Thanks for making this point! I'm chiming in just to add that the Jupyter Book project that builds MyST tooling is now using a new TypeScript stack instead of Sphinx, for any interested newcomers!
But yes, ^this. We are building around a shareable AST precisely because structure really matters.
The problem of "where did I see that" is something I suspect most people have encountered before. How that's actually done, though, is the devil. The vision -- semantic search of human experience -- is cool. The implementation -- always recording cameras piping every minute of your life to TotallyTrustworthyPeople's servers -- not so.
General chatbots are great for things they have general data about. "What was that movie where..." type things. They don't help with individualized information, unless you feed the same type of information as Recall type solutions gather anyways. Perhaps you don't have much individualized information, or perhaps you just remember it all very aptly - it shouldn't be hard to imagine differently though.
My main usage problem with Recall type solutions is less with lack of something to promise and more with lack of ability to deliver. Especially for local-only solutions. The concept can be great as can be, but it needs to be damn near foolproof to beat out how much we already remember.
I love this angle, and would take it further. I'm starting to think about AI in the same way that we think about food ethics.
Some people are vegan, some people eat meat. Usually, these two parties get on best when they can at least understand each-other's perspectives and demonstrate an understanding of the kinds of concerns the other might have.
When talking to people about AI, I feel much more comfortable when people acknowledge the concerns, even if they're still using AI in their day-to-day.
MyST Markdown (the MD flavour, not the same-named Document Engine) was inspired by ReST. It was created to address the main pain-point of ReST for incoming users (it's not Markdown!).
As a project, the tooling to parse MyST Markdown was built on top of Sphinx, which primarily expects ReST as input. Now, I would not be surprised if most _new_ Sphinx users are using MyST Markdown (but I have no data there!)
Subsequently, the Jupyter Book project that built those tools has pivoted to building a new document engine that's better focused on the use-cases of our audience and leaning into modern tooling.
The PyPI ecosystem can not, for the foreseeable future, replicate the scope of the conda ecosystem. From microarch builds to library deduplication, conda is a more general purpose solution. That doesn't mean that one "wins out" (and, for reference I predominantly use Python's PyPI), but they're not the same tools.
I don't disagree with the general vibe here, but a few points:
- It's hard to compare Omicron vs delta because of the number of confounding variables - population heterogeneity, vaccine + infection induced immunity, etc.
- Severe strains with latency periods are invulnerable to symptom recognition. I don't think the asymptomatic period for the COVID variants varied as much in the lower bound as it did the upper bound. The point being -- behavioural changes are much more likely to be general caution (i.e. limiting contacts, spacing social events in time, etc.) than responsive (I feel unwell).
Just a note on MyST's citations feature as I was researching it this morning: until this ticket [1] is worked on there's one bibliography style and that's it.
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