I think that the reason your mind pops is that you are not trying to understand what the person saying that is actually meaning.
Stating that we are no more than statistical inference is no different to saying that we are no more math - really, you can build the deepest mathematical truths on statistical inference.
The thing is that the math/s.i. that ML models do is too trivial in comparison to the math that would be required to describe a human identity. It can detect faces very well, it can calculate fifths roots very quickly, it can solve discrete problems quickly, yes, but its achievements are, in comparison to actual human understanding (and purpose), more closer to those of another tool, like a hammer, than those of humans.
I hear what they are saying and I reject it as trivially incorrect. Of course all we are is math. What else do you think there is?
"The thing is that the math/s.i. that ML models do is too trivial in comparison to the math that would be required to describe a human identity" why do you think this? How do you know the expressive power of neural networks? How have you guaged the expressive power of biological neural networks. How have you made any of these conclusions?
You are exasperated because when I wrote "that ML do is too trivial..." you did not realize that for ML I meant "the current state of the art of ML"...
I never assumed we are more than math. Just that there is a lot to still learn about the structure in which those buildings blocks are organized in order to fully tame what is understood as human intelligence. If we could simulate all the neurons of a real adult living brain accurately enough it would be intelligent from a human perspective, and still, both the model and us would be equally far, very far, from understanding how to arrive to that point of neural organization to achieve that kind of intelligence.
Stating that we are no more than statistical inference is no different to saying that we are no more math - really, you can build the deepest mathematical truths on statistical inference.
The thing is that the math/s.i. that ML models do is too trivial in comparison to the math that would be required to describe a human identity. It can detect faces very well, it can calculate fifths roots very quickly, it can solve discrete problems quickly, yes, but its achievements are, in comparison to actual human understanding (and purpose), more closer to those of another tool, like a hammer, than those of humans.
edit: typos/grammar