htmz is a minimalist HTML microframework for creating interactive and modular web user interfaces with the familiar simplicity of plain HTML.

This is a tangent, but I wonder if they feel that they are just creating LLM training data and that few readers (even of Sunday papers) will actually read their reviews.

If the query uses the index, then the on the fly tsvector rechecks are only on the matches and the benchmark queries have LIMIT 10, so few rechecks right?

Edit: yes but the query predicates have conditions on 2 gin indexes, so I guess the planner chooses to recheck all the matches for one index first even though it could avoid lots of work by rechecking row-wise

Also, 10M input token context is insane!

EDIT: https://huggingface.co/meta-llama/Llama-3.1-405B is BF16 so yes, it seems training in FP8 is new.

At one time I thought I read that there was a project to embed Kuzu into DuckDB, but bringing a vector store natively into kuzu sounds even better.

But I do think the legacy browser behavior with the ID attribute as window properties is very brittle for the reasons you suggest

Edit: My tone may have indicated that parent's solution was brittle. It's not!

I was also very fond of Phabricator (all though my team preferred GitHub style pull requests) but I haven't had a need for it recently, so I haven't tried phorge myself.

[0] - https://chromewebstore.google.com/detail/max-tabs/ghhcibaghj...

My pyenv python3.12.2's sqlite won't load extensions even after installing with what I think are the correct command line flags. Argh!

My brew installed python3.12's sqlite will load extensions though, so I can proceed.

In a way, its a search problem where bid≈relevance and targeting_match≈recall, so I've seen Solr used here too.