I think of it as System 1 vs System 2 thinking from 'Thinking, Fast and Slow' by Daniel Kahneman.[1]
Deep learning is very good at things we can do without thinking, and is in some cases superhuman in those tasks because it can train on so much more data. If you look at the list of tasks in System 1 vs System 2, SOTA Deep learning can do almost everything in System 1 at human or superhuman levels, but not as many in System 2 (although some tasks in System 2 are somewhat ill-defined), System 2 builds on system 1. Sometimes superhuman abilities in System 1 will seem like System 2. (A chess master can beat a noob without thinking while the noob might be thinking really hard. Also GPT-3 probably knows 2+2=4 from training data but not 17 * 24, although maybe with more training data it would be able to do math with more digits 'without thinking' ).
System 1 is basically solved, but System 2 is not. System 2 could be close behind System 2 by building on System 1 but it isn't clear how long that will take.
> a series of short sentences that mimic the reasoning process a person might have when responding to a question
Worried about the choice of the word 'mimic' - which as usual seems to retain the usual distance from foundational considerations.
Edit: nonetheless, the results of "Chain of Thought Prompting Elicits Reasoning in Large Language Models" are staggering and do seem, at least in appearance, go towards the foundationals.
In biological history, system two was an afterthought at best. It likely didn't exist before spoken language, and possibly barely before written language. And to the extent that system two exists, it's running on hardware almost entirely optimized for system one thinking.
Deep learning is very good at things we can do without thinking, and is in some cases superhuman in those tasks because it can train on so much more data. If you look at the list of tasks in System 1 vs System 2, SOTA Deep learning can do almost everything in System 1 at human or superhuman levels, but not as many in System 2 (although some tasks in System 2 are somewhat ill-defined), System 2 builds on system 1. Sometimes superhuman abilities in System 1 will seem like System 2. (A chess master can beat a noob without thinking while the noob might be thinking really hard. Also GPT-3 probably knows 2+2=4 from training data but not 17 * 24, although maybe with more training data it would be able to do math with more digits 'without thinking' ).
System 1 is basically solved, but System 2 is not. System 2 could be close behind System 2 by building on System 1 but it isn't clear how long that will take.
[1]. https://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow#Summar...