Three categories of problem solving patterns

I think there are broadly three categories of problem solving patterns — recitation, intuition, and reasoning.

Recitation: you simply recognize a known problem and apply the steps you’ve learned. Like playing a chess opening.

Intuition: in the face of a novel situation, you (mostly subconsciously) pattern-match it to what you’ve encountered before and you “just know” what to do (sometimes without really understanding why). Could be done completely in autopilot — no awareness required. Like a very experienced chess player seeing the best move in <1s.

Reasoning: you consciously and deliberately analyze a novel situation, using a combination of abstract principles and step-by-step simulation. Like analyzing a chess position and simulating in your mind possible future trajectories.

  1. Recitation is a database lookup.
  2. Intuition is interpolative generalization or proximity-based generalization in a continuous space.
  3. Reasoning is discrete search and discrete planning.

Deep Learning (DL) models do chiefly 2, with some 1 in the mix. Some rare AI systems attempt to do 3.

Humans do a combination of 2 and 3, for the most part (recitation is a thing but is les common). By "volume", most cognition is intuition, but reasoning accounts for the most critical bits.

The term "combination" here is important. Pretty much every conscious human thought is a mix of both intuition and reasoning. There is hardly anything that is pure reasoning or pure intuition (though unconscious processing is in fact pure intuition).

The fact that you do not have to consciously think about grammar and wording when speaking in your native language (though you have to consciously follow the thread of what you
mean) was always evidence that natural language fluency could be handled by intuitive systems (DL).

Meanwhile, making sense (other than via recitation or accident) does require reasoning. Sense and fluency are distinct — obviously.

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