Comment by ffwd | Hacker News Reader

Comment by ffwd | Hacker News Reader

I think something that's missing from AI is the ability humans have to combine and think about ANY sequence of patterns as much as we want. A simple example is say I think about a sequence of "banana - car - dog - house". I can if I want to in my mind, replace car with tree, then replace tree with rainbow, then replace rainbow with something else, etc... I can sit and think about random nonsense for as long as I want and create these endless sequences of thoughts.

Now I think when we're trying to reason about a practical problem or whatever, maybe we are doing pattern recognition via probability and so on, and for a lot of things it works OK to just do pattern recognition, for AI as well.

But I'm not sure that pattern recognition and probability works for creating novel interesting ideas all of the time, and I think that humans can create these endless sequences, we stumble upon ideas that are good, whereas an AI can only see the patterns that are in its data. If it can create a pattern that is not in the data and then recognize that pattern as novel or interesting in some way, it would still lack the flexibility of humans I think, but it would be interesting nevertheless.

one possible counter-argument: can you say for sure how your brain is creating those replacement words? When you replace tree with rainbow, does rainbow come to mind because of an unconscious neural mapping between both words and "forest"?

It's entirely possible that our brains are complex pattern matchers, not all that different than an LLM.

That's a good point and I agree. I'm not a neuroscientist but from what I understand the brain has an associative memory so most likely those patterns we create are associatively connected in the brain.

But I think there is a difference between having an associative memory, and having the capacity to _traverse_ that memory in working memory (conscious thinking). While any particular short sequence of thoughts will be associated in memory, we can still overcome that somewhat by thinking for a long time. I can for example iterate on the sequence in my initial post and make it novel by writing down more and more disparate concepts and deleting the concepts that are closely associated. This will in the end create a more novel sequence that is not associated in my brain I think.

I also think there is the trouble of generating and detecting novel patterns. We know for example that it's not just low probability patterns. There are billions of unique low probability sequences of patterns that have no inherent meaning, so uniqueness itself is not enough to detect them. So how does the brain decide that something is interesting? I do not know.

>I can for example iterate on the sequence in my initial post and make it novel by writing down more and more disparate concepts and deleting the concepts that are closely associated. This will in the end create a more novel sequence that is not associated in my brain I think.

This seems like something that LLMs can do pretty easily via CoT.

As a fun test, I asked ChatGPT to reflexively given me four random words that are not connected to each other without thinking. It provided: lantern, pistachio, orbit, thimble

I then asked it to think carefully about whether there were any hidden relations between them, and to make any changes or substitutions to improve the randomness.

The result: fjord, xylophone, quasar, baklava

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