[alexk101]

Foundational maybe isn't the best label for this kind of model. My understanding of foundational models is that they are made to be a baseline which can be further fine tuned for specific downstream tasks. This seems more like an already fine tuned model, but I haven't looked carefully enough at the methodology to say.

[lainga]

Would you then call it a buzzword, or is there some gentler excluded-middle interpretation of that word's application to the project?

[IanCal]

I don't think it's a particular buzzword here. They claim it's useful across a range of tasks, and that's the key part imo.

Now, "predictions for parts of drug discovery" isn't the widest range, so perhaps you need to consider "foundation" as somewhat context dependent, but I don't think it's a wild claim. Neither "foundation" nor "fine tuned" are really better than each other, but those are probably the two ends of a spectrum here.

My get-out clause here is that someone with a better understanding of the field may say these are actually extremely narrowly trained things, and the tests are equivalent to multiple different coding problem challenges rather than programming/translation/poetry/etc.

[brookst]

It’s about like referring to a famous person’s red carpet attire as “off the shelf [designer name]”. It downplays the effort that went into it more than anything.