4 ms·

While being very capable, AI is missing something required for true intelligence and I struggle to explain exactly what it is I see missing. It's not really "c

by mythrwy 1mo ago

While being very capable, AI is missing something required for true intelligence and I struggle to explain exactly what it is I see missing. It's not really "creativity" because much of that always was derivative in my opinion. And LLMs are (for some definition of the word) fairly creative as far as taking known elements and re-arranging them. I think what is missing is sort of a world model building capability. As humans we see phenomenon and classify them informally and model "what would it look like if this were the cause of that?" type scenarios. We see qualities in phenomena and realize this applies to other things even though the things may be completely different. We run informal "thought experiments" sort of. This is hard to duplicate because a lot (most?) of it occurs outside of systems of symbols like math and language with fixed rules in my opinion. Anyway yes, lots of human thinking is statistical and LLMs have that down pretty well but they are not "smart" I have concluded and it might be a very long time, if ever, until they are. That isn't to say they aren't very capable tools which they obviously are.

buzzin__ 1mo ago
So, right of the bat, you are warning us that you are going to apply the " no true Sscottman" fallacy, and that we should brace ourselves. Yes, models posses intelligence, but it is not a true one. Then you claim that models do not posses world-building capabilities. But this is simply not true. Even ignoring the whole subgenre of scientific papers on exactly that subject, it is not that hard to build some hypothetical scenarios, big or small, and then witness the ease with which models do navigate those worlds.
- layla5alive 1mo ago
  Yes. And they are criticizing a model for not having a default mode network - as if that is some impossibility rather than just an artifact of the current iteration of the specific architectures we have built so far. Why do people paint with these broad brushes over relatively specific complaints? LLMs are likely for machine intelligence something like drosophila are to biological intelligence - relatively early on the high dimensional spectrum of possibility. Though it stikes me that in a different way they're little alike - drosophila are relatively small and efficient.
mythrwy 1mo ago
I'll restate because both objections (which apparently skim instead of read) are missing the important point. Yes LLMs can run "what ifs" scenarios and build models. However LLMs deal entirely in symbols. 100%. Humans can "world build" aside from this and in fact are often at their best doing so. Did the first humans to use fire and some form of a wheel even have the capability to talk about it? Think about that.
- willmarch 1mo ago
  Isn't thinking in images (visualizing non-verbally) also dealing entirely in symbols?
- red75prime 1mo ago
  > However LLMs deal entirely in symbols. They use tokens as input/output encoding. They do 99.9999% of processing in a high-dimensional latent space.
  - mythrwy 1mo ago
    How exactly is this high dimensional latent space represented? Pixie dust and ethereal forces? Or floating point numbers? Where does it get the weights? Reddit? Do you hold your experience of "dogs" (for instance) as floating point numbers? The fur, the fear, the love, the wet mouths, the sounds and colors?
    - red75prime 1mo ago
      Do you experience dogs as lots of action potentials traveling along axons and lots of neurons doing their thing in your brain? I don't know how it gets from the physical processes or the information processing to our first-hand experiences. So, I can't be sure that a bunch of high-dimensional vectors can't lead to experiences. Regardless, the claim "LLMs deal entirely in symbols" is wrong as a matter of fact.
      - mythrwy 1mo ago
3dddad 1mo ago
How can human thinking be statistical when it is entirely based on ones lived experiences? When people pretend to know what they are talking about - sure - but even that is not probabilistic - that is the person babbling together mush from their lived experiences. Statistics has nothing to do with it - these are abstractions humans have invented to try and look at our surroundings objectively.

by mythrwy 1mo ago

buzzin__ 1mo ago

So, right of the bat, you are warning us that you are going to apply the " no true Sscottman" fallacy, and that we should brace ourselves. Yes, models posses intelligence, but it is not a true one. Then you claim that models do not posses world-building capabilities. But this is simply not true. Even ignoring the whole subgenre of scientific papers on exactly that subject, it is not that hard to build some hypothetical scenarios, big or small, and then witness the ease with which models do navigate those worlds.

layla5alive 1mo ago
Yes. And they are criticizing a model for not having a default mode network - as if that is some impossibility rather than just an artifact of the current iteration of the specific architectures we have built so far. Why do people paint with these broad brushes over relatively specific complaints? LLMs are likely for machine intelligence something like drosophila are to biological intelligence - relatively early on the high dimensional spectrum of possibility. Though it stikes me that in a different way they're little alike - drosophila are relatively small and efficient.

mythrwy 1mo ago

I'll restate because both objections (which apparently skim instead of read) are missing the important point. Yes LLMs can run "what ifs" scenarios and build models. However LLMs deal entirely in symbols. 100%. Humans can "world build" aside from this and in fact are often at their best doing so. Did the first humans to use fire and some form of a wheel even have the capability to talk about it? Think about that.

willmarch 1mo ago
Isn't thinking in images (visualizing non-verbally) also dealing entirely in symbols?
red75prime 1mo ago
> However LLMs deal entirely in symbols. They use tokens as input/output encoding. They do 99.9999% of processing in a high-dimensional latent space.
- mythrwy 1mo ago
  How exactly is this high dimensional latent space represented? Pixie dust and ethereal forces? Or floating point numbers? Where does it get the weights? Reddit? Do you hold your experience of "dogs" (for instance) as floating point numbers? The fur, the fear, the love, the wet mouths, the sounds and colors?
  - red75prime 1mo ago
    Do you experience dogs as lots of action potentials traveling along axons and lots of neurons doing their thing in your brain? I don't know how it gets from the physical processes or the information processing to our first-hand experiences. So, I can't be sure that a bunch of high-dimensional vectors can't lead to experiences. Regardless, the claim "LLMs deal entirely in symbols" is wrong as a matter of fact.
    - mythrwy 1mo ago

3dddad 1mo ago

How can human thinking be statistical when it is entirely based on ones lived experiences? When people pretend to know what they are talking about - sure - but even that is not probabilistic - that is the person babbling together mush from their lived experiences. Statistics has nothing to do with it - these are abstractions humans have invented to try and look at our surroundings objectively.