alt Hacker NewsI often wonder if there aren't some low hanging fruit in the nature of the python ecosystem surrounding AI/ML these days. I'm sure there are a lot of eyeballs looking at the problem, but every time I fire up a chat and see the python loadout, it "feels" like there might be work yet still to be done to make things as fast as possible.
And then, while I'm waiting for a response on things, the mind wanders to thinking about what the rust camp are doing, with regards to AI/ML.
To my addled mind, it really seems like the first thing to be done when getting the models firing, is turn them on their own tools and optimize, optimize, optimize. I'd sure like to know what the frontier labs are doing to squeeze those ergs out of our substrates.
Does anyone have clues what the landscape looks like outside the python tooling, vis a vis higher-performance infrastructure? Being glib about it I admit, it just seems 'odd' that the C/C++/Rust camp are letting scripting languages drive the AI/ML ship.
Mostly because many on that camp are averse to nice tooling, like REPLs, JITs, or incremental compilation.
They do exist, but again, not really loved enough.
https://clang.llvm.org/docs/ClangRepl.html
https://github.com/jupyter-xeus/xeus-cling
https://root.cern/cling
Additionally, while in the past there are been nice high level libraries for C++, which is where Java took its inspiration from in first place[0], current culture seems to hate having such frameworks around, and they are mostly gone nowadays.
[0] - It isn't writing Java in C++, rather how C++ inspired by Smalltalk used to look like, 1983 - 2000's, before Java got released in 1996.