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Here's a trivial example to illustrate the difference between pattern recognition and reasoning and it impacts behavior generation: let's say you encounter, for the very first time, a glass door with ⅃⅃Uꟼ written on it.
Pattern recognition: nearest neighbor is "PULL", I've learned to associate that with pulling the door. I pull. Reasoning: that's a mirror image of "PULL". Must be written on the other side. The door will open by pulling towards the other side, i.e. pushing from this side. I push
Only multi-step reasoning (which is slow and resource-intensive) enables zero-shot adaptation to novel situations. Meanwhile, pattern recognition makes navigating well-known situations faster and more efficient.
typo: "and *how* it impacts behavior generation"
One could argue with that - could interpret that we do object recognition via a Hawkins reference frame, rotated to correct for aberration, and then further "recognize" cross-temporal patterns of permitted motion relative to the door/sign frame.
This might actually be a good way to approach design of multi-step reasoning. Perception followed by contextual reasoning?
Pattern recognition combined with physics is needed for reasoning to kick in.
Laugh if you want, but my observation of a few highly intelligent people would overanalyze this. Pull out, pull up, pull down. I'm a simple man; some see situations like this and apply multiple solutions, not always beneficial or positive outcomes.
if your pattern recognition system is good enough / generalizes systematically, it would have a representation for "PULL" and a representation for "reverse" and would combine these to arrive at "PUSH".
I'm not trying to argue there is no difference between reasoning and pattern recognition, but I don't think this example illustrates it.
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