[anon35]

Think of it as: reasoning=computation, knowledge=data. Data alone doesn’t say it must be computed. But computation, by definition, is attempting to create data (the result) that doesn’t exist. Thus: knowledge isn’t aware it must be reasoned about, but reasoning knows it’s trying to find (deduce, compute) knowledge it lacks.

[NoToP]

I disagree. If you have knowledge, and you don't try to do anything other than compress it to make space, reasoning about that knowledge will come about by sheer unintended consequence once the patterns your compressing on reach some threshold of sophistication.

By definition, an optimal compression algo is a dimensionality reduction algo. A dimensionality reduction algo lets you do a bunch of machine learning tasks.

[kreeben]

In the world of large language models, what part of "reasoning" is hard-coded and what part, if any, is learnt?

Is reasoning simply a scan/search of your vector space (i.e. your knowledge) according to some hard-coded algo?

[synu]

Thanks for that!