Yes, they get confused with us evil engineers.

That’s not the history of that thing: https://en.wikipedia.org/wiki/Up_to_eleven

THANK GOD YES! Imaginary matrices are a pain to multiply!

Is this a bad thing? I always heard that here in France we have increasing forest coverage.

Alexandra Elbakyan deserves a Nobel and a presidential pardon. I doubt any other person alive now has made more for science.

A someone not in the field (CS/Machine learning) what did you expect these to be?

But… but… these are my maths shoes!

Yes, PDFs are much more permissive and may not have any semantic information at all. Hell, some old publications are just scanned images!

PDF -> semantic seems to be a hard problem that basically requires OCR, like these people are doing

I love that PDFs are so difficult to transform into HTML, too

FYI, if that’s relevant to your field, every new article published on arxiv.org now has a HTML render as well.

And on many older publications, transforming “arxiv.org” into “ar5iv.org” leads to an HTML rendering that is a best-effort experiments they ran for a while.

You are welcome.

Me as an intern in a lab, being asked among others to review a draft

Hey, can you explain to me equation 3.1? I am not sure what N and Q refers to?

Oh that one I just copied from another paper, it is not really important to the argument.

Actually I endorse the fact that we are less shy of calling “AI” algorithms that do exhibit emergent intelligence and broad knowledge. AI uses to be a legitimate name for the field that encompasses ML and we do understood a lot of interesting things about intelligence thanks to LLMs nowadays, like the fact that training on next-word-prediction is enough to create pretty complex world models, that transformer architectures are capable of abstraction or that morality arise naturally when you try to acquire all the pre-requisites to have a normal discussion with a human.

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