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Four Fallacies of Modern AI

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Re: Four Fallacies of Modern AI

#91

Post by mcv »

koonsolo wrote: post #40
AIPedant wrote: post #33

Earlier quoted context omitted.

"Making predictions about the world" is a reductive and childish way to describe intelligence in humans. Did David Lynch make Mulholland Drive because he predicted it would be a good movie? The most depressing thing about AI summers is watching tech people cynically try to define intelligence downwards to excuse failures in current AI.

I look at it the complete opposite way: humans are defining intelligence upwards to make sure they can perceive themselves better than a computer. It's clear that humans consider humans as intelligent. Is a monkey intelligent? A dolphin? A crow? An ant? So I ask you, what is the lowest form of intelligence to you? (I'm also a huge David Lynch fan by the way :D)

Intelligence has been a poorly defined moving goal post for as long as AI research has been around.

Originally they thought: chess takes intelligence, so if computers can play chess, they must be intelligent. Eventually they could, and later even better than humans, but it's a very narrow aspect of intelligence.

Struggling to define what we mean by intelligence has always been part of AI research. Except when researchers stopped worrying about intelligence and started focusing on more well-defined tasks, like chess, translation, image recognition, driving, etc.

I don't know if we'll ever reach AGI, but on the way we'll discover a lot more about what we mean by intelligence.

Re: Four Fallacies of Modern AI

#92

Post by mcv »

koonsolo wrote: post #51
peterashford wrote: post #48

Earlier quoted context omitted.

Im not sure what that gets you. I think most people would suggest that it appears to be a sliding scale. Humans, dolphins / crows, ants, etc. What does that get us?

Well, is an LLM more intelligent than an ant?

I would say yes. But is it more intelligent than an ant hill?

Re: Four Fallacies of Modern AI

#93

Post by mcv »

keiferski wrote: post #31
ta20240528 wrote: post #11

Earlier quoted context omitted.

> Language doesn't just describe reality; it creates it. I never under stand these kinds of statements. Does the sun not exist until we have a word for it, did "under the rock" not exist for dinosaurs?

I think create is the wrong word choice here. Shaping reality is a better one, as it doesn't hold the implication that before language, nothing existed. Think of it this way, though: the divisions that humans make between objects in the world are largely linguistic ones. For example, we say that the Earth is such-and-such an ecosystem with certain species occupying it. But this is more like a convenient shorthand, no…

I'm immediately thinking about Sapiens, by Harari. One of the big points of that book is that much of our reality is made up. Countries, laws, corporations, property, -isms, marriage, and many other things only exist because we all agree to believe in them. These are part of our shared subjective reality, created by our words and actions, and they will cease to exist the moment everybody stops believing in them.

Re: Four Fallacies of Modern AI

#94

Post by visarga »

vrighter wrote: post #66
visarga wrote: post #32

I think the Stochastic Parrots idea is pretty outdated and incorrect. LLMs are not parrots, we don't even need them to parrot, we already have perfect copying machines. LLMs are working on new things, that is their purpose, reproducing the same thing we already have is not worth it. The core misconception here is that LLMs are autonomous agents parroting away. No, they are connected to humans, tools, reference data,…

You can shuffle a deck of 52 cards, and be reasonably confident that nobody has ever gotten that exact shuffle (or probably ever will, until the universe dies). But at least in this case, we are sure that a deck of 52 cards can be arranged in any permutation of 52 cards. We know we can reach any state from any other state. This is not the case for LLMs. We don't know what the full state space looks like. Just because…

> but you still have no way of knowing whether A) it's the string of symbols you wanted

Time will tell. You take that output, use it, and see the outcomes. That's exactly how brains work too. We don't spark knowledge from our brains, it comes from environment observation.

Re: Four Fallacies of Modern AI

#95

Post by PolicyPhantom »

It’s true that much of the debate around AI swings between extremes — utopian promises on one side, dystopian collapse on the other. But institutions don’t operate well in extremes.

What matters is how we design governance that acknowledges uncertainty while still enabling progress. In practice, that means imperfect but adaptive frameworks — guardrails that evolve as technology and society evolve.

Instead of asking “which fallacy is right,” we might ask: how do we build systems that remain trustworthy even when our assumptions about AI turn out to be wrong?

Re: Four Fallacies of Modern AI

#96

Post by vrighter »

visarga wrote: post #94
vrighter wrote: post #66

Earlier quoted context omitted.

You can shuffle a deck of 52 cards, and be reasonably confident that nobody has ever gotten that exact shuffle (or probably ever will, until the universe dies). But at least in this case, we are sure that a deck of 52 cards can be arranged in any permutation of 52 cards. We know we can reach any state from any other state. This is not the case for LLMs. We don't know what the full state space looks like. Just because…

> but you still have no way of knowing whether A) it's the string of symbols you wanted Time will tell. You take that output, use it, and see the outcomes. That's exactly how brains work too. We don't spark knowledge from our brains, it comes from environment observation.

you're describing a general version of bogosort
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