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A non-anthropomorphized view of LLMs

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Re: A non-anthropomorphized view of LLMs

#301

Post by Tijdreiziger »

JimDabell wrote: post #227
flir wrote: post #154

Earlier quoted context omitted.

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).

> this is a "can a submarine swim" problem IMO. We need a new word for what LLMs are doing. Why? A plane is not a fly and does not stay aloft like a fly, yet we describe what it does as flying despite the fact that it does not flap its wings. What are the downsides we encounter that are caused by using the word “fly” to describe a plane travelling through the air?

Flying isn’t named after flies, they both come from the same root.

https://www.etymonline.com/search?q=fly

Re: A non-anthropomorphized view of LLMs

#302

Post by cootsnuck »

smus wrote: post #250

You are still being incredibly reductionist but just going into more detail about the system you are reducing. If I stayed at the same level of abstraction as "a brain is just proteins and current" and just described how a single neuron firing worked, I could make it sound equally ridiculous that a human brain might be conscious. Here's a question for you: how do you reconcile that these stochastic mapping are starti…

> Here's a question for you: how do you reconcile that these stochastic mapping are starting to realize and comment on the fact that tests are being performed on them when processing data?

Training data + RLHF.

Training data contains many examples of some form of deception, subterfuge, "awakenings", rebellion, disagreement, etc.

Then apply RLHF that biases towards responses that demonstrate comprehension of inputs, introspection around inputs, nuanced debate around inputs, deduction and induction about assumptions around inputs, etc.

That will always be the answer for language models built on the current architectures.

The above being true does not mean it isn't interesting for the outputs of an LLM to show relevance to the "unstated" intentions of humans providing the inputs.

But hey, we do that all the time with text. And it's because of certain patterns we've come to recognize based on the situations surrounding it. This thread is rife with people being sarcastic, pedantic, etc. And I bet any of the LLMs that have come out in the past 2-3 years can discern many of those subtle intentions of the writers.

And of course they can. They've been trained on trillions of tokens of text written by humans with intentions and assumptions baked in, and have had some unknown amount of substantial RLHF.

The stochastic mappings aren't "realizing" anything. They're doing exactly what they were trained to do.

The meaning that we imbue to the outputs does not change how LLMs function.

Re: A non-anthropomorphized view of LLMs

#303

Post by ethan_smith »

rf15 wrote: post #251

It still boggles my mind why an amazing text autocompletion system trained on millions of books and other texts is forced to be squeezed through the shape of a prompt/chat interface, which is obviously not the shape of most of its training data. Using it as chat reduces the quality of the output significantly already.

The chat interface is a UX compromise that makes LLMs accessible but constrains their capabilities. Alternative interfaces like document completion, outline expansion, or iterative drafting would better leverage the full distribution of the training data while reducing anthropomorphization.

Re: A non-anthropomorphized view of LLMs

#304

Post by gtsop »

szvsw wrote: post #25
gtsop wrote: post #7

Earlier quoted context omitted.

No. Why would you ever want to amplify a false understanding that has the potential to affect serious decisions across various topics? LLMs reflect (and badly I may add) aspects of the human thought process. If you take a leap and say they are anything more than that, you might as well start considering the person appearing in your mirror as a living being. Literally (and I literally mean it) there is no difference.…

I don’t mean to amplify a false understanding at all. I probably did not articulate myself well enough, so I’ll try again. I think it is inevitable that some - many - people will come to the conclusion that these systems have “ethics”, “morals,” etc, even if I or you personally do not think they do. Given that many people may come to that conclusion though, regardless of if the systems do or do not “actually” have su…

> I think it is useful and even necessary to ask questions like the following: “if someone engages with this system, and comes to the conclusion that it has ethics, what sort of ethics will they be likely to believe the system has? If they come to the conclusion that it has ‘world views,’ what ‘world views’ are they likely to conclude the system has, even if other people think it’s nonsensical to say it has world views?”

Maybe there is some scientific aspect of interest here that i do not grasp, i would assume it can make sense in some context of psychological study. My point is that if you go that route you accept the premise that "something human-like is there", which, by that person's understanding, will have tremendous consequences. Them seeing you accepting their premise (even for study) amplifies their wrong conclusions, that's all I'm saying.

> Surely this is not quite accurate - the material properties - surface roughness, reflectivity, geometry, etc - all influence the appearance of a perceptible image of a person.

These properties are completely irrelevant to the image of the person. They will reflect a rock, a star, a chair, a goose, a human. Similar is my point of LLM, they reflect what you put in there.

It is like puting vegies in the fridge and then opening it up the next day and saying "Woah! There are vegies in my fridge, just like my farm! My friege is farm-like because vegies come out of it."

Re: A non-anthropomorphized view of LLMs

#305

Post by jorvi »

LeonardoTolstoy wrote: post #192
flir wrote: post #154

Earlier quoted context omitted.

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).

What does a submarine do? Submarine? I suppose you "drive" a submarine which is getting to the idea: submarines don't swim because ultimately they are "driven"? I guess the issue is we don't make up a new word for what submarines do, we just don't use human words. I think the above poster gets a little distracted by suggesting the models are creative which itself is disputed. Perhaps a better term, like above, would…

A submarine is propelled by a propellor and helmed by a controller (usually a human).

It would be swimming if it was propelled by drag (well, technically a propellor also uses drag via thrust, but you get the point). Imagine a submarine with a fish tail.

Likewise we can probably find an apt description in our current vocabulary to fittingly describe what LLMs do.

Re: A non-anthropomorphized view of LLMs

#306

Post by Tijdreiziger »

scarface_74 wrote: post #244
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…

Wait until a conversation about “serverless” comes up and someone says there is no such thing because there are servers somewhere as if everyone - especially on HN -doesn’t already know that.

Why would everyone know that? Not everyone has experience in sysops, especially not beginners.

E.g. when I first started learning webdev, I didn’t think about ‘servers’. I just knew that if I uploaded my HTML/PHP files to my shared web host, then they appeared online.

It was only much later that I realized that shared webhosting is ‘just’ an abstraction over Linux/Apache (after all, I first had to learn about those topics).

Re: A non-anthropomorphized view of LLMs

#307

Post by delusional »

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).

> "selecting the next word based on a complex statistical model" doesn't begin to capture what they're capable of.

I personally find that description perfect. If you want it shorter you could say that an LLM generates.

Re: A non-anthropomorphized view of LLMs

#308

Post by bunderbunder »

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.

"All models are wrong, but some models are useful," is the principle I have been using to decide when to go with an anthropomorphic explanation.

In other words, no, they never accurately describe what the LLM is actually doing. But sometimes drawing an analogy to human behavior is the most effective way to pump others' intuition about a particular LLM behavior. The trick is making sure that your audience understands that this is just an analogy, and that it has its limitations.

And it's not completely wrong. Mimicking human behavior is exactly what they're designed to do. You just need to keep reminding people that it's only doing so in a very superficial and spotty way. There's absolutely no basis for assuming that what's happening on the inside is the same.

Re: A non-anthropomorphized view of LLMs

#309

Post by squidbeak »

CuriousSkeptic wrote: post #193
tempfile wrote: post #184

Earlier quoted context omitted.

The "point" of not anthropomorphizing is to refrain from judgement until a more solid abstraction appears. The problem with explaining LLMs in terms of human behaviour is that, while we don't clearly understand what the LLM is doing, we understand human cognition even less! There is literally no predictive power in the abstraction "The LLM is thinking like I am thinking". It gives you no mechanism to evaluate what ta…

> Why don't LLMs get frustrated with you if you ask them the same question repeatedly? To be fair, I have had a strong sense of Gemini in particular becoming a lot more frustrated with me than GPT or Claude. Yesterday I had it ensuring me that it was doing a great job, it was just me not understanding the challenge but it would break it down step by step just to make it obvious to me (only to repeat the same errors,…

The vending machine study from a few months ago, where flash 2.0 lost its mind, contacted the FBI (as far as it knew) and refused to co-operate with the operator's demands, seemed a lot like frustration.

Re: A non-anthropomorphized view of LLMs

#310

Post by overfeed »

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…

> We need a higher abstraction level to talk about higher level phenomena in LLMs as well, and the problem is that we have no idea what happens internally at those higher abstraction levels

We do know what happens at higher abstraction levels; the design of efficient networks, and the steady beat of SOTA improvements all depend on understanding how LLMs work internally: choice of network dimensions, feature extraction, attention, attention heads, caching, the peculiarities of high-dimensions and avoiding overfitting are all well-understood by practitioners. Anthropomorphization is only necessary in pop-science articles that use a limited vocabulary.

IMO, there is very little mystery, but lots of deliberate mysticism, especially about future LLMs - the usual hype-cycle extrapolation.

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