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A non-anthropomorphized view of LLMs

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Re: A non-anthropomorphized view of LLMs

#341

Post by lawlessone »

mvieira38 wrote: post #334
meroes wrote: post #327

Earlier quoted context omitted.

> there exists a string of words (not necessary ones that make sense) that will get the LLM to a better position to answer exactly. The opposite is also true. You might supply more clarifying information to the LLM, which would help any human answer, but it actually degrades the LLM's output.

This is frequently the case IME, especially with chat interfaces. One or two bad messages and you derail the quality

You can just throw in words to bias it towards certain outcomes too. Same applies with image generators or course.

Re: A non-anthropomorphized view of LLMs

#342

Post by suddenlybananas »

ants_everywhere wrote: post #262
seadan83 wrote: post #130

Earlier quoted context omitted.

> It is similar to how human brains operate. Is it? Do we know how human brains operate? We know the basic architecture of them, so we have a map, but we don't know the details. "The cellular biology of brains is relatively well-understood, but neuroscientists have not yet generated a theory explaining how brains work. Explanations of how neurons collectively operate to produce what brains can do are tentative and in…

The part I was referring to is captured in "The cellular biology of brains is relatively well-understood" Fundamentally, brains are not doing something different in kind from ANNs. They're basically layers of neural networks stacked together in certain ways. What we don't know are things like (1) how exactly are the layers stacked together, (2) how are the sensors (like photo receptors, auditory receptors, etc) hooke…

ANNs don't have action potentials, let alone neurotransmitters.

Re: A non-anthropomorphized view of LLMs

#343

Post by ordu »

grey-area wrote: post #120
Al-Khwarizmi wrote: post #117

I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent. The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing…

On the contrary, anthropomorphism IMO is the main problem with narratives around LLMs - people are genuinely talking about them thinking and reasoning when they are doing nothing of that sort (actively encouraged by the companies selling them) and it is completely distorting discussions on their use and perceptions of their utility.

> On the contrary, anthropomorphism IMO is the main problem with narratives around LLMs

I hold a deep belief that anthropomorphism is a way the human mind words. If we take for granted the hypothesis of Franz de Waal, that human mind developed its capabilities due to political games, and then think about how it could later lead to solving engineering and technological problems, then the tendency of people to anthropomorphize becomes obvious. Political games need empathy or maybe some other kind of -pathy, that allows politicians to guess motives of others looking at their behaviors. Political games directed the evolution to develop mental instruments to uncover causality by watching at others and interacting with them. Now, to apply these instruments to inanimate world all you need is to anthropomorphize inanimate objects.

Of course, it leads sometimes to the invention of gods, or spirits, or other imaginary intelligences behinds things. And sometimes these entities get in the way of revealing the real causes of events. But I believe that to anthropomorphize LLMs (at the current stage of their development) is not just the natural thing for people but a good thing as well. Some behavior of LLMs is easily described in terms of psychology; some cannot be described or at least not so easy. People are seeking ways to do it. Projecting this process into the future, I can imagine how there will be a kind of consensual LLMs "theory" that explains some traits of LLMs in terms of human psychology and fails to explain other traits, so they are explained in some other terms... And then a revolution happens, when a few bright minds come and say that "anthropomorphism is bad, it cannot explain LLM" and they propose something different.

I'm sure it will happen at some point in the future, but not right now. And it will happen not like that: not just because someone said that anthropomorphism is bad, but because they proposed another way to talk about reasons behind LLMs behavior. It is like with scientific theories: they do not fail because they become obviously wrong, but because other, better theories replace them.

It doesn't mean, that there is no point to fight anthropomorphism right now, but this fight should be directed at searching for new ways to talk about LLMs, not to show at the deficiencies of anthropomorphism. To my mind it makes sense to start not with deficiencies of anthropomorphism but with its successes. What traits of LLMs it allows us to capture, which ideas about LLMs are impossible to wrap into words without thinking of LLMs as of people?

Re: A non-anthropomorphized view of LLMs

#344

Post by [deleted] »

Angostura wrote: post #34
cmiles74 wrote: post #15

Earlier quoted context omitted.

IMHO, anthrophormization of LLMs is happening because it's perceived as good marketing by big corporate vendors. People are excited about the technology and it's easy to use the terminology the vendor is using. At that point I think it gets kind of self fulfilling. Kind of like the meme about how to pronounce GIF.

IMHO it happens for the same reason we see shapes in clouds. The human mind through millions of years has evolved to equate and conflate the ability to generate cogent verbal or written output with intelligence. It's an instinct to equate the two. It's an extraordinarily difficult instinct to break. LLMs are optimised for the one job that will make us confuse them for being intelligent

[deleted]

Re: A non-anthropomorphized view of LLMs

#345

Post by 0x457 »

loxs wrote: post #200
cmenge wrote: post #126

Earlier quoted context omitted.

I kinda agree with both of you. It might be a required abstraction, but it's a leaky one. Long before LLMs, I would talk about classes / functions / modules like "it then does this, decides the epsilon is too low, chops it up and adds it to the list". The difference I guess it was only to a technical crowd and nobody would mistake this for anything it wasn't. Everybody know that "it" didn't "decide" anything. With AI…

We can argue all day what "think" means and whether a LLM thinks (probably not IMO), but at least in my head the threshold for "decide" is much lower so I can perfectly accept that a LLM (or even a class) "decides". I don't have a conflict about that. Yeah, it might not be a decision in the human sense, but it's a decision in the mathematical sense so I have always meant "decide" literally when I was talking about a…

Well, it outputs a chain of thoughts that later used to produce better prediction. It produces a chain of thoughts similar to how one would do thinking about a problem out loud. It's more verbose that what you would do, but you always have some ambient context that LLM lacks.

Re: A non-anthropomorphized view of LLMs

#346

Post by marviel »

grey-area wrote: post #120
Al-Khwarizmi wrote: post #117

I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent. The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing…

On the contrary, anthropomorphism IMO is the main problem with narratives around LLMs - people are genuinely talking about them thinking and reasoning when they are doing nothing of that sort (actively encouraged by the companies selling them) and it is completely distorting discussions on their use and perceptions of their utility.

how do you account for the success of reasoning models?

I agree these things don't think like we do, and that they have weird gaps, but to claim they can't reason at all doesn't feel grounded.

Re: A non-anthropomorphized view of LLMs

#347

Post by godelski »

grey-area wrote: post #120
Al-Khwarizmi wrote: post #117

I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent. The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing…

On the contrary, anthropomorphism IMO is the main problem with narratives around LLMs - people are genuinely talking about them thinking and reasoning when they are doing nothing of that sort (actively encouraged by the companies selling them) and it is completely distorting discussions on their use and perceptions of their utility.

Serendipitous name...

In part I agree with the parent.

  >> it pointless to *not* anthropomorphize, at least to an extent.
I agree that it is pointless to not anthropomorphize because we are humans and we will automatically do this. Willingly or unwillingly.

On the other hand, it generates bias. This bias can lead to errors.

So the real answer is (imo) that it is fine to anthropomorphise but recognize that while doing so can provide utility and help us understand, it is WRONG. Recognizing that it is not right and cannot be right provides us with a constant reminder to reevaluate. Use it, but double check, and keep checking making sure you understand the limitations of the analogy. Understanding when and where it applies, where it doesn't, and most importantly, where you don't know if it does or does not. The last is most important because it helps us form hypotheses that are likely to be testable (likely, not always. Also, much easier said than done).

So I pick a "grey area". Anthropomorphization is a tool that can be helpful. But like any tool, it isn't universal. There is no "one-size-fits-all" tool. Literally, one of the most important things for any scientist is to become an expert at the tools you use. It's one of the most critical skills of *any expert*. So while I agree with you that we should be careful of anthropomorphization, I disagree that it is useless and can never provide information. But I do agree that quite frequently, the wrong tool is used for the right job. Sometimes, hacking it just isn't good enough.

Re: A non-anthropomorphized view of LLMs

#348

Post by tliltocatl »

criddell wrote: post #339
tliltocatl wrote: post #196

Earlier quoted context omitted.

Anthropomorphising implicitly assumes motivation, goals and values. That's what the core of anthropomorphism is - attempting to explain behavior of a complex system in teleological terms. And prompt escapes make it clear LLMs doesn't have any teleological agency yet. Whenever their course of action is, it is to easy to steer them of. Try to do it with a sufficiently motivated human.

How will you know when an AI has teleological agency?

Prompt escapes will be much harder, and some of them will end up in an equivalent of "sure here is… no, wait… You know what, I'm not doing that", i. e. slipping and then getting back on track.

Re: A non-anthropomorphized view of LLMs

#349

Post by ryeats »

flir wrote: post #154
cmenge wrote: post #126

Earlier quoted context omitted.

I kinda agree with both of you. It might be a required abstraction, but it's a leaky one. Long before LLMs, I would talk about classes / functions / modules like "it then does this, decides the epsilon is too low, chops it up and adds it to the list". The difference I guess it was only to a technical crowd and nobody would mistake this for anything it wasn't. Everybody know that "it" didn't "decide" anything. With AI…

Agreeing with you, this is a "can a submarine swim" problem IMO. We need a new word for what LLMs are doing. Calling it "thinking" is stretching the word to breaking point, but "selecting the next word based on a complex statistical model" doesn't begin to capture what they're capable of. Maybe it's cog-nition (emphasis on the cog).

It's more like muscle memory than cognition. So maybe procedural memory but that isn't catchy.

Re: A non-anthropomorphized view of LLMs

#350

Post by godelski »

Wowfunhappy wrote: post #314
fenomas wrote: post #143

Earlier quoted context omitted.

When I see these debates it's always the other way around - one person speaks colloquially about an LLM's behavior, and then somebody else jumps on them for supposedly believing the model is conscious, just because the speaker said "the model thinks.." or "the model knows.." or whatever. To be honest the impression I've gotten is that some people are just very interested in talking about not anthropomorphizing AI, an…

As I write this, Claude Code is currently opening and closing various media files on my computer. Sometimes it plays the file for a few seconds before closing it, sometimes it starts playback and then seeks to a different position, sometimes it fast forwards or rewinds, etc. I asked Claude to write a E-AC3 audio component so I can play videos with E-AC3 audio in the old version of QuickTime I really like using. Claud…

Would it help you to know that trial and error is a common tactic by machines? Yes, humans do it too, but that doesn't mean the process isn't mechanical. In fact, in computing we might call this a "brute force" approach. You don't have to cover the entire search space to brute force something, and it certainly doesn't mean you can't have optimization strategies and need to grid search (e.g. you can use Bayesian methods, multi-armed bandit approaches, or a whole world of things).

I would call "fuck around and find out" a rather simple approach. It is why we use it! It is why lots of animals use it. Even very dumb animals use it. Though, we do notice more intelligent animals use more efficient optimization methods. All of this is technically hypothesis testing. Even a naive grid search. But that is still in the class of "fuck around and find out" or "brute force", right?

I should also mention two important things.

1) as a human we are biased to anthropomorphize. We see faces in clouds. We tell stories of mighty beings controlling the world in an effort to explain why things happen. This is anthropomorphization of the universe itself!

2) We design LLMs (and many other large ML systems) to optimize towards human preference. This reinforces an anthropomorphized interpretation.

The reason for doing this (2) is based on a naive assumption[0]: If it looks like a duck, swims like a duck, and quacks like a duck, then it *probably* is a duck. But the duck test doesn't rule out a highly sophisticated animatronic. It's a good rule of thumb, but wouldn't it also be incredibly naive to assume that it *is* a duck? Isn't the duck test itself entirely dependent on our own personal familiarity with ducks? I think this is important to remember and can help combat our own propensity for creating biases.

[0] It is not a bad strategy to build in that direction. When faced with many possible ways to go, this is a very reasonable approach. The naive part is if you assume that it will take you all the way to making a duck. It is also a perilous approach because you are explicitly making it harder for you to evaluate. It is, in the fullest sense of the phrase, "metric hacking."

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