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Is AI reasoning right for the wrong reasons?

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Re: Is AI reasoning right for the wrong reasons?

#231

Earlier quoted context omitted.

"Philosophy is an intrinsically human thing. It has to be." What is philosophy? Thinking? Reasoning? Thinking about thinking? You're asserting that only a human brain can think and reason? Surely other animals can as well. Couldn't aliens as well? Why can't this crazy electronic box? Where do we draw the line? Do dolphins not have internal experiences? Dogs? Cats? Mice? Fish? Worms? Bugs? Amoebas? We don't even reall…

I suggest you print out this exchange and spend a week away from the computer, then re-read what was printed. I'm not trying to be rude but I gave you the answers. Alien philosophy is irrelevant to us because we're not aliens. Tree philosophy is irrelevant to us because we're not trees. Dolphin philosophy is irrelevant to us because we're not dolphins, etc. Everything else you mentioned is "hallucinatory" and you nee…

I’d respectfully disagree here. All phenomena are defined not just by what they are but also by what they are not. I can tell something is relatively tall because I can compare its size to something small. In a fully isolated environment with no reference points, the concept of a given object being small or tall is meaningless.

If we apply that same thought process to philosophy and reason, how can you define it without creating boundaries of what it is not?

Re: Is AI reasoning right for the wrong reasons?

#232

Earlier quoted context omitted.

Millions of adults get hooked by gambling, social media, and AI that pretends to be a person. We need a better standard than "@mdp2021 thinks he's too grown up for this."

The standard is "do grow up; build a society that facilitates growing up; and do not hinder adults with rules for children - that is very much not a society". And your insulting attitude disservices the loser more than the normal people: you know, there are people who can count, there are people who won't lie, there are people who do not take drugs... There do exist adults.

You're arguing that we should be deliberately build evil and manipulative technology... why? To assert your own superior discernment?

Re: Is AI reasoning right for the wrong reasons?

#233
post #79

Earlier quoted context omitted.

We know that human introspection is at best imperfect, and at worst outright fiction, thanks to Sperry's split brain experiments, so while it might be interesting, if the chain of reasoning isn't indicative, that would be in line with how humans work.

Even there half the brain was doing the real reasoning. It’s just the other half which was the verbal/story half didn’t know what that real reasoning was so made up a story it believed to make it fit but was different reasoning. It’s not without reasoning. But half got the reasoning wrong; even if thinking it was right.

No, in the experiment in question, the experimenters made the choice, and claimed to the brain half that couldn't observe that the one that could made the choice.

That is how we know the rationale wasn't the result of information making it between brain halves somehow.

But irrespective of that, the point is exactly that it made up a rationale that couldn't possibly be true, and insisted it was.

In other words, we have no reason to trust our own mind when we rationalize our own actions.

Re: Is AI reasoning right for the wrong reasons?

#234

What an asshole: On the other side of the AI-reasoning fence, the disdain seems to be mutual. “These ‘scientific’ papers from last summer — I would put this in big, big air quotes,” said Sébastien Bubeck, a member of OpenAI’s technical staff (and a prominent evangelist for the company’s reasoning models among scientists and mathematicians). He called earlier Apple results critiquing AI reasoning “wrong,” claiming tha…

Interesting mention of Lean...

Re: Is AI reasoning right for the wrong reasons?

#235
post #221

Earlier quoted context omitted.

LLMs are not classifiers. A classifier is an algorithm or neural net that assigns a label from a fixed set of labels to an input. You can broaden the definition of classifier to anything that internally divides its input space into regions, but that definition would include every neural network, whether biological or artificial. So it's not very meaningful, and certainly doesn't give any insight into how they differ…

But a LLM literally does assign a token from a fixed set of tokens (its vocab) to an input, rinse and repeat, until the stop token. Classifiers have been giving logits since decades ago.

Sure, but then there's no such thing as a network that isn't a classifier. Every physically computable function that terminates in finite time will map an input to a fixed set of outputs. And it goes against the common usage, where in machine learning we talk about classifiers, regressors, generative models, etc. as different things. They all become classifiers.

The parent commenter was trying to draw some insight from LLMs being classifiers that wouldn't apply equally to everything else.

Re: Is AI reasoning right for the wrong reasons?

#236
There are potential parallels with how AIs are trained and the evolutionary pressures that our brains likely evolved under. Human AI trainers accept/reject or give a rating to the AI's response so the selection pressure on AI models is to produce a response that is likely to be accepted by the humans "in its environment" or at least to mirror the responses of humans it's seen provide in its training data.

Long ago I was struck by an idea I heard about human reasoning that I paraphrase as "human reasoning evolved not to reason, but to provide reasons"[1]. Basically that the heaviest evolutionary pressures on our brain were for social utility, like for influencing others to do something for us, or giving pre/post justifications for our actions that most others are likely to accept to avoid punishment. The flawed mechanisms that we developed to do such things are not significantly grounded in logical reasoning, but can sometimes be pressed into duty for that.

LLM models are trained to "generate the best next token" which augments the response so far and makes the evaluator happy. When I reflect on my own mind responding quickly to someone in a meeting it doesn't feel altogether different from that. We don't typically carefully and fully logically reason before we start talking. We typically start talking and think only a little ahead about what we say next that supports and doesn't contradict what we've said already. As we're speaking we are monitoring the other person's facial expressions to infer their emotional response and adjusting our next words based on that. I think at least common neurotypical[2] conversation might be closer to the "next token" reasoning than we would be comfortable admitting.

[1] I _think_ who I heard say that was Hugo Mercier, on either Sean Carroll's consistently amazing science podcast or maybe on Lex Friedman before he veered into Joe Rogan emulation. I'm normally a little suspicious of the theories of psychologists and cognitive scientists, but I intuitively related to many of his lines of thinking.

[2] I'm arguably pretty neurodivergent in more than one way so I think my thought processes are a little different by default, but that makes me more reflective about common conversation. When I'm trying to mask and communicate more similarly to a neurotypical corporate employee I feel like I become a "stochastic parrot" that's just predicting the best next few words to improve the emotional response I'm reading in my conversation partner.

Re: Is AI reasoning right for the wrong reasons?

#237

Earlier quoted context omitted.

"Philosophy is an intrinsically human thing. It has to be." What is philosophy? Thinking? Reasoning? Thinking about thinking? You're asserting that only a human brain can think and reason? Surely other animals can as well. Couldn't aliens as well? Why can't this crazy electronic box? Where do we draw the line? Do dolphins not have internal experiences? Dogs? Cats? Mice? Fish? Worms? Bugs? Amoebas? We don't even reall…

I suggest you print out this exchange and spend a week away from the computer, then re-read what was printed. I'm not trying to be rude but I gave you the answers. Alien philosophy is irrelevant to us because we're not aliens. Tree philosophy is irrelevant to us because we're not trees. Dolphin philosophy is irrelevant to us because we're not dolphins, etc. Everything else you mentioned is "hallucinatory" and you nee…

> irrelevant to us because we're not

What an unnecessarily dismissive "argument". I'm certainly not a CPU, nor a painting, nor a bird, yet plenty of people find these topics and many others interesting.

Re: Is AI reasoning right for the wrong reasons?

#238

LLMs lack qualia, among other things. If I ask an LLM "what is an apple?" it tells me: > An apple is the edible fruit of the apple tree, scientifically known as Malus domestica. It is one of the world's most widely grown fruits and is eaten fresh or used in many foods and drinks. If I ask an LLM "what is a mundu fruit?" it tells me: > Mundu is a tropical fruit native to Southeast Asia, especially found in Indonesia,…

> but without any lived experience perhaps that's an unreasonable expectation. I don't think that follows. We learn via our perception (i.e. our inputs from the outside world); our perception is mediated by some kind of filter, and memories get written or altered. An LLM on the other hand has static weights. You can provide an LLM a "facts.md" (or whatever) file that "teaches" it stuff that's not in its weights (via…

Neither does my amygdala reshape itself and move closer to my frontal lobe, nor do my cells change their DNAs (minus damage).

Just because "the substrate" has some fixed parts doesn't materially change the equation, I think. Going even more abstract, if I have two Turing complete machines, just because one is Turing complete via some self-modification, or through some other means (e.g. game of life vs Turing machine whose states are fixed) still make them equally powerful.

Don't get me wrong, you are right to point out this shortcoming of LLMs, and I certainly don't believe we are singularity-level. I just don't think this is a good enough argument to prove these statements. A sufficiently smart intelligence that is somehow "fixed", but that can "write on paper" put in a box can't really be distinguished from a "self-modifying" intelligence. In the "worst case" it can just write down a self-modifying intelligence itself as data (since it's sufficiently smart) and execute it to emulate any kind of learning.

Re: Is AI reasoning right for the wrong reasons?

#240

Earlier quoted context omitted.

It is not semantics. For decades, logic and CS researchers have known what reasoning is. LLM folks suddenly can’t claim an approximation of that is what constitutes full scale reasoning just because they can achieve only an approximation. Imagine a calculator program that computes billions of two number multiplications accurately by looking up prior examples but fails on simple multiplications often as it doesn’t hav…

> It is not semantics. For decades, logic and CS researchers have known what reasoning is. Curious what this is!

This is a great resource

https://en.wikipedia.org/wiki/Handbook_of_Automated_Reasonin...

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