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what are your favorite examples of distillation in different fields?
Is this question the same as "what are your favorite examples of pedagogy in different fields?" Or if not, what's the difference?
Good question - frankly, I'm not sure!
I have an intuitive sense that distillation (as defined in the Research Debt article) differs from pedagogy by focusing more on clarity, being more opinionated, and drawing connections between topics/fields while focusing less on comprehensiveness and accessibility. Admittedly though, some of my favorite examples of distillation--Paths Perspective on Value Learning, If correlation doesn't imply causation, then what does?--are also quite accessible as pedagogical examples. That said, I do think these examples illustrate the opinionated point. These authors are writing about the parts of their topics that interest them and from their perspectives, not trying to describe the topics comprehensively.
Let me just reiterate that this is me thinking out loud. I have not yet distilled the difference between distillation and pedagogy.
Thought I just had after writing this: I think distillation is probably a subset of pedagogy.
I'm a big fan of the Distill machine learning journal and the ideas of Research Debt and distillation. I consider Distill and LessWrong great repositories for distillations of ML / AI and some math topics. However, I've recently been hankering for distillations from other fields with which I'm somewhat familiar -- biology, algorithms, economics-- or even not that familiar. (John Wentworth's recent series of posts on aging and constraints are good examples of one form posts like this could take.)
So, I figured I'd ask here: what are your favorite examples of distillation in different fields? I'm open to more ML / AI related posts but am especially excited about responses in the fields I mentioned above or other different fields (I would include math here too). Ideal answers would be posts that optimally trade off: