upvote
Now show me a writeup that explains how the brain works so I can understand why the brain does those things.

> We know how these machines work, it's not mysterious, there's nothing "extra" happening.

It sounds like you're saying "We don't know how brains work, they're mysterious, there's something 'extra' happening", and using that as justification for why you're saying a computer, an AI, can't "understand".

I think most people on Hackernews now who would use the phrase "my AI worked overnight and hypothesized, compared, etc..." already know how an LLM works, and still chooses to use those words. So the issue isn't that they don't understand. It's that they understand and still use those words. So the disagreement is somewhere else.

reply
I'm not claiming there's something "extra" happening in brains. Merely that we just don't know how they work well enough to use that knowledge to do engineering. Neural nets are quite unlike brains, despite the unfortunate shared vocabulary.

OTOH we do know how neural nets work, and they definitely don't do "thinking" or "reasoning".

reply
First you have to give a specific definition for thinking and reasoning before determining if they definitely do or don't do such a thing.
reply
Fair enough, I should have phrased that less strongly. Until you show that your neural net does "thinking" or "reasoning" I'll disregard that and prefer to think about it in terms of what we actually know neural nets actually do. Does that work?
reply
Just start with your definition for reasoning. If A implies B, and B implies C, does A imply C? Does that count as reasoning?
reply
This feels like a semantic disagreement to me? If an LLM got to an acceptable end result code-wise, what would you call the process that took place to get it there?
reply
I'd call it what it is: a good enough stochastic search result extracted from the model's embedding space.
reply
Is an implication of this that models are incapable of producing entirely novel code?

Also, not to get too reductionist about this, but what do you posit is special about what is happening when humans think? Intelligence is hard to define so clearly, I reckon.

reply
> Is an implication of this that models are incapable of producing entirely novel code?

No, it does not imply that at all. Google "temperature in LLMs".

> what do you posit is special about what is happening when humans think?

I don't. And IIUC nobody knows, but I'm not a brain scientist. There have been some wild theories over the years (recall Penrose's). I don't really have a dog in the hunt, except that probably whatever is happening is physical. It doesn't really matter, except insofar as whatever is happening very probably isn't what LLMs are doing. We know enough about what an LLM does, and what a brain does, to be quite certain they don't work the same.

reply
> Google "temperature in LLMs".

No need to condescend, I'm very aware of what temperature is for LLMs. But I'm going to push back - if you're claiming all LLMs simply do is a stochastic _search_, how can that produce novelty, in the conceptual sense? (I'm not, for example, talking about novel rearrangement of existing ideas and code)

> We know enough about what an LLM does, and what a brain does, to be quite certain they don't work the same.

I don't think the claim is that LLMs do what brains do - I think the correct form of the counterargument is that _whatever LLMs seem to be doing_ produces end results that were previously only possible through the application of human intelligence, so there must be some axis of however you define human intelligence that LLMs currently seem to display as an emergent behaviour.

reply
> if you're claiming all LLMs simply do is a stochastic _search_, how can that produce novelty, in the conceptual sense?

By reaching into the voids of its embedding space and returning tokens related to nonexistent semantics. Or, if you like, "hallucinating". The hallucinations which are useful we might call "novel".

> _whatever LLMs seem to be doing_ produces end results that were previously only possible through the application of human intelligence, so there must be some axis of however you define human intelligence that LLMs currently seem to display as an emergent behaviour.

I don't think that has earned its therefore. Another perfectly reasonable explanation is that LLM's output is a close enough facsimile to intelligence that if you allow yourself you can easily be fooled into thinking its intelligent. That's not the same category of thing. It's not an incremental step away from intelligence. It's a whole different animal.

reply
> By reaching into the voids of its embedding space and returning tokens related to nonexistent semantics. Or, if you like, "hallucinating". The hallucinations which are useful we might call "novel".

This sounds to me like an admission that LLMs are not just doing a stochastic search, then.

> close enough facsimile to intelligence

What's the distinguishing criteria then? How can you tell the difference?

reply
I think we must be talking past eachother. I define stochastic search as a search process with randomness injected into it that can return the following things:

- Something contained in the data set, not necessarily the same thing for every iteration of a given query

- Something not contained the data set (hallucination), not necessarily the same thing for every iteration of a given query

Does that clear it up?

> What's the distinguishing criteria then? How can you tell the difference?

All the ways they fail to exhibit intelligence. They can't learn. They can't adapt. They can't reason abstractly. They can't count. Etc...

reply
Ah it seems you are a stochastic parrot believer (https://en.wikipedia.org/wiki/Stochastic_parrot). What are your responses to the Expert Rebuttals section?

I find the rebuttals pretty convincing - that there seems to be some emergent behaviour that is not simply just next-token-prediction, or that the ability to do accurate next-token-prediction requires something "extra" that LLMs have.

> All the ways they fail to exhibit intelligence

Another implicit admission that there _are_ ways that LLMs exhibit intelligence?

reply
> there seems to be some emergent behaviour that is not simply just next-token-prediction, or that the ability to do accurate next-token-prediction requires something "extra" that LLMs have.

The next step then would be to design and conduct experiments that isolate this effect. Figure out how to make it happen reliably and in such a way that you know it's actually happening as opposed to just something you're imagining. Isolate it or distill it so it can be studied directly. Until then, it's easiest to dismiss it as imaginary.

reply
> Figure out how to make it happen reliably

And you're happy that the replication of LLMs across many foundation model companies is insufficiently reliable?

> just something you're imagining

So the alternative explanation you're suggesting to emergent LLM behaviour is mass independently-corroborated human hallucination. Which is more likely?

Also it really does seem like you've moved the goalposts a lot here without really giving me a substantive response.

reply
To say that LLMs' existence is evidence for emergent phenomena in LLMs is tautological. I'm merely suggesting if you want to make a claim about emergence it would be best, especially in absence of a convincing theory, to demonstrate it experimentally. Otherwise probably better not to claim it's actually happening.
reply
> To say that LLMs' existence is evidence for emergent phenomena in LLMs is tautological.

This is not at all what I was saying. I think you've already conceded that LLMs demonstrate emergent behaviour but you dismissed it as a "close enough facsimile to intelligence". I was saying that the emergent behaviour is reliably replicable, in response to your following statement:

> Figure out how to make it happen reliably and in such a way that you know it's actually happening as opposed to just something you're imagining.

I think there is real work underway in the area of interpretability. In the meantime, there appears to be plenty of empirical evidence for the claim that LLMs exhibit some sort "intelligence" in the enormous penetration that agentic coding has achieved in software development? Do you deny the usefulness of LLMs here, or are you going to assert that actually software development requires no intelligence of any sort?

reply
> I think you've already conceded that LLMs demonstrate emergent behaviour

No. Please don't put words in my mouth. What I said is that an LLM compresses a bunch of information into a semantic embedding space and then does sort of a stochastic search in that embedding space. Any similarity to "intelligence" is accidental. You may look at the results of that process and "see" thinking or reasoning or something, but it ain't there.

> "intelligence" ... agentic ... usefulness

I don't think LLMs need to be intelligent to be (at least narrowly) useful. No more than random forests or genetic algorithms do at least.

[edit] Look, this has devolved to the point where it's no longer productive to continue. If you're going to state things like this as fact, there's really nothing more I can do here:

> emergent behaviour is reliably replicable

Go collect your Nobel prize then! This is no longer a discussion grounded in reality.

reply
> but it ain't there

On what grounds? I don't think you've provided any evidence other than LLMs can't "adapt" or "learn" to show that LLMs do not show intelligence in any way. I think it's clear that there must be some emergent form of intelligence over words from just the agentic coding ability alone. I am not claiming that LLMs are intelligent, only that they display aspects of what we understand as intelligence.

> I don't think LLMs need to be intelligent to be (at least narrowly) useful

I agree! But they are more than narrowly useful, and they absolutely do not belong in the same category as random forests or genetic algorithms!

> Go collect your Nobel prize then! This is no longer a discussion grounded in reality

Once again you are being condescending while misrepresenting my position. The emergent aspects of "intelligence" have been replicated by virtue of independent LLM vendors training their own models - I am not making a stronger claim, you have misunderstood me.

Thanks for participating.

reply
Just a few comments ago you argued that we don't know how to build superintelligence. Now you're saying we know how the (unevenly superintelligent) Fable system works.

It doesn't seem like you're being consistent here. I'm concerned there might be some motivated cognition going on.

"What is true is already so. Owning up to it doesn't make it worse. Not being open about it doesn't make it go away. And because it's true, it is what is there to be interacted with. Anything untrue isn't there to be lived. People can stand what is true, for they are already enduring it."

reply
I'm not following the "Fable" stuff, what is that? [edit: ah it's a new language model from Anthropic.. yeah still don't see how it's relevant here]
reply
[dead]
reply
> We know how these machines work, it's not mysterious, there's nothing "extra" happening.

Lol. This is more telling about your implicit unscientific preconceptions that you wanted to reveal. Of course there isn't anything "extra". Where do you think intelligence comes from, some mysterious realm? It's physical, computational. The fact that at the bottom we produced it via matrix multiplication is irrelevant. Maybe humbling. You are denying a visible fact (a machine performs tasks that require flexible analytical and cognitive skills) precisely because there is no magic happening anywhere.

reply
> Where do you think intelligence comes from, some mysterious realm? It's physical, computational.

Well, no. I don't think it comes from some mysterious realm. I think that which is not physical does not exist [edit: and if you like I'll follow that one right down the rabbit hole--continuity and infinity are useful delusions]. But that eminently does not mean we know what intelligence is, let alone how to build one.

> The fact that at the bottom we produced it via matrix multiplication is irrelevant.

Huh? We don't even know what "it" is. How can you say you produced it?

> a machine performs tasks that require flexible analytical and cognitive skills

You see that, I see a lucky stochastic search result. Don't underestimate the "creativity" of random algorithms! They can do some wild shit! This is nothing new, we've been playing with these toys for like 70 fucking years. It's only recently that they started spewing words and everyone lost their minds over it.

reply
You do realise then that "we know how it works, there is no "extra" there" is an argument that can be used against any artificial intelligence, now or in a thousand years, as well as (at some level) against human intelligence (no magic, it's all physics, just dumb cells exchanging signals). This should be enough to give you pause- you immediately reached for an argument that is entirely empty.

> I see a lucky stochastic search result

Again you're reaching for a mechanistic explanation of some kind (let's leave for the moment whether it makes sense or not) as if having an explanation somehow contradicted a display of intelligence. It doesn't. Yes of course we made it, we know how it works (ar some level) and there is no magic. But what matters is the result- this machine, matrix multiplier, stochastic parrot, consistently displays intelligence, to the point of being able to perform very complex, open-ended tasks that integrate discovery, planning, tool usage, decision and even some aesthetic sense, understanding and using natural language, context awareness, you name it.

> This is nothing new, we've been playing with these toys for like 70 fucking years

Lol no. For god's sake. Hundreds of billions of parameters organised in a specific architecture and trained with unimaginable amounts of data and compute? Unless by "these toys" you mean "any computer program vaguely AI-related".

reply
> But what matters is the result- this machine, matrix multiplier, stochastic parrot, consistently displays intelligence, to the point of being able to perform very complex, open-ended tasks that integrate discovery, planning, tool usage, decision and even some aesthetic sense, understanding and using natural language, context awareness, you name it.

IDK, it doesn't seem like they actually do any of that. To me it seems like they have good enough semantic embeddings that they can kind of approximate those things, sometimes, well enough if you don't look too hard. This is enough to fool people. Of course there's gold in them hills--some recent mathematical results were found there. But to say that's "intellgence" is to say that lossy compression is intelligence. It's static. It does not learn. It does not adapt.

> Unless by "these toys" you mean "any computer program vaguely AI-related".

Not "vaguely AI related". I mean stochastic computer programs that can do things that look awful thinky. They've existed for a long time, but only recently (due to word2vec and other advances) have the results been words that mostly go together well instead of numbers. For some reason people seem to think a lot less critically when the output is words. IDGI but it's a whole thing.

reply