Max-Limelihood

5 ms·

31.
by Max-Limelihood 3y ago
13 million is substantial but not even close to the 100 million Modular got. Which really makes me wonder what Modular has been doing with that money, if they're still getting beat in benchmarks like this...
32.
by Max-Limelihood 3y ago
That's not a fundamental restriction or design problem with Julia, you're just describing JIT compilation. Plenty of languages can be compiled either ahead-of-time or just-in-time. Actually, this should be unusually easy for Jul
33.
by Max-Limelihood 3y ago
Not necessarily. Julia will always be 11 years older than Mojo, no matter how old both of them get, and that advantage won't shrink. Not to mention, Mojo is a superset of a 40-year old language with billions of dollars of development p
34.
by Max-Limelihood 3y ago
This is quite possibly the first good language comparison I've seen on HN. Good job! The upshot: 1. If you need to eke out that last extra drop of performance, and can't deal with any mistakes, Rust is good because it makes it ver
35.
by Max-Limelihood 3y ago
Are the first 3 causes dying, aging, and poor health? As soon as you start allowing abstract concepts that contribute to a person's death to count as the cause of a person's death, this stops being an especially meaningful sta
36.
by Max-Limelihood 3y ago
If nothing else, you can just pipe the code and then write comments explaining what's left after each step. But the verbose code can be substantially slower (which happens when piping can be used to perform all these operations lazily)
37.
by Max-Limelihood 4y ago
Have you tried Julia for this instead?
38.
by Max-Limelihood 4y ago
It really is that slow. You're completely correct that the speed-sensitive parts are written in lower-level libraries, but another way to phrase that is "Python can go really fast, as long as you don't use Python." But
39.
by Max-Limelihood 4y ago
In ML? No, the best competition for Python in ML is... well, it's either C++ or Julia, depending on how you define "competition," given Python is effectively a glorified C++ interface.
40.
by Max-Limelihood 4y ago
In that case I'd suggest Julia; it's got syntax pretty much identical to R, and is just as easy to pick up, but it's much, much faster, and it works as a general-ish computing language. (It's still definitely math/s
41.
by Max-Limelihood 4y ago
Nicer syntax for mathematical operations, but it's very slow (even slower than Python, similar to R) and it doesn't always work with Matlab code like it's supposed to. Julia is just a straightforward improvement (substantiall
42.
by Max-Limelihood 4y ago
> For example, error messages thrown by Julia can be multiple screens long and are as hard to read as C++ errors. The good news is this can be fixed by using AbreviatedStackTraces.jl, which will probably be added to the base language in
43.
by Max-Limelihood 4y ago
Replacing Matlab with Python in engineering seems like a very bad idea, given Python's poor performance. Matlab (and most Python) packages get around this by coding everything in C++, then just having users call that C++ code. But then
44.
by Max-Limelihood 4y ago
I think you should try out Julia, in that case. Julia installation and package management is extremely easy (MUCH easier than Python). The syntax is very similar to a cross between Matlab and Python, so it's easy to pick up if you&#x27
45.
by Max-Limelihood 4y ago
Fastest until you include the runtime. (And even then, it falls pretty far behind both Python and Julia in terms of ease-of-use.) The main advantage of R is there's a package for everything , because of how old it is. But it's no