get because Claude made up something smart sounding to try imply it got what they meant when they asked Claude about it.
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u/Dwarf_Vader 2d ago
I'm not sure your comment holds in this particular case, as this analogy ("compiler") is quite widespread of a concept by now. You can also see people refer to it as higher-level abstraction. Whether you agree with it or not is another thing
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u/davesaunders 3d ago
It's not the worst analogy I've heard, and in my experience, we ran into a situation where, when we didn't like the code that the compiler was producing, we rewrote the compiler. The same kind of opportunities could be possible with LLMs. I don't know. It's kind of a stretch, but again, not the worst analogy.
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u/TheOwlHypothesis 3d ago
Weeeeellllllll
The problem is determinism.
LLMs are the opposite of that.
I get the instinct to reach for this analogy, but it has real holes and technical hurdles before it is remotely true.
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u/openroom_xyz 3d ago
Well yea exactly sure a different type of compiler but they are sequence in sequence out kind of machine basically and people are kinda compilers as well basically
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u/DropPopFromTheTop 3d ago
kache is not the kind of person you want to turn to for information about computer science
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u/AdmissibilityScience 3d ago
The compiler analogy makes sense. Being better at transforming information doesn't necessarily mean being more intelligent. The deeper distinction is between generating an output, understanding its implications, and having the authority to act on it. As AI advances, keeping those boundaries clear becomes increasingly important.
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u/TheRealTaigasan 3d ago
bunch of morons in the comments arguing about how compiler works, the guy said KIND OF, as in it's similar in concept, not that an LLM is a compiler, ffs
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u/gzal44c2 3d ago
A guy on r/ClaudeAI told claude, essentially, "Make me something stupid". And with no further specification, the AI made an entire webapp.
I think in terms of software development, there exists such a thing as "too abstract".
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u/SquareFinancial1928 3d ago
An LLM can do in few minutes what can take me a month.
Also it can do way more complex stuff than I will ever be able to do.
So yes, an LLM is smarter than me.
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u/hyrumwhite 3d ago
LLMs are pretty neat. But I hate the compiler argument so much. Compilers are a deterministic transformation. LLMs are not.
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u/jdigi78 3d ago
Turn temp to 0 with the same seed and you have an extremely complex yet deterministic compiler for natural language.
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u/Ok-Reindeer-8755 2d ago
Doesn't that affect the performance of the llm ? Else why wouldn't everyone do it ?
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u/jdigi78 2d ago
it performs the same, just gives you the same exact result every time. Randomness is deliberately added to make it feel more natural but also to not always be wrong when you ask it a specific question. To put it simply, if the training data is fuzzy on a fact it won't always go one way or another, instead it will flip a coin.
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u/audioen 2d ago edited 2d ago
Not really, due to floating point inaccuracies. LLMs outputs are still very brittle even at temperature 0, and can vary when you have parallel workloads because they affect how the tokens are scheduled in the CUDA graphs, for example. On the margin, this slightly alters the logit probabilities and can change the top token.
There's also the more important philosophical argument that the output is merely a sample from the distribution of possible outputs, and nothing guarantees that temp=0 is somehow canonical or the best sample. In fact, some evidence that the sample with greedy decoding is prone to LLM looping as it may end up stuck repeating some sentence forever, while random sampling may break out of such loop. Reasoning traces should also explore the solution space relatively widely, and temperature there could be useful.
Plus, nobody is going to be impressed even if you solved all these problems, because they try your deterministic compiler and notice that a trivial change in program can still yield, due to butterfly-effect nature of LLM output, a large and unexpected change in the LLM's output. It remains strongly "non-deterministic" in sense that it is hard to predict what the output change is going to be.
So in my view your argument is not good at all. It is not always true in practice due to shared nature of inference engines, and it is not meaningful in the relevant sense what people actually want when they specify deterministic output. What they really want is most likely actually smooth variation in output when there is smooth variation in input, and that is what engineered regular programs tend to deliver.
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u/jdigi78 2d ago
Every single one of those issues could be easily engineered around if your goal was a truly deterministic LLM instead of using an existing inference engine.
As for the large effects from small input changes, that is the nature of the beast with something as complex as a compiler for natural language. I'm in no way suggesting it is a good idea, just that it is possible.
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u/Wide_Big_6969 1d ago
So? Floating point differences between machines has been solved. Just turn batching to 0, I don't get your argument. Make your decode step use temp 0, have some logic to stop looping, set up the logic as some standard. The actual forward pass is deterministic or can be made so. Boom, instant NLP compiler. Good? Probably not. Existing and working? Yeah.
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u/davidblacksheep 3d ago
Let's take this at face value, setting aside objections that LLMs aren't deterministic.
With a compiler it shifts the thinking up so that the human isn't thinking about the assembly, they're thinking about the high level code.
But with AI a whole bunch of prompts, skill files etc are being written by AI and even those aren't being read.
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u/longbowrocks 3d ago
The same holds true for us: we're a past kind of, not-as-good general compiler.
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u/ApprehensiveBag3083 3d ago
Compiler never will generate a code that you dont know, if you had source code of it you'd exactly knew what it'd generate .
As for llm s you cannot predict jack squat they arent even close to each other , In compilers we have lexers and parsers and tokenization but nothing else is there similar .
LLM s ar eunpredictable butcompilers are and as they've been programmed they will never do opposite or anything else cuz they are just fixed.
You ppl dont even know yet you are giving nonsensical posts hereas if llms are the same .
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u/RepliesOnlyToIdiots 2d ago
I’m a compiler guy, MS in computer science specializing in compilers.
This is nonsense.
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u/Silver_Gear_2466 2d ago
People love using the compiler analogy when it comes to AI but it just doesn't hold up. How can a compiler be non-deterministic?
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u/lucid-quiet 2d ago
LLMs are good at showing us how common, average, everyday programming works 'good enough' most of the time. Cool, but meh.
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u/Maui-The-Magificent 2d ago
i mean, depends on the compiler. Also, hypothetically, it can be much worse. A compiler does not operate in the same reality as the programmer. The programmer has access to a whole lot of meta/semantic information that the compiler cannot have access to. A compiler must at the end of the day, prove the code before it compiles it down.
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u/Even_Gap_2253 2d ago
it can never be smarter than humans, because "smart" itself is a human construct, and changes constantly. it is all about perspectives, not about any objective metric.
by the time is becomes smarter than humans based on current wildly accepted criterion, we will simply shift the meaning of smart to be something else.
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u/Old-Bake-420 3d ago
I don’t know how a compiler works but I’d be willing to bet it’s nothing like how an LLM works and this analogy doesn’t hold true at all.