something tells me the lonboard basemap refactor will now move forward quickly :P

😂 this is reminding me a bit of the rube-goldberg machine that is [rvlib](github.com/QuantEcon/rv...)

... a python package that uses numba's foreign functions interface to call a C library written for R--all designed to make the python api work more like julia 🤯

lol i think it's really just the call chain though... afaict the rust HiGHS interface is just a passthrough, and all the algos are *actually* written in C++

(i guess it's easier to bind r to rust, and rust to C++ than make r talk to c?). Feels like rust is almost a cython-like layer here

great work as usual. It's using the rust interface to HiGHS?

(fwiw, ive been happy as both a user and contributor under that model. Once my book is slightly further along I'm going to remove the "no derivatives" clause so its easier for people to riff on examples)

you own the copyright, so one way this is handled in open source is to license the materials under something permissible but requiring citation to you (e.g. CC BY: creativecommons.org/share-your-w... )

often a good compromise because the person gets to 'teach your slides', but you get credit

wait they're trying to put kansas city into kansas??

wait, doesn't every scooby doo villain already meet all of those criteria?

*chefs kiss*

remote sensing is AI now, because $

Is logistic regression "AI"? What about convex optimization? Is LLM AI? What about an image recognition system built without using "feature learning" techniques but done through "feature engineering"?

in other words, this:

"geo" is already such a huge umbrella that 'geoai', as a term, is basically meaningless

lolol you're making my point. the db was beaten by 3 steps when the ball was thrown and any starting qb makes that throw. db hanging off moore during the catch says a great deal more about the catch than the throw. i'm not arguing with you man; think what you want

man, both of those throws at the end were first-read to open receivers. color me unimpressed.

...i'll grant you that malik literally fumbled the game away...

lol it was meant as jest, but i am actually of the staunch opinion that a) social sciences are harder than natural sciences, as a general rule [and b) LLMs are generally bullshit machines]

i'm not sure the degree to which those contradict your point (though also geo is too often reduced to "a map")

to be clear, i dont think 'artificial intelligence' is really an accurate description in either context and both groups are using it because marketing, but the physical geography application is much more appropriate

...even though human geog, as a social science, is a much harder discipline :P