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To this day, whenever I see Machine Learning abbreviated, my heart skips a beat, then I become crestfallen as I realize I'm not about to read something about Meta Language.
Earlier quoted context omitted.
What is this alleged friction? Because plenty of people have been shipping great projects in Ocaml since it was released so it doesn’t seem to be much of an issue to many. I doubt Ocaml will be surpassed soon. They just added an effect system to the multicore rewrite so all things being considered, they seem to be pulling even more ahead.
Alleged? Come now. Beginners face the following problems: there's multiple standard libraries, many documents are barely more than type signatures, and data structures aren't printable by default. Experts also face the problem of a very tiny library ecosystem, and tooling that's often a decade behind more mainstream languages (proper gdb support when?). OCaml added multicore support recently, but now there is the who…
> there's multiple standard libraries
Scala has a far more fragmented ecosystem with Cats, Scalaz, Zio and Akka. C++ and Java have a bunch of stdlib extensions like boost, Guava, Apache Commons etc.
> many documents are barely more than type signatures
Can be said of most of Java, Kotlin, Scala, Erlang etc etc. Just compiled javadocs, sometimes with a couple of unhelpful lines.
> data structures aren't printable by default
Neither they are in C++
I think the real reason it's not popular is that there are languages which solve more or less the same problems of system programming but look far more familiar to an avg. programmer who was raised on C++ and Java.
OCaml did become popular, but via Rust, which took the best parts of OCaml and made the language more imperative feeling. That's what OCaml was missing!
To this day, whenever I see Machine Learning abbreviated, my heart skips a beat, then I become crestfallen as I realize I'm not about to read something about Meta Language.
ML refers to Meta Language and LLM refers to Languages and Logic Montreal [0], a PL theory group. [0] https://llm.uqam.ca
I know there are great many Polish people in the world, but why it matters so much in this case? They could have been any nationality, even French!
To this day, whenever I see Machine Learning abbreviated, my heart skips a beat, then I become crestfallen as I realize I'm not about to read something about Meta Language.
If people start using the term AI, we better be living in I, Robot. Not whatever the hell this is.
Tangential rant. Sorry.
Yes, in every ML/OCaml tutorial, sooner or later the words object, class, and type inference appear and that’s when a once–minimalist language turns into an academic Frankenstein.
Earlier quoted context omitted.
Almost there, but in the meantime supporting a casual squillion dollars of trades at JS
Yes and they had to basically build their own version of the compiler to keep everything from falling over ( https://oxcaml.org/ ).
The latter going much further than most mainstream languages.
I've dabbled in F# (and aside from the rough setup with little coherent information at the time) had a pretty good time. Actor-based concurrency was easy to grok. The one gotcha was whenever those mutable Arrays entered the picture. I'd like to hear some practical reasons for preferring OCaml over F#. [Hoping I don't get a lot about MS & .NET which are valid concerns but not what I'm curious about.] I want to know mo…
> I'd like to hear some practical reasons for preferring OCaml over F# Bigger native ecosystem. C#/.net integration is a double edged sword: a lot of libraries, but the libraries are not written in canonical F#. A lot of language features F# misses, like effect handlers, modules, GADTs etc.
As for missing language features, they can also be a double-edged sword. I slid down that slippery slope in an earlier venture with Scala. (IIRC mostly implicits and compile times).
As a Rust newbie and seasoned Go dev, I'm pretty interested to knownwhere would people experienced in both OCaml and Haskell, would put it in the spectrum.