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I am impressed. Whenever I try to build a tree of thoughts, I run into the problem that I want things to fall under multiple categories. I might start by classifying them according to subject area (as you have done), but then I might want a collection of those notes to also fall under "could help with project X" or "would be of interest to person Y" or "can be learned from reference Z" or any number of things.

This is a use of AI I've not seen yet, to sift through soups of knowledge, categorise it and make judgements on what else is related and relevant

Isn't this essentially what search engines do? Ie. Google's Page Rank.

It doesn't really seem very AI-ish except maybe for some NLP. Otherwise it's very straightforward indexes and catelogues.

I used to work at a company that used Elasticsearch to catelog and group articles and small snippets. I'm currently working at a company that's using Algolia to do something similar.

Not really what I had in mind, to be honest. I mean, yes, you can search by keyword, but I was thinking of it being more like a research assistant.

Isn't that what tags are for? Search by tag?

I don't know. Can you point at an implementation you like?

[pinboard.in][1] has an implementation that I like. What I especially like about pinboard is that you can chain tags together (logically AND'd, not OR'd) to narrow/filter topics to highly specific criteria. This all works well provided you usefully tag your entries.


This is what links were originally invented for.

Links are fragile and one-sided. You might move the destination. You might edit the title of the destination and want that to show up in the link text. You might want the content, not just the title, to be visible (preferably foldable) from where the link is. You might want to be able to see from the destination what links to it.

In Hugo its actually pretty easy to color code whether a page/destination exists. Optionally you could do up a Wiki using the Media Wiki stuff. Then links are color coded automatically.

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