zlacker

You have pointed to the examples where the tasks are pattern recognition. I certainly agree that many tasks that humans perform are pattern recognition. But my point is that not ALL tasks are pattern recognition and intelligence involves pattern recognition but that not all of intelligence is pattern recognition.

Pattern recognition works when there is a pattern (repetitive structure). But in the case of outliers, there is no repetitive structure and hence there is no pattern. For example, what is the pattern when a kid first learns 1+1=2? or why must 'B' come after 'A'? It is taught as a rule(or axiom or abstraction) using which higher level patterns can be built. So, I believe that while pattern recognition is useful for intelligence, it is not all there is to intelligence.

>>sriniv+(OP)
Aren't axioms just training data that you feed to the model?

>>sriniv+(OP)
What I'm trying to point out is that if you had asked someone whether any of those examples were "pattern matching" prior to the discovery that neural networks were so good at them, very reasonable and knowledgeable people would have said no. They would have said that generating sentences which make sense is more than any system _which simply predicted the next character in a sequence of characters_ could do.

Given this track record, I have learned to be suspicious of that part of my brain which reflexively says "no, I'm doing something more than pattern matching"

It sure feels like there's something more. It feels like what I do when I program or think about solutions to climate change is more than pattern matching. But I don't understand how you can be so sure that it isn't.