Comment by kristopolous

I think this applies to everything right now. Papers like this are just ridiculous examples. In like, 6th grade I won second place at the LA county science fair for coding a simulation of a coyote's life in hypercard (with tons of graphs). Yay. Y'know what? That shit and those graphs would've been incomprehensible to the judges if it hadn't been written in plain language, in an attempt to make them understand what they were looking at. My entire career since has been an attempt to communicate and alleviate the pain points in communication between parties, by way of writing software that encapsulated their descriptions of what they needed. And likewise I never pretended to be smarter or know more than my clients did: Everything must be explained and comprehensible in normal people language. People need to know how shit works, especially if they're paying for it.

Or they should.

Or if they don't know and don't care, they're fucking negligent.

Especially if they say "wow that sounds smart, let's let these guys run our weapons program".

To your point, the reason this ornate language thrives and people get away with complacency about how their own systems work, boils down to a silent pact between managers and engineers to sweep everything under the rug out of laziness and ill-will. There's something blatantly mendacious and evil (in the banal way) about the agreement that managers approve black boxes which were approved by complex-sounding papers so that upper management can wash their hands of the results.

[edit] maybe I'm just bitter because I spent hours today pondering exactly how many engineers at Monsanto must have known about the dangers of the astroturf, and how many raised their hand, or hid behind a spreadsheet

https://frontofficesports.com/investigation-links-astroturf-...

“Engineers who like to pretend to be mathematicians” - I heard once.

What I find entertaining/confounding is how difficult the abstracts to these new AI papers are to understand. It feels like academia is pushing this style, so it’s hard to blame the authors since they have to play the game.

For reference I have an undergrad degree in computer science, have been working professionally for 25 years, and am fairly data centric in my work.

I’m hoping when I run this through GPT4 to get an explanation for a mortal software developer something sensible comes out the other end.

"Not math-y enough"/ "Needs more math" is a very common feedback ML/AI researchers get when writing papers.

The other day I was watching a live-stream of a doctoral defense, as the thesis was quite relevant to my work.

So one of the committee members would really pick and criticize the math - ask questions like "You are supposed to be the bleeding edge on this topic, why was the math so simple? Did you research more rigorous theories to explain the math?" etc. (He was awarded the doctorate though)

So, I dunno, if that's how things are now - it makes sense to me that the authors go overboard with complicated notation, even if they could have written it much simpler. Probably makes the work seem more rigorous and legit.

Doesn't really take that much more time, and it covers your ass from "not rigorous enough" gotchas - though at the expense of readability.

If the excuse is true and the "ornate" language really is a dense representation of information then it should be fairly trivial to have an LLM agent unsummarize it.

There could be a webservice that offers a parallel track of layman's translations of any paper.

That's literally the entire field of philosophy after the ~18th century.

I wish also. When I was young and new, so much wasted time trying to parse the 'arcane' math that was really something simple bug dressed up as complicated to give it weight.

People have to get their PhD's somehow... ;)