Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

A non-anthropomorphized view of LLMs

addxorrol.blogspot.com

Post reply on HN
Print view View original

121–130 of 432 posts

Re: A non-anthropomorphized view of LLMs

#121

Post by throw310822 »

positron26 wrote: post #103
lostmsu wrote: post #101

Earlier quoted context omitted.

> Current LLMs can only introspect from output tokens The only interpretation of this statement I can come up with is plain wrong. There's no reason LLM shouldn't be able to introspect without any output tokens. As the GP correctly says, most of the processing in LLMs happens over hidden states. Output tokens are just an artefact for our convenience, which also happens to be the way the hidden state processing is tra…

There are no recurrent paths besides tokens. How may I introspect something if it is not an input? I may not.

Introspection doesn't have to be recurrent. It can happen during the generation of a single token.

Re: A non-anthropomorphized view of LLMs

#122

Post by Marazan »

lostmsu wrote: post #101
positron26 wrote: post #98

Earlier quoted context omitted.

> Is it too anthropomorphic to say that this is a lie? Yes. Current LLMs can only introspect from output tokens. You need hidden reasoning that is within the black box, self-knowing, intent, and motive to lie. I rather think accusing an LLM of lying is like accusing a mousetrap of being a murderer. When models have online learning, complex internal states, and reflection, I might consider one to have consciousness an…

> Current LLMs can only introspect from output tokens The only interpretation of this statement I can come up with is plain wrong. There's no reason LLM shouldn't be able to introspect without any output tokens. As the GP correctly says, most of the processing in LLMs happens over hidden states. Output tokens are just an artefact for our convenience, which also happens to be the way the hidden state processing is tra…

"Hidden layers" are not "hidden state".

Saying so is just unbelievably confusing.

Re: A non-anthropomorphized view of LLMs

#123

Post by NetRunnerSu »

The author's critique of naive anthropomorphism is salient. However, the reduction to "just MatMul" falls into the same trap it seeks to avoid: it mistakes the implementation for the function. A brain is also "just proteins and currents," but this description offers no explanatory power.

The correct level of analysis is not the substrate (silicon vs. wetware) but the computational principles being executed. A modern sparse Transformer, for instance, is not "conscious," but it is an excellent engineering approximation of two core brain functions: the Global Workspace (via self-attention) and Dynamic Sparsity (via MoE).

To dismiss these systems as incomparable to human cognition because their form is different is to miss the point. We should not be comparing a function to a soul, but comparing the functional architectures of two different information processing systems. The debate should move beyond the sterile dichotomy of "human vs. machine" to a more productive discussion of "function over form."

I elaborate on this here: https://dmf-archive.github.io/docs/posts/beyond-snn-plausibl...

Re: A non-anthropomorphized view of LLMs

#124

Post by orbital-decay »

>I am baffled by seriously intelligent people imbuing almost magical human-like powers to something that - in my mind - is just MatMul with interspersed nonlinearities.

I am baffled by seriously intelligent people imbuing almost magical powers that can never be replicated to to something that - in my mind - is just a biological robot driven by a SNN with a bunch of hardwired stuff. Let alone attributing "human intelligence" to a single individual, when it's clearly distributed between biological evolution, social processes, and individuals.

>something that - in my mind - is just MatMul with interspersed nonlinearities

Processes in all huge models (not necessarily LLMs) can be described using very different formalisms, just like Newtonian and Lagrangian mechanics describe the same stuff in physics. You can say that an autoregressive model is a stochastic parrot that learned the input distribution, next token predictor, or that it does progressive pathfinding in a hugely multidimensional space, or pattern matching, or implicit planning, or, or, or... All of these definitions are true, but only some are useful to predict their behavior.

Given all that, I see absolutely no problem with anthropomorphizing an LLM to a certain degree, if it makes it easier to convey the meaning, and do not understand the nitpicking. Yeah, it's not an exact copy of a single Homo Sapiens specimen. Who cares.

Re: A non-anthropomorphized view of LLMs

#126

Post by cmenge »

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.

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 being so mainstream and the math being much more elusive than a simple if..then I guess it's just too easy to take this simple speaking convention at face value.

EDIT: some clarifications / wording

Re: A non-anthropomorphized view of LLMs

#127

Post by seadan83 »

LeifCarrotson wrote: post #68
ants_everywhere wrote: post #20

> I am baffled that the AI discussions seem to never move away from treating a function to generate sequences of words as something that resembles a human. This is such a bizarre take. The relation associating each human to the list of all words they will ever say is obviously a function. > almost magical human-like powers to something that - in my mind - is just MatMul with interspersed nonlinearities. There's a ric…

> I am baffled that the AI discussions seem to never move away from treating a function to generate sequences of words as something that resembles a human. You appear to be disagreeing with the author and others who suggest that there's some element of human consciousness that's beyond than what's observable from the outside, whether due to religion or philosophy or whatever, and suggesting that they just not do that…

>> given a human and a sequence of words, I cannot begin putting a probability on "will this human generate this sequence".

> Sure you can! If you address an American crowd of a certain age range with "We’ve got to hold on to what we’ve got. It doesn’t make a difference if..." I'd give a very high probability that someone will answer "... we make it or not".

I think you may have this flipped compared to what the author intended. I believe the author is not talking about the probability of an output given an input, but the probability of a given output across all inputs.

Note that the paragraph starts with "In my worldview, humans are dramatically different things than a function, (R^n)^c -> (R^n)^c". To compute a probability of a given output, (which is a any given element in "(R^n)^n"), we can count how many mappings there are total and then how many of those mappings yield the given element.

The point I believe is to illustrate the complexity of inputs for humans. Namely for humans the input space is even more complex than "(R^n)^c".

In your example, we can compute how many input phrases into a LLM would produce the output "make it or not". We can than compute that ratio to all possible input phrases. Because "(R^n)^c)" is finite and countable, we can compute this probability.

For a human, how do you even start to assess the probability that a human would ever say "make it or not?" How do you even begin to define the inputs that a human uses, let alone enumerate them? Per the author, "We understand essentially nothing about it." In other words, the way humans create their outputs is (currently) incomparably complex compared to a LLM, hence the critique of the anthropomorphization.

Re: A non-anthropomorphized view of LLMs

#128

Post by Al-Khwarizmi »

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.

I think it's worth distinguishing between the use of anthropomorphism as a useful abstraction and the misuse by companies to fuel AI hype.

For example, I think "chain of thought" is a good name for what it denotes. It makes the concept easy to understand and discuss, and a non-antropomorphized name would be unnatural and unnecessarily complicate things. This doesn't mean that I support companies insisting that LLMs think just like humans or anything like that.

By the way, I would say actually anti-anthropomorphism has been a bigger problem for understanding LLMs than anthropomorphism itself. The main proponents of anti-anthropomorphism (e.g. Bender and the rest of "stochastic parrot" and related paper authors) came up with a lot of predictions about things that LLMs surely couldn't do (on account of just being predictors of the next word, etc.) which turned out to be spectacularly wrong.

Re: A non-anthropomorphized view of LLMs

#129

Post by orbital-decay »

rockskon wrote: post #94

The people in this thread incredulous at the assertion that they are not God and haven't invented machine life are exasperating. At this point I am convinced they, more often than not, financially benefit from their near religious position in marketing AI as akin to human intelligence.

Are we looking at the same thread? I see nobody claiming this. Anthropic does sometimes, their position is clearly wishful thinking, and it's not represented ITT.

Try looking at this from another perspective - many people simply do not see human intelligence (or life, for that matter) as magic. I see nothing religious about that, rather the opposite.

Re: A non-anthropomorphized view of LLMs

#130

Post by seadan83 »

ants_everywhere wrote: post #21
mewpmewp2 wrote: post #16

My question: how do we know that this is not similar to how human brains work. What seems intuitively logical to me is that we have brains evolved through evolutionary process via random mutations yielding in a structure that has its own evolutionary reward based algorithms designing it yielding a structure that at any point is trying to predict next actions to maximise survival/procreation, of course with a lot of s…

> My question: how do we know that this is not similar to how human brains work. It is similar to how human brains operate. LLMs are the (current) culmination of at least 80 years of research on building computational models of the human brain.

> 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 incomplete." [1]

"Despite a century of anatomical, physiological, and molecular biological efforts scientists do not know how neurons by their collective interactions produce percepts, thoughts, memories, and behavior. Scientists do not know and have no theories explaining how brains and central nervous systems work." [1]

[1] https://pmc.ncbi.nlm.nih.gov/articles/PMC10585277/

Post reply on HN