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The Case That A.I. Is Thinking

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Re: The Case That A.I. Is Thinking

#211

Post by pegasus »

omnicognate wrote: post #182
OrderlyTiamat wrote: post #157

Earlier quoted context omitted.

Google's AlphaEvolve independently discovered a novel matrix multiplication algorithm which beats SOTA on at least one axis: https://www.youtube.com/watch?v=sGCmu7YKgPA

That was an impressive result, but AIUI not an example of "coming up with and proving (preferably numerous) significant new theorems without human guidance". For one thing, the output was an algorithm, not a theorem (except in the Curry-Howard sense). More importantly though, AlphaEvolve has to be given an objective function to evaluate the algorithms it generates, so it can't be considered to be working "without hum…

Yes, it's a very technical and circumscribed result, not requiring a deep insight into the nature of various mathematical models.

Re: The Case That A.I. Is Thinking

#212

Post by hackinthebochs »

almosthere wrote: post #25
famouswaffles wrote: post #11

Earlier quoted context omitted.

We do not write the code that makes it do what it does. We write the code that trains it to figure out how to do what it does. There's a big difference.

The code that builds the models and performance inference from it is code we have written. The data in the model is obviously the big trick. But what I'm saying is that if you run inference, that alone does not give it super-powers over your computer. You can write some agentic framework where it WOULD have power over your computer, but that's not what I'm referring to. It's not a living thing inside the computer, it…

This is a bad take. We didn't write the model, we wrote an algorithm that searches the space of models that conform to some high level constraints as specified by the stacked transformer architecture. But stacked transformers are a very general computational paradigm. The training aspect converges the parameters to a specific model that well reproduces the training data. But the computational circuits the model picks out are discovered, not programmed. The emergent structures realize new computational dynamics that we are mostly blind to. We are not the programmers of these models, rather we are their incubators.

As far as sentience is concerned, we can't say they aren't sentient because we don't know the computational structures these models realize, nor do we know the computational structures required for sentience.

Re: The Case That A.I. Is Thinking

#213

Post by brianpan »

oergiR wrote: post #195
Symmetry wrote: post #71

Earlier quoted context omitted.

"The question of whether a computer can think is no more interesting than the question of whether a submarine can swim." - Edsger Dijkstra

There is more to this quote than you might think. Grammatically, in English the verb "swim" requires an "animate subject", i.e. a living being, like a human or an animal. So the question of whether a submarine can swim is about grammar. In Russian (IIRC), submarines can swim just fine, because the verb does not have this animacy requirement. Crucially, the question is not about whether or how a submarine propels itse…

I don't think the distinction is animate/inanimate.

Submarines sail because they are nautical vessels. Wind-up bathtub swimmers swim, because they look like they are swimming.

Neither are animate objects.

In a browser, if you click a button and it takes a while to load, your phone is thinking.

Re: The Case That A.I. Is Thinking

#214

Post by prmph »

esafak wrote: post #170
prmph wrote: post #51

> An A.I smarter than a Nobel prize winner. I don't even know what this means. If we assembled the sum total of all published human knowledge on a storage medium and gave a computer the ability to search it extremely well in order to answer any question falling within its domain, there, you would have a Nobel Prize beating "A.I". But this is as "earth-shattering" (/s) as the idea that human knowledge can be stored ou…

Search is not intelligence, but synthesis is, and LLMs interpolate well. They don't invent new branches of mathematics and science yet.

You really think the reason we revere Nobel Prize winners is because they are good at interpolating?

Re: The Case That A.I. Is Thinking

#215

Post by jmcodes »

zahlman wrote: post #135
IanCal wrote: post #106

Earlier quoted context omitted.

> Don't be sycophantic. Disagree and push back when appropriate. They can do this though. > Can they spontaneously come up with something, anything, without any external input? I don’t see any why not, but then humans don’t have zero input so I’m not sure why that’s useful.

> but then humans don’t have zero input Humans don't require input to, say, decide to go for a walk. What's missing in the LLM is volition .

Our entire extistence and experience is nothing _but_ input.

Temperature changes, visual stimulus, auditory stimulus, body cues, random thoughts firing, etc.. Those are all going on all the time.

Re: The Case That A.I. Is Thinking

#216

Post by bitwize »

mft_ wrote: post #123

Personal take: LLMs are probably part of the answer (to AGI?) but are hugely handicapped by their current architecture: the only time that long-term memories are formed is during training, and everything after that (once they're being interacted with) sits only in their context window, which is the equivalent of fungible, fallible, lossy short-term memory. [0] I suspect that many things they currently struggle with c…

I'm also reminded of the bit from Neuromancer where Case removes and then reinserts the Dixie Flatline "ROM construct" cartridge, resetting Dixie to the moment just before his death and causing him to forget their previous (albeit brief) conversation. Dixie can't meaningfully grow as a person. All that he ever will be is burned onto that cart; anything he learns since then is stored in temporary memory. Perhaps this is part of the reason why he wishes to be erased forever, ending his suffering.

Re: The Case That A.I. Is Thinking

#217

Post by [deleted] »

gwd wrote: post #196
handfuloflight wrote: post #120

Earlier quoted context omitted.

What an oversimplification. Thinking computers can create more swimming submarines, but the inverse is not possible. Swimming is a closed solution; thinking is a meta-solution.

I think you missed the point of that quote. Birds fly, and airplanes fly; fish swim but submarines don't. It's an accident of language that we define "swim" in a way that excludes what submarines do. They move about under their own power under the water, so it's not very interesting to ask whether they "swim" or not. Most people I've talked to who insist that LLMs aren't "thinking" turn out to have a similar perspect…

[deleted]

Re: The Case That A.I. Is Thinking

#219

Post by adamzwasserman »

The article misses three critical points:

1. Conflates consciousness with "thinking" - LLMs may process information effectively without being conscious, but the article treats these as the same phenomenon

2. Ignores the cerebellum cases - We have documented cases of humans leading normal lives with little to no brain beyond a cerebellum, which contradicts simplistic "brain = deep learning" equivalences

3. Most damning: When you apply these exact same techniques to anything OTHER than language, the results are mediocre. Video generation still can't figure out basic physics (glass bouncing instead of shattering, ropes defying physics). Computer vision has been worked on since the 1960s - far longer than LLMs - yet it's nowhere near achieving what looks like "understanding."

The timeline is the smoking gun: vision had decades of head start, yet LLMs leapfrogged it in just a few years. That strongly suggests the "magic" is in language itself (which has been proven to be fractal and already heavily compressed/structured by human cognition) - NOT in the neural architecture. We're not teaching machines to think.

We're teaching them to navigate a pre-existing map that was already built.

Re: The Case That A.I. Is Thinking

#220

Post by hamdingers »

baq wrote: post #139
crazygringo wrote: post #99

Earlier quoted context omitted.

> But they do not actually think. I'm so baffled when I see this being blindly asserted. With the reasoning models, you can literally watch their thought process . You can see them pattern-match to determine a strategy to attack a problem, go through it piece-by-piece, revisit assumptions, reformulate strategy, and then consolidate findings to produce a final result. If that's not thinking, I literally don't know wha…

Brains are pretrained models, change my mind. (Not LLMs obviously, to be perfectly clear)

Brains continue learning from everything they do for as long as they're in use. Pretrained models are static after initial training.
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