I’m rather certain Bob punting his paycheque on short-dated options is not a complex decision about the future

arxiv.org/abs/2302.06710

Looks interesting!

Models from the leading companies are trained on LibGen or similar hence also on paywalled papers

Very roughly speaking of course :-)

I saw this :-) looks interesting indeed. Unfortunately it’s too much material on a subject I’m only dabbling in. Maybe in the future!

Summarized in the first paragraph

Also read this but unfortunately gained relatively little from it. I'll probably have to revisit it at some point
www.probabilityandfinance.com/misc/snapsho...

www.math.uci.edu/~rvershyn/pa...

@shubhendu.bsky.social I just thought of 2 :-) Bombastic claims as a negative signal? And mentions of simplicity or naturalness as a positive one? What do you reckon?

The keywords strategy works reasonably well for stat.ML and stat.ME but seemingly less so for math.ST because I find that the titles are a lot more “obscure”

Are there nice heuristics you can recommend for arXiv? :-) I’ve mostly been relying on name recognition and keywords related to topics I’m interested in which feels unfortunate

It's a great discussion because we all have different interpretation of what this means and what the consequences are.

Myself, I have absolutely no doubt that scaling works. If you have all the videos in the world and are able to train a model that can recall and merge any of them, then for sure...