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Bag of words, have mercy on us

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Re: Bag of words, have mercy on us

#191

Post by habinero »

Kim_Bruning wrote: post #31
tkgally wrote: post #19

I am unsure myself whether we should regard LLMs as mere token-predicting automatons or as some new kind of incipient intelligence. Despite their origins as statistical parrots, the interpretability research from Anthropic [1] suggests that structures corresponding to meaning do exist inside those bundles of numbers and that there are signs of activity within those bundles of numbers that seem analogous to thought. T…

Amanda Askell studied under David Chalmers at NYU: the philosopher who coined "the hard problem of consciousness" and is famous for taking phenomenal experience seriously rather than explaining it away. That context makes her choice to speak this way more striking: this isn't naive anthropomorphizing from someone unfamiliar with the debates. It's someone trained by one of the most rigorous philosophers of consciousne…

A person can study fashion extensively, under the best designers, they can understand tailoring and fit and have a phenomenal eye for color and texture.

Their vivid descriptions of what the Emperor could be wearing doesn't make said emperor any less nakey.

Re: Bag of words, have mercy on us

#192

Post by thesz »

akoboldfrying wrote: post #112
RayVR wrote: post #70

Earlier quoted context omitted.

Are you a stream of words or are your words the “simplistic” projection of your abstract thoughts? I don’t at all discount the importance of language in so many things, but the question that matters is whether statistical models of language can ever “learn” abstract thought, or become part of a system which uses them as a tool. My personal assessment is that LLMs can do neither.

LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different.

  > Human brains aren't magic, special or different.
DNA inside neurons uses superconductive quantum computations [1].

[1] https://www.nature.com/articles/s41598-024-62539-5

As the result, all living cells with DNA emit coherent (as in lasers) light [2]. There is a theory that this light also facilitates intercellular communication.

[2] https://www.sciencealert.com/we-emit-a-visible-light-that-va...

Chemical structures in dendrites, not even neurons, are capable to compute XOR [3] which require multilevel artificial neural network with at least 9 parameters. Some neurons in brain have hundredths of thousands of dendrites, we are now talking of millions of parameters only in single neuron's dendrites functionality.

[3] https://www.science.org/doi/10.1126/science.aax6239

So, while human brains aren't magic, special or different, they are just extremely complex.

Imagine building a computer with 85 billions of superconducting quantum computers, optically and electrically connected, each capable of performing computations of a non-negligibly complex artificial neural network.

Re: Bag of words, have mercy on us

#193

Post by quantummagic »

rob74 wrote: post #186
ben_w wrote: post #162

Earlier quoted context omitted.

The general argument you make is correct, but you conclusion "And this one doesn't." is as yet uncertain. I will absolutely say that all ML methods known are literally too stupid to live, as in no living thing can get away with making so many mistakes before it's learned anything, but that's the rate of change of performance with respect to examples rather than what it learns by the time training is finished. What is…

> no living thing can get away with making so many mistakes before it's learned anything If you consider that LLMs have already "learned" more than any one human in this world is able to learn, and still make those mistakes, that suggests there may be something wrong with this approach...

But humans do the same thing. How many eons did we make the mistake of attributing everything to God's will, without a scientific thought in our heads? It's really easy to be wrong, when the consequences don't lead to your death, or are actually beneficial. The thinking machines are still babies, whose ideas aren't honed by personal experience; but that will come, in one form or another.

Re: Bag of words, have mercy on us

#194

Post by robinei »

visarga wrote: post #109
bloaf wrote: post #32

Earlier quoted context omitted.

I'll make the following observation: The contra-positive of "All LLMs are not thinking like humans" is "No humans are thinking like LLMs" And I do not believe we actually understand human thinking well enough to make that assertion. Indeed, it is my deep suspicion that we will eventually achieve AGI not by totally abandoning today's LLMs for some other paradigm, but rather embedding them in a loop with the right pers…

The loop, or more precisely the "search" does the novel part in thinking, the brain is just optimizing this process. Evolution could manage with the simplest model - copying with occasional errors, and in one run it made everyone of us. The moral - if you scale search the model can be dumb.

Let’s not underestimate the scale of the search which led to us though, even though you may be right in principle. In addition to deep time on earth, we may well be just part of a tiny fraction of a universe-wide and mostly fruitless search.

Re: Bag of words, have mercy on us

#195

Post by ACCount37 »

Ukv wrote: post #30
akomtu wrote: post #26

Earlier quoted context omitted.

Spoken Query Language? Just like SQL, but for unstructured blobs of text as a database and unstructured language as a query? Also known as Slop Query Language or just Slop Machine for its unpredictable results.

> Spoken Query Language? Just like SQL, but for unstructured blobs of text as a database and unstructured language as a query? I feel that's more a description of a search engine. Doesn't really give an intuition of why LLMs can do the things they do (beyond retrieval), or where/why they'll fail.

If you want actionable intuition, try "a human with almost zero self-awareness".

"Self-awareness" used in a purely mechanical sense here: having actionable information about itself and its own capabilities.

If you ask an old LLM whether it's able to count the Rs in "strawberry" successfully, it'll say "yes". And then you ask it to do so, and it'll say "2 Rs". It doesn't have the self-awareness to know the practical limits of its knowledge and capabilities. If it did, it would be able to work around the tokenizer and count the Rs successfully.

That's a major pattern in LLM behavior. They have a lot of capabilities and knowledge, but not nearly enough knowledge of how reliable those capabilities are, or meta-knowledge that tells them where the limits of their knowledge lie. So, unreliable reasoning, hallucinations and more.

Re: Bag of words, have mercy on us

#196

Post by d4rkn0d3z »

An LLM creates a high fidelity statistical probabistic model of human language. The hope is to capture the input/output of various hierarchical formal and semiformal systems of logic that transit from human to human, which we know as "Intelligence".

Unfortunately, its corpus is bound to contain noise/nonsense that follows no formal reasoning system but contributes to the ill advised idea that an AI should sound like a human to be considered intelligent. Therefore it is not a bag of words but a bag of probabilities perhaps. This is important because the fundamental problem is that an LLM is not able, by design, to correctly model the most fundamental precept of human reason, namely the law of non-contradiction. An LLM must, I repeat must assign nonvanishing probability to both sides of a contradiction, and what's worse is the winning side loses, since long chains of reason are modelled with probability the longer the chain, the less likely an LLM is to follow it. Moreover, whenever there is actual debate on an issue such that the corpus is ambiguous the LLM becomes chaotic, necessarily, on that issue.

I literally just had an AI prove the forgoing with some rigor, and in the very next prompt, I asked it to check my logical reasoning for consistency and it claimed it was able to do so (->|<-).

Re: Bag of words, have mercy on us

#197

Post by nkrisc »

panarky wrote: post #152
meheleventyone wrote: post #147

Earlier quoted context omitted.

Human brains aren’t magic in the literal sense but do have a lot of mechanisms we don’t understand. They’re certainly special both within the individual but also as a species on this planet. There are many similar to human brains but none we know of with similar capabilities. They’re also most obviously certainly different to LLMs both in how they work foundationally and in capability. I definitely agree with the mat…

When someone says "AIs aren't really thinking" because AIs don't think like people do, what I hear is "Airplanes aren't really flying" because airplanes don't fly like birds do.

If I shake some dice in a cup are they thinking about what number they’ll reveal when I throw them?

Re: Bag of words, have mercy on us

#198

Post by A4ET8a8uTh0_v2 »

d4rkn0d3z wrote: post #196

An LLM creates a high fidelity statistical probabistic model of human language. The hope is to capture the input/output of various hierarchical formal and semiformal systems of logic that transit from human to human, which we know as "Intelligence". Unfortunately, its corpus is bound to contain noise/nonsense that follows no formal reasoning system but contributes to the ill advised idea that an AI should sound like…

^^; I think this post is close to singularity as we may get on this Monday.

Re: Bag of words, have mercy on us

#199

Post by A4ET8a8uTh0_v2 »

balamatom wrote: post #190
RayVR wrote: post #70

Earlier quoted context omitted.

Are you a stream of words or are your words the “simplistic” projection of your abstract thoughts? I don’t at all discount the importance of language in so many things, but the question that matters is whether statistical models of language can ever “learn” abstract thought, or become part of a system which uses them as a tool. My personal assessment is that LLMs can do neither.

I'm definitely a stream of words. My "abstract thoughts" are a stream of words too, they just don't get sounded out. Tbf I'd rather they weren't there in the first place. But bodies which refuse to harbor an "interiority" are fast-tracked to destruction because they can't suf^W^W^W be productive. Funny movie scene from somewhere. The sergeant is drilling the troops: "You, private! What do you live for!", and expects…

Hmm, seems unlikely. They are not sounded out part is true, sure, but I question whether 'abstract thoughts' can be so easily dismissed as mere words.

edit: come to think of it and I am asking this for a reason: do you hear your abstract thoughts?

Re: Bag of words, have mercy on us

#200

Post by arowthway »

akoboldfrying wrote: post #112
RayVR wrote: post #70

Earlier quoted context omitted.

Are you a stream of words or are your words the “simplistic” projection of your abstract thoughts? I don’t at all discount the importance of language in so many things, but the question that matters is whether statistical models of language can ever “learn” abstract thought, or become part of a system which uses them as a tool. My personal assessment is that LLMs can do neither.

LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different.

For some unexplainable reason your subjective experience happens to be localized in your brain. Sounds pretty special to me.
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