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Four Fallacies of Modern AI

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Re: Four Fallacies of Modern AI

#31

Post by keiferski »

ta20240528 wrote: post #11
theturtlemoves wrote: post #7

I've always had the feeling that AI researchers want to build their own human without having to change diapers being part of the process. Just skip to adulthood please, and learn to drive a car without having experience in bumping into things and hurting yourself. > Language doesn't just describe reality; it creates it. I wonder if this is a statement from the discussed paper or from the blog author. Haven't found th…

> 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, not a totally accurate description of reality. A more accurate description would be something like, ever-changing organisms undergo this complex process that we call evolution, and are all continually changing, so much so that the species concept is not really that clear, once you dig into it.

https://plato.stanford.edu/entries/species/

Where it really gets interesting, IMO, is when these divisions (which originally were mostly just linguistic categories) start shaping what's actually in the world. The concept of property is a good example. Originally it's just a legal term, but over time, it ends up reshaping the actual face of the earth, ecosystems, wars, migrations, on and on.

Re: Four Fallacies of Modern AI

#32

Post by visarga »

I think the Stochastic Parrots idea is pretty outdated and incorrect.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, and validation systems. They are in a dialogue, and in a dialogue you quickly get into a place where nobody has ever been before. Take any 10 consecutive words from a human or LLM and chances are nobody on the internet stringed those words the same way before.

LLMs are more like pianos than parrots, or better yet, like another musician jamming together with you, creating something together that none would do individually. We play our prompts on the keyboard and they play their "music" back to us. Good or bad - depends on the player at the keyboard, they retain most control. To say LLMs are Stochastic Parrots is to discount the contribution of the human using it.

Related to intelligence, I think we have a misconception that it comes from the brain. No, it comes from the feedback loop between brain and environment. The environment plays a huge role in exploration, learning, testing ideas, and discovery. The social aspect also plays a big role, parallelizing exploration and streamlining exploitation of discoveries. We are not individually intelligent, it is a social, environment based process, not a pure-brain process.

Searching for intelligence in the brain is like searching for art in the paint pigments and canvas cloth.

Re: Four Fallacies of Modern AI

#33

Post by AIPedant »

entropyneur wrote: post #18

This article seems to fall straight into the trap it aims to warn us about. All this talk about "true" understanding, embodiment, etc. is needless antropomorphizing. A much better framework for thinking about intelligence is simply as the ability to make predictions about the world (including conditional ones like "what will happen if we take this action"). Whether it's achieved through "true understanding" (however…

"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.

Re: Four Fallacies of Modern AI

#34

Post by keiferski »

entropyneur wrote: post #18

This article seems to fall straight into the trap it aims to warn us about. All this talk about "true" understanding, embodiment, etc. is needless antropomorphizing. A much better framework for thinking about intelligence is simply as the ability to make predictions about the world (including conditional ones like "what will happen if we take this action"). Whether it's achieved through "true understanding" (however…

It matters if your civilizational system is built on assigning rights or responsibilities to things because they have consciousness or "interiority." Intelligence fits here just as well.

Currently many of our legal systems are set up this way, if in a fairly arbitrary fashion. Consider for example how sentience is used as a metric for whether an animal ought to receive additional rights. Or how murder (which requires deliberate, conscious thought) is punished more harshly than manslaughter (which can be accidental or careless.)

If we just treat intelligence as a descriptive quality and apply it to LLMs, we quickly realize the absurdity of saying a chatbot is somehow equivalent, consciously, to a human being. At least, to me it seems absurd. And it indicates the flaws of grafting human consciousness onto machines without analyzing why.

Re: Four Fallacies of Modern AI

#37

Post by simianwords »

AIPedant wrote: post #33
entropyneur wrote: post #18

This article seems to fall straight into the trap it aims to warn us about. All this talk about "true" understanding, embodiment, etc. is needless antropomorphizing. A much better framework for thinking about intelligence is simply as the ability to make predictions about the world (including conditional ones like "what will happen if we take this action"). Whether it's achieved through "true understanding" (however…

"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.

"David Lynch made Mullholland Drive because he was intelligent" is also absurd.

Re: Four Fallacies of Modern AI

#38

Post by ttoinou »

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,…

The fact that it can copy smartly exactly ONE of the information in a given prompt (which is a complex sentence only humans could process before) and not others is absolutely a progress in computer science, and very useful. I’m still amazed by that everyday, I never thought I’d see an algorithm like that in my lifetime. (Calling it parroting is of course pejorative)

Re: Four Fallacies of Modern AI

#39

Post by simianwords »

> But that still leaves a crucial question: can we develop a more precise, less anthropomorphic vocabulary to describe AI capabilities? Or is our human-centric language the only tool we have to reason about these new forms of intelligence, with all the baggage that entails?

I don't get the problem with this really. I think LLM's "reasoning" is a very fair and proper way to call it. It takes time and spits out tokens that it recursively uses to get a much better output than it otherwise would have. Is it actually really reasoning using a brain like a human would? No. But it is close enough so I don't see the problem calling it "reasoning". What's the fuss about?

Re: Four Fallacies of Modern AI

#40

Post by koonsolo »

AIPedant wrote: post #33
entropyneur wrote: post #18

This article seems to fall straight into the trap it aims to warn us about. All this talk about "true" understanding, embodiment, etc. is needless antropomorphizing. A much better framework for thinking about intelligence is simply as the ability to make predictions about the world (including conditional ones like "what will happen if we take this action"). Whether it's achieved through "true understanding" (however…

"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)

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