Imagine a future where you could tell if your shit's broken by recompiling it, and your "deployment" would be just putting some RPC in front of your existing code.
If it's not too forward, do you know at the moment if FastAI will continue to invest in Swift? I know development was a bit stalled due to the work needed for FastAI 2.0, but I was wandering if it'll resume, or if Richard Wei and Chris Lattner leaving changes anything?
Cheers and thanks for FastAI!
PD: Was working a bit on SwiftCV, added the videoio and highgui modules. Was wondering if I should PR it to fastai's or vvmnnnkv's version of the repo?
(Most data scientists on Windows, including me, use SSH to connect to a GPU server running Linux for training models.)
Anyone that cares about bash on Windows can install mingw or WSL, preferably WSL2.
Tablets don't have CLIs by default.
Even if UNIX clones ruled the world, chsh is a thing.
All of them much more mature than Swift, outside Apple's eco-system, including being able to target CUDA.
Also C++17/C++20 isn't that bad.
I learned C++ARM at the age of 16, and many Portuguese universities teach it at first year students, surely newcomers can grok it.
Also Portuguese universities seem to be out of sync with the rest of the world if they teach C++. In the US most people with a CS degree haven't been exposed to C++. It's either Java or something functional. C++ typically doesn't even come up. Which is pretty puzzling to me, because most of the programs I use daily (including this very browser) are C++ programs.
Also, I actually learned C++ during high school, back when C++ARM was the only "standard", and most C compilers still did a mix of K&R and C89.
Nowadays many high schools do stuff with Raspeberry PI and Arduinos (Processing is just C++).
And you have books like these available https://www.amazon.de/f%C3%BCr-Kids-Grundlagen-Spieleprogram...
I think a compiled subset of python is the best way to make that happen. All of the JITs (Numba, PyTorch, Jax, etc) already handle a decent portion of the language, so it should be doable.
But yes, I think S4TF has had zero interest among people actually doing ML and is probably dead. It might take Google a while to actually kill it off, though.
From conversations I’ve had with people doing ML, if they know about S4TF at all they actively dislike certain aspects (for example that it’s based on a statically typed language), or are dismissive of others (like support for differentiation, which is a neat parlor trick but saves a tiny bit of effort).