It's a sad time to be a fan of Julia-- everyone forgets it's there.

Especially when it is actually successful at what it was designed to be, a faster Python for data science folks, having gotten enough researchers, more than most toy languages that almost daily drop on HN and Reddit.

I was excited to try Julia, but then, as I saw it was an interpreted language, with bulky runtime, slow startup times and bloated library sizes - my initial interest quickly faded.

For the same reasons I see languages like Python, Java, C# as inferior.

How is Julia an interpreted language? I sometimes wish there was a robust interpreter for Julia when the compilation latency is not worth the execution speed.

Julia compiles to native code, same as C++/Rust.

Java and C# definitely don't belong on the same basket.

And inferior to what, the crab?

Inferior to languages that compile to native binaries, not burning dramatically more cpu cycles than necessary.

Showing your ignorance regarding Java and C# ecosystems and available compilers on that reply.

I indeed don't know about Java, but with C# there are a lot of limitations if you want AOT compilation and you still get the bloated binary and limited performance.

I also, personally, never seen a single project written in either Java or C# that distributes aot binaries.

You mean bloated as Go, the superior language?

The limited performance of game engines like the one used by Capcom for Devil May Cry on the Playstation 5?

Java binaries deployed in embedded systems by PTC and Aicas are AOT compiled.

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