We've just launched a new experimental feature: "Automated Jargon Glossaries." If it goes well, it may pave the way for things like LaTeX hoverovers and other nice things.

Whenever an author with 100+ karma saves a draft of a post, our database queries a language model to:

• Identify terms that readers might not know.
• Write a first draft of an explanation of that term
• Make a guess as to which terms are useful enough to include.

By default, explanations are not shown to readers. Authors get to manually approve term/explanations that they like, or edit them. Authors will see a UI looking like this, allowing them to enable terms so readers see them. They can also edit them (by clicking on the term).

Meanwhile, here's a demo of what readers might see, from the Infra-Bayesian physicalism post.[1]

TLDR: We present a new formal decision theory that realizes naturalized [...]

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Outline:

(01:54) 0. Background

(02:47) Managing Slop: Author Approval and Opt In

(06:16) The longterm vision

(06:31) Automated adjust to reader level.

(07:26) The 0-1 second level

(08:33) LaTeX

(08:52) Curating technical posts

(09:52) Higher level distillation

(10:27) Remember AI capabilities are probably bad, actually

(11:05) Feedback

The original text contained 1 footnote which was omitted from this narration.

The original text contained 1 image which was described by AI.

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First published:

Source:

Narrated by TYPE III AUDIO.

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Images from the article:

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