Nanopore data is a lot easier to analyze than short read sequencing data. You just don’t get the same alignment/assembly issues: these things sequence incredibly long reads.
> What would you say are the benefits of the grammar-of-graphics approach?
When a mathematical formalism exists, just use that. Other approaches just reinvent the wheel on an ad-hoc/piecemeal basis and end up making all sorts of unnecessary compromises.
Cognitive ability can be highly specific. If you don't use it you lose it. You may be able to keep your chess ELO high, but realize you can't implement basic algorithms in C++ quite as readily as you used to. Or you can't write as well as you used to. Or you can't quite make that old recipe taste as good as you remember.
We can argue about what skills are important or not, but these things tend to sneak up on us.
> I don't think my actual cognitive skills have declined by using AI
I'm not speaking about you but... I know most people would not have much awareness of their cognitive decline. I know this because that awareness gap is there with or without LLMs, across all age groups and cultures.
It’s easy to imagine this being a problem both in quality and in volume. Verifiable work is less valuable than verified work. And noise is always costly.
[ my public key: https://keybase.io/epgui; my proof: https://keybase.io/epgui/sigs/y564TgN5chSlzKFy-9SIa9Lpqeo22kBECpmXwEVwMJ8 ]