I believe that an ML should be the First Language for Computer Scientists. It's much less clear which language we should teach people for whom it will likely be their Only Language, today Python is common, and for fields which care about stats often R is used, I've also seen Java used in this role. But for a First Language specifically I am in no doubt that an ML should be chosen, and this is despite the fact that the University where I work has taught Java for decades and Python most recently as First Language.
I'm an old man, I learned the Standard ML of New Jersey when I was an undergraduate many years ago, but I'm pretty sure that experience though it isn't irrelevant, did not overly colour my belief in what we [speaking broadly of humanity] ought to teach.
An ML is great for the theory or abstraction side of programming, but C is also hands down the best language to get a sense of how the computer is running your program.
It’s still an abstraction, but at least being aware of memory management, copying vs referencing, etc are hugely important concepts that ML languages can hide.
> but C is also hands down the best language to get a sense of how the computer is running your program.
C is in an odd position right now to argue it is how the machine is really working. Computers are more complicated since bigger caches entered the picture. Hell I do not think even ASM is a good approximation on how machine really work given the data dependencies will make stuff being processed in parallel instead of sequentially.
What you could argue is that C is the archetype for an imperative language procedural language with a clean mapping to ASM. That is different than how the machine works. Simpler architecture have less distance between their ASM and what is really hapenning.
> an imperative language procedural language with a clean mapping to ASM
C really isn't as great for this as is often suggested either, not for decades at least
K&R's original compiler on an actual Digital machine from that era makes the case best, but remember this is the era when if you hot loop over modifying a variable your compiler is going to emit memory stores for each iteration - because that's what you wrote, isn't it? No modern C compiler would do this because it's awfully slow.
Likewise that iteration of C doesn't have what you'd recognise as function prototypes, it doesn't care whether your function takes six arguments, here are six arguments the first two are integers, good luck with that. In assembler that makes sense, but you don't do that in modern C either.
C is still a close-to-the-metal language, but it is programming an abstract machine and it is important that the programmer knows that's not really how the machine works, if you want to learn about the machine you will need to write at least assembler and possibly just go learn electronics. Good luck.
C is still heavily abstracted. Modern OS evolved in conjunction with C s.t. it behaves like a C runtime simulating a PDP11 (I remember reading a nice article on that). To learn system, what you need is an OS course, not C. I'd say the current C-based stack is in a quite embarrassing state.
I think this PDP-11 meme is quite misleading. There is nothing really in the C programming model specific to the PDP-11 and C was used on systems much weirder than a PDP-11.
C is also very successfully the basis of many parallel programs running on multi-processor systems with a memory model in the standard that was created much later than the PDP-11.
Also somehow the implied argument that computing hardware and operating systems simulate a PDP-11 for the sake of C is completely backwards. Historically, there were other approaches, e.g. processors designed for object-oriented programming or actors etc.. All those were not very successful.
For someone just starting to learn CS, it should not matter whether they're on PDP-11 or x64 or ARM. You can't start teaching with pipelining and speculative branch execution.
So C is good choice because there is a simple CPU architecture that it maps to well.
The entire series of interviews with various language designers by Ryan Peterman is really great and a highly recommended watch.
It gives an insight into how they thought/think and what we can learn from them.
While watching the series i was stuck by the fact that they often only focused/reiterated the conceptual basics and building on top of them in a step-by-step manner. Whereas if you watch interviews with programmers (even famous ones) you will often see a lot of fancy talk about the complicated features of the language etc.
I believe "Experts" have a way of modeling domain knowledge in their mind in such a way that they intuitively know what is the "wheat" and what is the "chaff". This is what we need to learn. Scheme can do a lot with a minimal language and so can C++ on the other end of the spectrum. So then what constitutes "Programming"? It is simply an expression of Intent via syntax supporting abstraction of state/behaviour.
I do really wonder what it would be like to learn to program for the first time with OCaml.
I remember learning to use OCaml in a properly functional way after so long writing code in C and it was really miserably painful trying to change how I thought about algorithms. I eventually got over the hill and it changed how I write code in C (for the better?), but I do wonder if it would have been easier to have learned OCaml as a first language instead.
I did so! (quirks of the path I took in the French educational system)
I went through a book similar to the one above, with no internet connection. The first few weeks were rough: I did not quite know what a type was and the compiler error messages were unforgiving and hard to understand without that context.
But, once I grokked the core ideas (a proper idea of what could be done with recursion took much longer), things went surprisingly smooth. I definitely credit it with making me a better programmer.
I started programming at 18 right after highschool (which, I guess, is late by HN standards: a number of my peers had played with Python first and hated Ocaml).
When I first learned to program at university we were taught Haskell. That was 15 years ago and I've not really programmed anything in Haskell since, instead I've racked up years coding professionally in pretty much all the major imperative languages.
I'm aware of why Haskell is not practical as a production language for most companies, but I have to say I've never really coded in anything else that feels as "neat" and it's a shame. Every other language feels like it has some idiosyncratic scaffolding one has to learn, reminding you that you're constrained by how computer hardware works, rather than just expressing an algorithm in terms of inputs and outputs.
I would say it has made me a better coder, I've still kept a preference for keeping data immutable, copyable and abstracting complexity into easily testable functions over classes with unobservable mutable state.
It's a good language to learn programming. Very simple semantics. But ultimately, you need to learn different paradigms, I think the order doesn't matter, they'll still be an element of surprise.
Also OCaml lets you write imperative code if you wish so. So you can learn the different paradigms within the same language.
Caml was how I was taught computer science in prépa and first few years of engineering school, a mere 25 years ago.
(Ok, I had done bits of BASIC before, but I had time to recover.)
To be honest, the learning path was
1. Lots of maths. Then add some more.
2. Algos in pseudo code. (In "French", pseudo code, of course, because, why not ?)
3. Caml as "executable pseudo code". With all the warnings and a hints of disgust as the use of mutation and side effect. (And of course ":=" his completely different from "=", what are we, beasts ?)
4. Lots of exams where you have to write properly indented programs on paper on the first try to submit all sorts of recursive trees to all sorts of horrendous manipulations - and you can imagine the grader doing the mother of all code reviews
5. Re do that again in engineering school, because a third of the class had done zero computer science, and the other third had learn in Pascal
6. Then learn C and assembler, and get your mind blown in the exact opposite direction
7. See your teachers reluctantly say that "you should just learn java", because "that's what used in the industry", and "no one will ever get a job writing caml anyway"
...
25 years later : yup, some people managed to get jobs writing a dialect of caml for this small startup in a garage serving cat pictures and racist memes to billions of people
26 years later: "you should just learn to prompt LLMs anyway", because "that's what the industry needs, and no one will get a job programming any more"
This book, while excellent otherwise, is much too harder for beginners, IMO. The pace is too brisk, and it's far from pedagogically useful if you don't already know how to program.
Yeah, I don’t think it assumes zero knowledge, which is what I’d expect from a “first programming language” book.
But it does say it’s targeted more for an “algorithms” course in the introduction.
As a side note, I think a REPL is the best environment for learning to program for absolute beginners. You get instant feedback and can focus entirely on just short snippets of real code, without having to worry about compilers, build systems, and “the OS” as a whole. Especially if it comes with a GUI wrapper, you can skip the terminal entirely.
You can also learn for your own amusement, and solely for the fun of comprehension; a lot of mathematician were driven by this. It's a shame current social value places so much utilitariaism on learning.
I like baking. There are machines that can bake bread at an industrial scale that I cannot compete with. There are home kneaders that do much of the work very well. I use one of those more often than not.
I still think it worth my time kneading dough by hand. It teaches me the various properties of flour, how external factors like humidity or temperature impact the overall process, and I believe that it makes me a better baker, even when I use a machine, because I am better at controlling what the machine does. When I get a new brand of flour I will make sure to bake everything by hand first to "get a feel".
Kneading by hand is also very relaxing to me. This is probably the main reason I bake in the first place.
Programming, and other activities are not very different. We now have machines that can do it faster, at a fraction of the quality many people deem good enough. If you hate coding, that is probably all you need to use, and learning a new language might just be a frustrating experience not worth subjecting yourself to. But if you enjoy coding then it should make you better at it, even when you use the machines.
As always, it is good to be aware that many people are too anxious about more existential issues to comfortably an consistently expend effort on intellectually-taxing tasks that aren't perceived as directly related to their survival. If it's an issue with social values, it's less of one related to learning as it is to perpetuating artificial scarcity.
>to comfortably an consistently expend effort on intellectually-taxing tasks that aren't perceived as directly related to their survival.
the average person spends 6(!) hours a day on their smartphone, the average TikTok user spends 100 minutes on the app alone. This isn't about artificial scarcity, it's about the average person looking like the Wall-E people
Escapism and making a concentrated effort on something are two different things. Yes it would probably be good if you could flip a switch and use the small windows of time we look at our phone per day to study OCaml, but it's not really realistic..
People who are asking these questions are saying "will me spending my time learning OCaml help me land that job that pays six figures and has health insurance so I can not rot away living on the margin". They aren't saying "I only do things that will make me money".
>use the small windows of time we look at our phone
again, it's not a small window. It's six hours. That's almost half your waking day. People spend virtually their entire leisure time rotting away on low quality entertainment.
>will me spending my time learning OCaml help me land that job
that's a pointless question for one you never know if something will land you a job, new opportunities don't open up before you do something, secondly the relevant question is, should I stop doing X and start learning Ocaml, or Chinese, or take a welding class because all of that even if it doesn't work out beats scrolling through Instagram.
I don't even take offense with the idea that you engage in activity that makes you money, because pure selfishness on that front would be an improvement to what most people are doing now.
“Low quality entertainment” is a very elitist thing to say. Most don’t have time or luxury of even being introduced ( via an east coast liberal arts college ) to read Tolstoy or appreciate the finer motions of Tchaikovsky. Instead the Druski memes will do just fine, mixed in with the AI slop. Or maybe they’re physically or physiologically incapable of enjoying the outdoors or sport. Point is, my gen played strategy games and first person shooters and listened to Eminem, this one marls TikToks until their thumbs have RSI.
As for OCAML vs not, I think the vast majority of even intellectual and studious people would be better served trying to AI max and build some kind of agent serving businesses than trying to get a job at, uhh, Jane Street. 1% of the best engineers in the world get to work in that language, so yeah the parent makes a valid point
Even if those statistics are correct, I do think you're ignoring that smartphone apps are specifically engineered to be low-friction and highly-addictive, and pushed specifically to the people who are anxious about spending money on other pursuits (free time often being necessary but insufficient), as they contend with the artificial scarcity (which this is absolutely about) of affordable housing, affordable food, affordable transportation, affordable guided education, etc.
My experience with OCaml has transformed how I think about programming and complex system design. This may also be true if you learn any other functional programming language, but OCaml is easy and flexible which makes it good imo as a door towards the more formal part of comp sci. Even for steering an LLM I think this might help.
My experience with lisp was exactly that: it completely changed how I think about programming, but much more, how I think about systems and engineering. (I learned it through SICP)
Michael Clarkson teaches OCaml at Cornell. I highly recommend his free course materials [1]. He’s an excellent educator. Learning functional programming paradigms had a major influence on how I design programs. Clarkson also taught snippets from the Pragmatic Programmer, which was equally influential (as it has been for many many others) [2].
You could have asked this question 10 years ago, long before llms. It's not like you'd realistically would get an ocaml job back then when there's so few of them, so why bother?
The answer is still the same as well, people learn ocaml either because they enjoy it, or because learning a functional language makes them a better programmer overall and teaches your brain to approach a problem in a different way.
Cultural inertia: until recently, you couldn't just press play and get even a wide selection of music: for most of history, if you wanted music, you had to make it or hire someone to do it for you.
More recently, you had to go to the store and buy it, which meant you didn't have much variety.
Today, learning an instrument is for social status, inheriting the shine of the past, where music was rare and costly. The reason to learn an instrument today is because the former situation was romanticized.
It'll probably take a generation before people ease into guilt-free enjoying infinite, fully generated music.
Sure, I guess. But today, something like 30% of people play music or sing regularly enough to say they do it (ie, not very much at all). Even a couple of generations ago, it was much higher. It's not going to die out, but I think a lot of people are asking themselves if they want to bother.
> So (asking genuinely), should we learn these things?
I wanted to learn a functional programming language with powerful type capabilities and I chose the Lean Language for that and not OCamel or Haskell. Reason being: Better type system (dependent types!), applicable in formal domains and can use it to learn math too.
For your bread and butter programming, there is already JS/Go anyways.
Seeing that you already know programming, I'd say it'd be less risky for you. But the only reason you're able to pilot an LLM to do programming for you, is because you understand programming and architecture.
But what about the future generations skipping the step of learning the OCaml's, the C's, the Python's...? It's quite concerning.
you are eventually going to have a very bad time if you do not have a solid mental model of the code the LLM is writing, and indeed if you cannot steer the LLM so that its code conforms to your mental models. learning ocaml is a great way to add some valuable tools to your toolkit when it comes to thinking about code and how it fits together.
This mindset (i.e. LLMs are available so why do i need to learn anything?) is highly insidious and will destroy your brain/mind/future if you let it.
Humans are the ones who Understand, while LLMs only Know.
So inter-disciplinary/cross-disciplinary insights, new modes of thinking/reasoning, flashes of insight etc. are still in the purview of Humans only. AI/LLMs can help focus and short-circuit the study of various subjects but their understanding can only happen within a human "Mind". If you do not even have basic domain knowledge (i.e. unknown unknowns) how can you even prompt/query an LLM for answers?
A few illustrative examples; a) Newton came up with limits/calculus out of a need to measure continuous motion with varying speeds b) Kekule came up with the benzene ring from a dream where he saw a snake grab its own tail c) Descartes came up with the cartesian coordinates in an attempt to solve geometry via algebra etc. Each of these was a novel leap of insight bringing together various concepts to create entirely new knowledge domains.
So one should learn/study the core concepts/ideas in various domains and then push the tedious mechanical labour onto the machines. In this regard see also the concept of "Active Learning" - https://en.wikipedia.org/wiki/Active_learning
I think it's helpful to have a deep understanding of one c-type language, one lisp, and one ML-type language. There are so many things influenced by these three language families that being comfortable with them makes it so much easier to understand a wide variety of languages and libraries.
I would not make that dependent on LLMs. If OCaml covers a use case you have, why not.
Personally I try to stick within my own niche though - ruby, java and also python (ruby is unfortunately losing grounds really hard now, the writing was on the well in the last some years though, and people such as DHH are now indeed a liability rather than an asset to be had, but that's a side topic).
I think what LLMs will force in the long run is to make programming languages used by real humans in a traditional way, more effective. That is, writing code by humans will have to become a lot more efficient, both time-wise and speed-wise. And for that there is always a use case IMO since LLMs are, despite the promo, incredibly stupid.
1. Compile times. OCaml compiles very quickly (think Go) and this gives you a fast feedback loop. It lets the LLM rip through the implementation.
2. OCaml has an idiomatic approach of using interface files for all modules that can be accessed outside their libraries, and interface files give LLMs a great précis of exactly what is wanted. They then just have to follow the types and fill in the blanks to get the implementation. It's nearly the perfect use case.
Both force the model to reason about types too much. The more constrained type system plus global inference merely holds them to what they already wrote, with very fast feedback.
Rust is fine if you need it but most things don’t and ocaml has more convenient abstractions for “regular” work. If you need rust you need rust but ocaml isn’t that far off in perf.
Haskell type system is too expressive, it itself becomes a place for the agent to make mistakes and get bogged down.
For web frontend, it's derivative programming language, rescript, is also a secret weapon because of types, fast compilation times and first class support of React. Using React in rescript is much nicer than TypeScript.
Yes I contributed code to a paper on it this spring. It’s hard to measure and “studying” it just means feeding money into frontier models. If anyone has a few billion tokens for a couple masters students hmu so they can get it published.
I'm interested too - besides the paper, is it your personal experience that working with llms on ocaml is superior to other languages? I thought with the sheer amount of training data languages like python and java would be "ideal"
I believe that an ML should be the First Language for Computer Scientists. It's much less clear which language we should teach people for whom it will likely be their Only Language, today Python is common, and for fields which care about stats often R is used, I've also seen Java used in this role. But for a First Language specifically I am in no doubt that an ML should be chosen, and this is despite the fact that the University where I work has taught Java for decades and Python most recently as First Language.
I'm an old man, I learned the Standard ML of New Jersey when I was an undergraduate many years ago, but I'm pretty sure that experience though it isn't irrelevant, did not overly colour my belief in what we [speaking broadly of humanity] ought to teach.
An ML is great for the theory or abstraction side of programming, but C is also hands down the best language to get a sense of how the computer is running your program.
It’s still an abstraction, but at least being aware of memory management, copying vs referencing, etc are hugely important concepts that ML languages can hide.
> but C is also hands down the best language to get a sense of how the computer is running your program.
C is in an odd position right now to argue it is how the machine is really working. Computers are more complicated since bigger caches entered the picture. Hell I do not think even ASM is a good approximation on how machine really work given the data dependencies will make stuff being processed in parallel instead of sequentially.
What you could argue is that C is the archetype for an imperative language procedural language with a clean mapping to ASM. That is different than how the machine works. Simpler architecture have less distance between their ASM and what is really hapenning.
> an imperative language procedural language with a clean mapping to ASM
C really isn't as great for this as is often suggested either, not for decades at least
K&R's original compiler on an actual Digital machine from that era makes the case best, but remember this is the era when if you hot loop over modifying a variable your compiler is going to emit memory stores for each iteration - because that's what you wrote, isn't it? No modern C compiler would do this because it's awfully slow.
Likewise that iteration of C doesn't have what you'd recognise as function prototypes, it doesn't care whether your function takes six arguments, here are six arguments the first two are integers, good luck with that. In assembler that makes sense, but you don't do that in modern C either.
C is still a close-to-the-metal language, but it is programming an abstract machine and it is important that the programmer knows that's not really how the machine works, if you want to learn about the machine you will need to write at least assembler and possibly just go learn electronics. Good luck.
> It’s still an abstraction
C is still heavily abstracted. Modern OS evolved in conjunction with C s.t. it behaves like a C runtime simulating a PDP11 (I remember reading a nice article on that). To learn system, what you need is an OS course, not C. I'd say the current C-based stack is in a quite embarrassing state.
I think this PDP-11 meme is quite misleading. There is nothing really in the C programming model specific to the PDP-11 and C was used on systems much weirder than a PDP-11. C is also very successfully the basis of many parallel programs running on multi-processor systems with a memory model in the standard that was created much later than the PDP-11.
Also somehow the implied argument that computing hardware and operating systems simulate a PDP-11 for the sake of C is completely backwards. Historically, there were other approaches, e.g. processors designed for object-oriented programming or actors etc.. All those were not very successful.
It's clear that the authors were either inspired by the PDP-11 ISA and/or designed the language to make porting UNIX from PDP-11 Assm to it easier.
UNIX for PDP-7 in Assm -> UNIX for PDP-11 in Assm -> UNIX for PDP-11 in C
https://news.ycombinator.com/item?id=42644851
and
https://news.ycombinator.com/item?id=43245166
For someone just starting to learn CS, it should not matter whether they're on PDP-11 or x64 or ARM. You can't start teaching with pipelining and speculative branch execution. So C is good choice because there is a simple CPU architecture that it maps to well.
Probably thinking of this article: "C Is Not a Low-level Language: Your computer is not a fast PDP-11."
https://queue.acm.org/doi/10.1145/3212477.3212479
Sure, you need an OS course, but that's when students should learn C as well.
This is the best OCaml resource I know, and I have gone through it in full, and highly recommend:
CS3110: OCaml Programming: Correct + Efficient + Beautiful [0]
It is one of the best programming resources that I know of.
[0]: https://cs3110.github.io/textbook/cover.html
Tangentially, a great interview with the creator of OCaml, Xavier Leroy [1].
[1] https://www.youtube.com/watch?v=9Cswiqrq6So
The entire series of interviews with various language designers by Ryan Peterman is really great and a highly recommended watch.
It gives an insight into how they thought/think and what we can learn from them.
While watching the series i was stuck by the fact that they often only focused/reiterated the conceptual basics and building on top of them in a step-by-step manner. Whereas if you watch interviews with programmers (even famous ones) you will often see a lot of fancy talk about the complicated features of the language etc.
I believe "Experts" have a way of modeling domain knowledge in their mind in such a way that they intuitively know what is the "wheat" and what is the "chaff". This is what we need to learn. Scheme can do a lot with a minimal language and so can C++ on the other end of the spectrum. So then what constitutes "Programming"? It is simply an expression of Intent via syntax supporting abstraction of state/behaviour.
I do really wonder what it would be like to learn to program for the first time with OCaml.
I remember learning to use OCaml in a properly functional way after so long writing code in C and it was really miserably painful trying to change how I thought about algorithms. I eventually got over the hill and it changed how I write code in C (for the better?), but I do wonder if it would have been easier to have learned OCaml as a first language instead.
I did so! (quirks of the path I took in the French educational system)
I went through a book similar to the one above, with no internet connection. The first few weeks were rough: I did not quite know what a type was and the compiler error messages were unforgiving and hard to understand without that context. But, once I grokked the core ideas (a proper idea of what could be done with recursion took much longer), things went surprisingly smooth. I definitely credit it with making me a better programmer.
How old were you?
I started programming at 18 right after highschool (which, I guess, is late by HN standards: a number of my peers had played with Python first and hated Ocaml).
When I first learned to program at university we were taught Haskell. That was 15 years ago and I've not really programmed anything in Haskell since, instead I've racked up years coding professionally in pretty much all the major imperative languages.
I'm aware of why Haskell is not practical as a production language for most companies, but I have to say I've never really coded in anything else that feels as "neat" and it's a shame. Every other language feels like it has some idiosyncratic scaffolding one has to learn, reminding you that you're constrained by how computer hardware works, rather than just expressing an algorithm in terms of inputs and outputs.
I would say it has made me a better coder, I've still kept a preference for keeping data immutable, copyable and abstracting complexity into easily testable functions over classes with unobservable mutable state.
It's a good language to learn programming. Very simple semantics. But ultimately, you need to learn different paradigms, I think the order doesn't matter, they'll still be an element of surprise.
Also OCaml lets you write imperative code if you wish so. So you can learn the different paradigms within the same language.
Ooooh, the memories...
Caml was how I was taught computer science in prépa and first few years of engineering school, a mere 25 years ago.
(Ok, I had done bits of BASIC before, but I had time to recover.)
To be honest, the learning path was
1. Lots of maths. Then add some more.
2. Algos in pseudo code. (In "French", pseudo code, of course, because, why not ?)
3. Caml as "executable pseudo code". With all the warnings and a hints of disgust as the use of mutation and side effect. (And of course ":=" his completely different from "=", what are we, beasts ?)
4. Lots of exams where you have to write properly indented programs on paper on the first try to submit all sorts of recursive trees to all sorts of horrendous manipulations - and you can imagine the grader doing the mother of all code reviews
5. Re do that again in engineering school, because a third of the class had done zero computer science, and the other third had learn in Pascal
6. Then learn C and assembler, and get your mind blown in the exact opposite direction
7. See your teachers reluctantly say that "you should just learn java", because "that's what used in the industry", and "no one will ever get a job writing caml anyway"
...
25 years later : yup, some people managed to get jobs writing a dialect of caml for this small startup in a garage serving cat pictures and racist memes to billions of people
26 years later: "you should just learn to prompt LLMs anyway", because "that's what the industry needs, and no one will get a job programming any more"
Drawing cardioids in maple V while I had darkbasic pro at home and could write my own games and delve into quaternions since 3eme. :x
No wonder I failed this sht, kind of.
Yup, I did not mention the classmates who were already fluent in c++ at 15 and were not that kind of pretending "loops" were mathematical wonder :D
Being a functional programmer in a group of imperative programmers is miserable
OCaml programmers, what learning resource would you recommend starting out with? I know there's https://cs3110.github.io/textbook/chapters/basics/intro.html. How does this book compare? Anything else you would recommend?
This book, while excellent otherwise, is much too harder for beginners, IMO. The pace is too brisk, and it's far from pedagogically useful if you don't already know how to program.
Yeah, I don’t think it assumes zero knowledge, which is what I’d expect from a “first programming language” book.
But it does say it’s targeted more for an “algorithms” course in the introduction.
As a side note, I think a REPL is the best environment for learning to program for absolute beginners. You get instant feedback and can focus entirely on just short snippets of real code, without having to worry about compilers, build systems, and “the OS” as a whole. Especially if it comes with a GUI wrapper, you can skip the terminal entirely.
Indeed--so the title is somewhat misleading.
Agree with you wrt to REPL, though sooner or later the programmer-wanna-be has to embrace technical sophistication. :)
The French original version of the book appears to be 12 years old (2014). Is the English translation linked here a somehow more up to date book?
What is the recommended GUI framework for OCaml? (Please don't say HTML)
https://github.com/sanette/bogue
What language and framework do you use for GUI programming?
Camlkit-gui for macOS
Anything for Linux? Or cross-platform?
I looked for Qt bindings but they appeared to be abandoned last time I checked.
GTK4 bindings https://github.com/chris-armstrong/ocgtk
I see that unison (file sync tool) seems to use: https://garrigue.github.io/lablgtk/
For Linux UI.
But that uses Gtk 3. Gtk 4 is already more than 5 years old ...
> Learn Programming with OCaml
Lately, I keep asking myself, do I need to learn this new thing, should I force myself to learn this thing, LLMs know it anyways and so on.
So (asking genuinely), should we learn these things?
You can also learn for your own amusement, and solely for the fun of comprehension; a lot of mathematician were driven by this. It's a shame current social value places so much utilitariaism on learning.
I like baking. There are machines that can bake bread at an industrial scale that I cannot compete with. There are home kneaders that do much of the work very well. I use one of those more often than not.
I still think it worth my time kneading dough by hand. It teaches me the various properties of flour, how external factors like humidity or temperature impact the overall process, and I believe that it makes me a better baker, even when I use a machine, because I am better at controlling what the machine does. When I get a new brand of flour I will make sure to bake everything by hand first to "get a feel".
Kneading by hand is also very relaxing to me. This is probably the main reason I bake in the first place.
Programming, and other activities are not very different. We now have machines that can do it faster, at a fraction of the quality many people deem good enough. If you hate coding, that is probably all you need to use, and learning a new language might just be a frustrating experience not worth subjecting yourself to. But if you enjoy coding then it should make you better at it, even when you use the machines.
This. The question can be seen like “should I learn to solve sodoku, if a computer can do it better?”
As always, it is good to be aware that many people are too anxious about more existential issues to comfortably an consistently expend effort on intellectually-taxing tasks that aren't perceived as directly related to their survival. If it's an issue with social values, it's less of one related to learning as it is to perpetuating artificial scarcity.
>to comfortably an consistently expend effort on intellectually-taxing tasks that aren't perceived as directly related to their survival.
the average person spends 6(!) hours a day on their smartphone, the average TikTok user spends 100 minutes on the app alone. This isn't about artificial scarcity, it's about the average person looking like the Wall-E people
Escapism and making a concentrated effort on something are two different things. Yes it would probably be good if you could flip a switch and use the small windows of time we look at our phone per day to study OCaml, but it's not really realistic..
People who are asking these questions are saying "will me spending my time learning OCaml help me land that job that pays six figures and has health insurance so I can not rot away living on the margin". They aren't saying "I only do things that will make me money".
>use the small windows of time we look at our phone
again, it's not a small window. It's six hours. That's almost half your waking day. People spend virtually their entire leisure time rotting away on low quality entertainment.
>will me spending my time learning OCaml help me land that job
that's a pointless question for one you never know if something will land you a job, new opportunities don't open up before you do something, secondly the relevant question is, should I stop doing X and start learning Ocaml, or Chinese, or take a welding class because all of that even if it doesn't work out beats scrolling through Instagram.
I don't even take offense with the idea that you engage in activity that makes you money, because pure selfishness on that front would be an improvement to what most people are doing now.
“Low quality entertainment” is a very elitist thing to say. Most don’t have time or luxury of even being introduced ( via an east coast liberal arts college ) to read Tolstoy or appreciate the finer motions of Tchaikovsky. Instead the Druski memes will do just fine, mixed in with the AI slop. Or maybe they’re physically or physiologically incapable of enjoying the outdoors or sport. Point is, my gen played strategy games and first person shooters and listened to Eminem, this one marls TikToks until their thumbs have RSI.
As for OCAML vs not, I think the vast majority of even intellectual and studious people would be better served trying to AI max and build some kind of agent serving businesses than trying to get a job at, uhh, Jane Street. 1% of the best engineers in the world get to work in that language, so yeah the parent makes a valid point
Even if those statistics are correct, I do think you're ignoring that smartphone apps are specifically engineered to be low-friction and highly-addictive, and pushed specifically to the people who are anxious about spending money on other pursuits (free time often being necessary but insufficient), as they contend with the artificial scarcity (which this is absolutely about) of affordable housing, affordable food, affordable transportation, affordable guided education, etc.
This ^
My experience with OCaml has transformed how I think about programming and complex system design. This may also be true if you learn any other functional programming language, but OCaml is easy and flexible which makes it good imo as a door towards the more formal part of comp sci. Even for steering an LLM I think this might help.
My experience with lisp was exactly that: it completely changed how I think about programming, but much more, how I think about systems and engineering. (I learned it through SICP)
Michael Clarkson teaches OCaml at Cornell. I highly recommend his free course materials [1]. He’s an excellent educator. Learning functional programming paradigms had a major influence on how I design programs. Clarkson also taught snippets from the Pragmatic Programmer, which was equally influential (as it has been for many many others) [2].
[1] https://www.cs.cornell.edu/courses/cs3110/2025sp/
[2] https://pragprog.com/titles/tpp20/the-pragmatic-programmer-2...
You could have asked this question 10 years ago, long before llms. It's not like you'd realistically would get an ocaml job back then when there's so few of them, so why bother?
The answer is still the same as well, people learn ocaml either because they enjoy it, or because learning a functional language makes them a better programmer overall and teaches your brain to approach a problem in a different way.
Should I continue to walk, when technology can move me from place to place?
https://tenor.com/view/tf2-wall-e-team-fortress-2-autobalanc...
Outsourcing all the thinking to machines may have consequences you might not like.
An oblique explanation: https://croissanthology.com/earring
Posting 'why should we learn' a programming language on Hacker News is top-quality ragebait :-D
Should you learn history if it is already written in a book? Should you live if others are already living?
For most people, history is trivia.
If you ignore history everything is perfect, or at least a controlled slight deviation.
Why learn an instrument when you can just press play?
Why does anyone have any hobbies?
Cultural inertia: until recently, you couldn't just press play and get even a wide selection of music: for most of history, if you wanted music, you had to make it or hire someone to do it for you.
More recently, you had to go to the store and buy it, which meant you didn't have much variety.
Today, learning an instrument is for social status, inheriting the shine of the past, where music was rare and costly. The reason to learn an instrument today is because the former situation was romanticized.
It'll probably take a generation before people ease into guilt-free enjoying infinite, fully generated music.
These theories sound vaguely plausible.
I would rate them as about 5% true and 95% false, as explanation of the past and prediction of the future.
The satisfaction of learning to do something difficult isn't going away, and the social status associated with it won't either.
Sure, I guess. But today, something like 30% of people play music or sing regularly enough to say they do it (ie, not very much at all). Even a couple of generations ago, it was much higher. It's not going to die out, but I think a lot of people are asking themselves if they want to bother.
your body needs exercise or you end up an obese couch potato. Your mind is similar: it needs exercise or you end up a dunce.
> The reason to learn an instrument today is because the former situation was romanticized.
Lol. The reason to learn an instrument is because it is directly pleasurable to play an instrument. You've got consumer/spectator brain.
I mean, why post a comment when you could have just read a comment?
> So (asking genuinely), should we learn these things?
I wanted to learn a functional programming language with powerful type capabilities and I chose the Lean Language for that and not OCamel or Haskell. Reason being: Better type system (dependent types!), applicable in formal domains and can use it to learn math too.
For your bread and butter programming, there is already JS/Go anyways.
So don't see much point in learning OCamel.
Seeing that you already know programming, I'd say it'd be less risky for you. But the only reason you're able to pilot an LLM to do programming for you, is because you understand programming and architecture.
But what about the future generations skipping the step of learning the OCaml's, the C's, the Python's...? It's quite concerning.
Oh by the way, yes. Learn OCaml!
Keep using your brain or you will forget stuff. Doing puzzles is great, programming in new languages is also great.
you are eventually going to have a very bad time if you do not have a solid mental model of the code the LLM is writing, and indeed if you cannot steer the LLM so that its code conforms to your mental models. learning ocaml is a great way to add some valuable tools to your toolkit when it comes to thinking about code and how it fits together.
LLM + static types is a winning combo. And if you want to be serious with what you do with your LLM, you need to understand the output to some extent.
That being said, you may as well use Rust. The extra complexity of manual memory management and Rust idiosyncracies are easily dealt with by the LLM.
LLMs are better at OCaml than any other language, and being able to read and think in OCaml is very helpful to understanding LLM generated OCaml code.
Also, it may very well be the decade of formal verification - if so, OCaml is a good place to be.
This mindset (i.e. LLMs are available so why do i need to learn anything?) is highly insidious and will destroy your brain/mind/future if you let it.
Humans are the ones who Understand, while LLMs only Know.
So inter-disciplinary/cross-disciplinary insights, new modes of thinking/reasoning, flashes of insight etc. are still in the purview of Humans only. AI/LLMs can help focus and short-circuit the study of various subjects but their understanding can only happen within a human "Mind". If you do not even have basic domain knowledge (i.e. unknown unknowns) how can you even prompt/query an LLM for answers?
A few illustrative examples; a) Newton came up with limits/calculus out of a need to measure continuous motion with varying speeds b) Kekule came up with the benzene ring from a dream where he saw a snake grab its own tail c) Descartes came up with the cartesian coordinates in an attempt to solve geometry via algebra etc. Each of these was a novel leap of insight bringing together various concepts to create entirely new knowledge domains.
So one should learn/study the core concepts/ideas in various domains and then push the tedious mechanical labour onto the machines. In this regard see also the concept of "Active Learning" - https://en.wikipedia.org/wiki/Active_learning
I would sharpen my software engineering skills rather than coding / programming skills.
Yes. LLMs do not know anything, and they will make mistakes as a result. You have to be able to check their work if you wish to do a good job.
This isn’t really true for many programming tasks anymore. And as the saying goes, “this is the worse they will ever be”.
> “this is the worse they will ever be”
This is assuming that the current state of LLMs is sustainable, which it definitely isn’t.
I think it's helpful to have a deep understanding of one c-type language, one lisp, and one ML-type language. There are so many things influenced by these three language families that being comfortable with them makes it so much easier to understand a wide variety of languages and libraries.
LLMs know it anyways?
Hhhmmmmm
I mean if you want to let llms do everything for you go ahead. Wall-e implications aside, it seems like a great self centric life.
I would not make that dependent on LLMs. If OCaml covers a use case you have, why not.
Personally I try to stick within my own niche though - ruby, java and also python (ruby is unfortunately losing grounds really hard now, the writing was on the well in the last some years though, and people such as DHH are now indeed a liability rather than an asset to be had, but that's a side topic).
I think what LLMs will force in the long run is to make programming languages used by real humans in a traditional way, more effective. That is, writing code by humans will have to become a lot more efficient, both time-wise and speed-wise. And for that there is always a use case IMO since LLMs are, despite the promo, incredibly stupid.
What the hell else do you have to do?!
Why is the PDF smaller than the Epub file?
The ePub contains both SVGs and PNGs, the latter of which doesn't compress all that well for "plain zip", which an ePub is.
The PDF on the other hand gets to use zlib for streaming all the objects. It gets half decent compression.
Probably vector-drawn diagrams are rendered into bitmap images for the EPUB version.
Don't learn programming with OCaml, it's horrible.
I know a few programs written in OCaml such as weidu.
OCaml is a very strange programming language. I don't think it will be able to sustain e. g. success stories of other languages, such as python.
Ocaml is ancient at this point. It's never going to be python, but I doubt it's going to disappear.
OCaml is the LLM secret weapon right now. They are better at writing it than they are any other language.* That’s all I have to say about it.
* Other “pure” hindley-milner languages are tied but among them ocaml has some particular strengths that I’m sure others will discuss.
Two genuine questions. (1) Why not Rust? (2) Why not Haskell?
(I have my own answers, but I'd love to hear yours, too.)
1. Compile times. OCaml compiles very quickly (think Go) and this gives you a fast feedback loop. It lets the LLM rip through the implementation.
2. OCaml has an idiomatic approach of using interface files for all modules that can be accessed outside their libraries, and interface files give LLMs a great précis of exactly what is wanted. They then just have to follow the types and fill in the blanks to get the implementation. It's nearly the perfect use case.
Both force the model to reason about types too much. The more constrained type system plus global inference merely holds them to what they already wrote, with very fast feedback.
Rust is fine if you need it but most things don’t and ocaml has more convenient abstractions for “regular” work. If you need rust you need rust but ocaml isn’t that far off in perf.
Haskell type system is too expressive, it itself becomes a place for the agent to make mistakes and get bogged down.
(1) complexity
(2) performance
For web frontend, it's derivative programming language, rescript, is also a secret weapon because of types, fast compilation times and first class support of React. Using React in rescript is much nicer than TypeScript.
Did you also compare F#?
Couldn't agree more. Even when the models could barely write it, the compiler was so good
Flamebait aside, has this been studied for real ? Curious how you would rate that...
Yes I contributed code to a paper on it this spring. It’s hard to measure and “studying” it just means feeding money into frontier models. If anyone has a few billion tokens for a couple masters students hmu so they can get it published.
Can it not be studied with open weight models? This is a genuinely curious question, not an attempt at scoring a point.
I'd be very interested to read this paper when it comes out.
I will add you to the list, I’ll definitely post it on HN also.
They had originally planned on june and my part is in so…. Me too.
I'm interested too - besides the paper, is it your personal experience that working with llms on ocaml is superior to other languages? I thought with the sheer amount of training data languages like python and java would be "ideal"
No it’s more about speed and quality of the feedback loop. So you want the compiler that catches the most stuff when given the least information.