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They’re made out of weights

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Re: They’re made out of weights

#411

Post by dbspin »

phkahler wrote: post #392
f_klem wrote: post #161

After reading Being and Time from Martin Heidegger, What Computers can't still do by Hubert Dreyfus, and some authors in cognitive linguistics (Langacker and Lakoff mainly), I strongly tend to disagree with any theory about emergent consciousness in modern or future AI systems, any theory proposing a similarity between AI systems and the human brain/mind, or any theory about the computational mind. What all these the…

>> and that is that we understand (or we think we understand) how our brain/mind works. But the truth is that we don't know. And there's even not a single clue that we actually know too much, and not a clue that our brain/mind and cells work 'as the machines we build'. >> I highly recommend people in the AI research space should read philosophy and modern linguistics. I highly recommend the philosophers read some neu…

Hard disagree. We only discovered the role that glial cells play in processing around 2014. We're still uncertain how patterns of activation consolidate through long term potentiation, let alone how signaling encodes information. We understand quite a bit about the role of the hippocampus and subiculum in encoding memories; but we don't understand the structural layout of engram complexes - which were themselves mapped for the first time only in 2022!

Taking effective results in machine learning, and somehow assuming that they apply to cognition - simply because neural nets were inspired by our limited knowledge of neural signaling and structure - is like trying to apply aircraft engineering to studying ornithology. For a better articulation of this point (from the reverse direction) check out the paper 'Could a Neuroscientist Understand a Microprocessor?' from 2017 - https://journals.plos.org/ploscompbiol/article?id=10.1371/jo...

Re: They’re made out of weights

#412

Post by bwest87 »

He forgot the tokens!

It's not simple weights and numbers all the way down. The available output is pre-set by the tokens we allow it to predict.

There was a whole bit in there about not having a language module or using words. But it does. We tell it.

Humans do not come pre programmed with a set of possible "tokens". We just figure it out and I believe that fact captures something very essential. Maybe the missing piece of AGI. The fact that humans can just be awash in pure sense data, and somehow just figure out what is important and what to do. Never ceases to amaze me.

Re: They’re made out of weights

#413

Post by Lplololopo »

yencabulator wrote: post #372
Lplololopo wrote: post #235

Earlier quoted context omitted.

I would say that the LLM is something completly different especiayll as its not a normal algorithm but is very close to what brains do.

Ah yes, matrix multiplication is "not a normal algorithm", surely.

The matrix multilication underneath a large language model is the hardware but the data and the forming weights is not.

A quick sort sorts a list. A LLM depends on its learning data.

You train a model and then you use the model.

Re: They’re made out of weights

#414

Post by aspenmartin »

jimbokun wrote: post #396
codeflo wrote: post #259

Earlier quoted context omitted.

> These theories are flawed in the sense that they cannot account for subjective experience and agency, amongst other things. On the contrary, it's precisely this assumption, that there is a "subjective experience" that requires explanation beyond the material, that is axiomatically assumed without evidence. It falls apart quickly, any "subjective experience" is completely tied to neurons, knock out the neurons and t…

It’s the opposite. Descartes made clear that subjective experience is the ONLY thing we know. Everything else is theories to explain the phenomena we subjectively experience. We theorize that there is a physical world and other beings like us having similar subjective experiences, because that seems the best explanation for our subjective experiences. But we might be living in the Matrix, with all the people we think…

And this has some bearing on the debate about whether these systems do or could in the future exhibit something similar?

Re: They’re made out of weights

#415

Post by Lplololopo »

skydhash wrote: post #315
Lplololopo wrote: post #230

Earlier quoted context omitted.

Compression is the reason why these Models are able to learn and understand. My brain is doing the exact same thing. I learned enough to compress concepts like a bike and what a bike does and for what i can use a bike. Ask a LLM and it will answer you similiar to humans. Blind people learn concepts of bikes too and in a smiliar way: by description. LLMs just have so much data in form of text available and are able to…

> Blind people learn concepts of bikes too and in a smiliar way: by description. And by touch and sound. And maybe some were daring enough to drive one, or unlucky enough to get hit by one. But have way more input than just texts.

So a blind person only can describe lava to you after they touched and heared it?

Re: They’re made out of weights

#416

Post by sperandeo »

I don't like to say one way or the other on things. Especially LLM's. However, if ive learned anything about LLMs and real life problems, is to break it down to the foundation like already mention with weights being compared to neurons and map the parallels.

Re: They’re made out of weights

#417

Post by vkazanov »

davrosthedalek wrote: post #330
vkazanov wrote: post #309

Earlier quoted context omitted.

I don't ignore anything. I just refuse to accept the magical thinking around biological machines that are our brains/bodies. There are inputs, there are outputs, there is hidden function. And it seems that, given enough input/outputs/compute, it is possible to train the necessary function. Details of how the building bricks look like (matmul, electromagnetism or quantum effects) are not that relevant in the broader p…

I mostly agree, but I see two points that might be problematic: a) The brain might have an entropy source (then it can't be modeled as a function). Trivially to fix, and in some sense, with diffusion models starting from random numbers, AI has done so. b) The hidden function might be not computable. I would have no idea how that would work, but I think this is what it boils down to if people say "the human brain is m…

a) enthropy can be injected as well. In fact there are hidden sources in current training.

b) well, it can be the case that, say, certain kinds of computation are either too inefficient or outright impossible within the current model.

Who knows...

Re: They’re made out of weights

#418

Post by californical »

phkahler wrote: post #392
f_klem wrote: post #161

After reading Being and Time from Martin Heidegger, What Computers can't still do by Hubert Dreyfus, and some authors in cognitive linguistics (Langacker and Lakoff mainly), I strongly tend to disagree with any theory about emergent consciousness in modern or future AI systems, any theory proposing a similarity between AI systems and the human brain/mind, or any theory about the computational mind. What all these the…

>> and that is that we understand (or we think we understand) how our brain/mind works. But the truth is that we don't know. And there's even not a single clue that we actually know too much, and not a clue that our brain/mind and cells work 'as the machines we build'. >> I highly recommend people in the AI research space should read philosophy and modern linguistics. I highly recommend the philosophers read some neu…

> There are also differences between discrete neuron firing and weights as signals, but there is enough similarity to make artificial neural nets useful and do things similar to what real one do.

There is barely a surface-level similarity. The best example I can come up with is this…

Imagine the most intricate and beautiful tall building that you can think of. Think like an older skyscraper in Chicago or a palace. There are water features and moving parts everywhere but also tiny little handmade carvings and materials throughout.

Now imagine we have no reference designs and no blueprints - we hire an architect to attempt to study the building by looking at it from a distance and understand everything they possibly can about it. She can go into the building to check but every time she does, it stops functioning normally.

That architect is a neuroscientist.

Then the ML researcher is like a graphic designer who sees the work that the architect is doing and makes a napkin sketch of the building the architect has been studying, to use for a project later. Sure the designer has some of her representations. But the difference in complexity between the designer’s napkin sketch and the architect’s analysis is massive. Several orders of magnitude.

Then another many orders of magnitude is the level of detail that the architect can understand about this strange building without being able to fully interact with it, versus the actual complexity of the building.

So yeah, an AI is modeled after neurons in the sense that they represent a couple of surface level features of neurons. But the difference in complexity is about as much as a napkin drawing of a grand building represents the actual structure and details of the building, no matter the level of skill that the graphic designer has

Re: They’re made out of weights

#419

Post by stonogo »

codeflo wrote: post #259
f_klem wrote: post #161

After reading Being and Time from Martin Heidegger, What Computers can't still do by Hubert Dreyfus, and some authors in cognitive linguistics (Langacker and Lakoff mainly), I strongly tend to disagree with any theory about emergent consciousness in modern or future AI systems, any theory proposing a similarity between AI systems and the human brain/mind, or any theory about the computational mind. What all these the…

> These theories are flawed in the sense that they cannot account for subjective experience and agency, amongst other things. On the contrary, it's precisely this assumption, that there is a "subjective experience" that requires explanation beyond the material, that is axiomatically assumed without evidence. It falls apart quickly, any "subjective experience" is completely tied to neurons, knock out the neurons and t…

"that is axiomatically assumed"

passive voice doing a hell of a lot of work in this phrase

Re: They’re made out of weights

#420

Post by SlinkyOnStairs »

ACCount37 wrote: post #355
sixeyes wrote: post #343

Earlier quoted context omitted.

oh yeah! i recall a paper linked here not so long ago, where it was shown that the dendrites of a neuron do computations themselves. The "weight per neuron" is very simplistic then. At the very least, each actual neuron is a network of weights. https://www.quantamagazine.org/neural-dendrites-reveal-their...

I'm partial to "modern ML weights are much closer to 1:1 capacity mapping to synapse count than to neuron count". A single biological neuron is closer to 100 or even 1000 weights worth of ANN than to 1 weight worth of ANN. In which case: modern LLMs are still running in a capacity-starved regime! Even Mythos 5, the 10-trillion monster LLM, the scaling law boogeyman, the harbinger of Vera Rubin NVL72, doesn't quite ri…

> A single biological neuron is closer to 100 or even 1000 weights worth of ANN than to 1 weight worth of ANN.

Even those comparisons need to be cautioned. The complexity of biology is enormous, and more importantly yet, it's simply not comparable. And doing so invited a bunch of bad assumptions.

An ANN could quite probably model a single in vitro neuron with reasonable accuracy. Whether that requires a hundred or a hundred million nodes isn't terribly relevant.

But the way neurons combine in vivo is completely unlike the way machine learning systems are built. Both "locally" in how neurons interface which is vastly more complex than a weighted sum of inputs, and the macro scale interactions of hormones and other chemicals.

It's not even a given that large numbers of neurons will create the emergent behaviour of human intelligence; Elephants have significantly more neurons, but they're not the triple galaxy brains writing all our science papers. Other animal intelligence similarly is only loosely correlated with brain complexity. (Heck, not to be forgotten is the other end of the scale. Plenty of microscopic life that manages shockingly complex behaviour without any dedicated neurons)

This also applies to ANNs. There's no reason to expect that stuffing enough matrix multiplications into a program will make it intelligent or turn out conscious.

Really, the history of machine learning suggests the opposite; That the big gains are primarily had in architectural changes.

In this regard, I find the talk of the "limits of AI" quite credible. LLMs have already hit the diminishing returns on their growth, and even reasoning/agentic models display failure modes that confirm they're not "thinking" in the ways that humans do.

This is not to say that we've hit the final limits of what AI in the broad sense can do, it's just that the next advancement won't be "LLM but even bigger"

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