I'm not sure what you'd call a "pioneering scientific advancement", but there is an increasing amount of examples showing that LLMs can be used for research (with agents, particularly). A survey about this was published a few months ago: https://aclanthology.org/2025.emnlp-main.895.pdf

If you want to bind Tab to Accept suggestions:

Set-PSReadLineKeyHandler -Chord "Tab" -Function AcceptSuggestion

And plug.dj!

What we also learned after GPT-3.5 is that, to circumvent the need for new training data, we could simply resort to existing LLMs to generate new, synthetic data. I would not be surprised if the em dash is the product of synthetically generated data (perhaps forced to be present in this data) used for the training of newer models.

For type only though.

FWIW, there is an open-source collaborative editor for Typst that was posted a couple of weeks ago on HN: https://news.ycombinator.com/item?id=45481791

Maybe you can use Touying Exporter: https://github.com/touying-typ/touying-exporter

To add on what's been said already on slide decks, another great slide creation package in Typst is touying[1]. I've used it to create my own academic theme[2] for courses or conference presentations.

[1] https://touying-typ.github.io/ [2] https://typst.app/universe/package/touying-unistra-pristine/

> The project was recently granted new funding so the research can get to market and benefit patients.

How is it now? Has this been extended to real use outside of research?

There is a repo: https://github.com/google-deepmind/synthid-text