Mojo’s starting point is absurdly complex. Seems very obviously doomed to me.
Julia is a very clever design, but it still never felt that pleasant to use. I think it was held back by using llvm as a JIT, and by the single-minded focus on data science. Programming languages need to be more opportunistic than that to succeed, imo.
The github blurb says the language is comparable to general purpose languages like python and haskell.
Perhaps unintentionally, this seems to imply that the language can speed up literally any algorithm linearly with core count, which is impossible.
If it can automatically accelerate a program that has parallel data dependencies, that would also be a huge claim, but one that is at least theoretically possible.
Out of the ones you listed I’d suggest Julia or Clojure. They are simple and have interactive modes you can use to experiment easily.
Experienced programmers often undersell the value of interactive prompts because they don’t need them as much. They already have a detailed mental model of how most languages behave.
Another thing: although Julia and Clojure are simple, they are also quite obscure and have very experimental designs. Python might be a better choice. From a beginner’s perspective it’s very similar to Julia, but it’s vastly more popular and lots of people learn it as their first language.
Based on the languages you found, I’m guessing you were looking for something simple and elegant. I think Python fits this description too.
How did they ask all these random people and not bother to ask a single software engineer?
“Hi is this excuse real, or is it just a sign of an inappropriate relationship between the local council and a dodgy software company that pays more dividends than developers? Oh it’s the latter? Okay, thanks.”
You can argue about productivity and “progress” all you like, but none of that will raise you back into my good opinion.
Why would you quote this and then immediately argue about productivity and progress?
They are not stupid at all. Their interests are in conflict with the interests of tech workers and they are winning effortlessly, over and over again.
The big tech companies are all owned by the same people. If these layoffs cause google to lose market share to another company, it’s fine because they own that company too.
What matters is coordinating regular layoffs across the whole industry to reduce labour costs. It’s the same principle as a strike: if the whole industry does layoffs, workers gradually have to accept lower salaries. In other words, the employers are unionised and the employees are not.
This process will probably continue for the next 20 years, until tech workers have low salaries and no job security. It has happened to countless industries before, and I doubt we are special.
I’m sure the next big industries will be technology-focused, but that’s not the same as “tech”. They won’t involve people being paid $200k to write websites in ruby.
“As we’ve said, we’re responsibly investing in our company’s biggest priorities and the significant opportunities ahead,” said Google spokesperson Alex García-Kummert. “To best position us for these opportunities, throughout the second half of 2023 and into 2024, a number of our teams made changes to become more efficient and work better, remove layers, and align their resources to their biggest product priorities. Through this, we’re simplifying our structures to give employees more opportunity to work on our most innovative and important advances and our biggest company priorities, while reducing bureaucracy and layers”
There was this incredible management consultant in france in the 18th century. Name eludes me, but if he was still around Google could hire him and start finding some far more convincing efficiencies.
The guy was especially good at aligning resources to remove layers
I believe Mercury is intended to be comparable to languages like Java, C# and Ocaml, in terms of the performance profile and generality. I don’t know what it’s like in practice though.
I view it more as a fascinating proof of concept than a language I’d actually like to use. Really I just want new projects to steal ideas from it.
Datalog is sometimes used as an alternative to SQL. Prolog is used by researchers experimenting with rule systems (e.g. type systems, theorem provers, etc).
Mercury has been used to write regular desktop software, with a couple of notable successes.
One way to think about Mercury is that it’s like Haskell, except it’s so declarative that the functions can run backwards, generating arguments from return values! Obviously that comes with some pretty big caveats, but in many cases it works great and is extremely useful.
Prolog, Mercury, Datalog. Very of intrigued by Verse now that I know it has some logic programming features.
Mercury is, roughly, a fusion of Haskell and Prolog. Bizarre and fascinating.
Prolog and Datalog are great but not aimed at general purpose programming.
Really I just want to see more people trying to adapt ideas from logic programming for general purpose use. Logic programming feels truly magic at times, in a way that other paradigms do not (to me at least).
Literally any logic programming language
Why is this? Did they introduce breaking changes to the language or something?
I mean, let’s be real, Rust is really called out because it causes high drama between C devs and Rust advocates, which drives engagement.
It’s probably all kicking off in about 10 different comment sections right now
5 years ago everything was moving to TypeScript. Now everything has moved. Developers are still catching up, but it will be one-way traffic from here.
I’m guessing your manager thinks TypeScript is like CoffeeScript. It is not like CoffeeScript.
Also, TypeScript is only the beginning. In the halls of the tech giants most devs view TypeScript as a sticking plaster until things can be moved to webassembly. It will be a long time until that makes any dent in JS, but it will also be one-way traffic when it does.
It’s very common. I’d bet most software projects still fail. I once met a guy who’d been a gamedev for over 10 years at some big companies, and every game he ever worked on got cancelled.
Sometimes these long, poorly managed projects do succeed though. Usually because they launch a beta or get publicly scheduled for release, and the sudden reality check causes someone senior to trim the scope down dramatically.
It might be worth sticking around if you think you’re learning things, but impose some personal limits. Don’t kill yourself trying to meet some idiot’s impossible schedule. Work your contracted hours and no more. Be blunt and unashamed about how long tasks really take. Share your concerns when the month’s schedule looks unrealistic, referring back to previous tasks that overran. This is how you learn to one day become a lead who doesn’t run shitty projects like the one you’re on.
They are both doomed because neither is transformative enough to justify adoption. They are going to need to solve much harder problems to do that.
Take Rust as an example. It solved a problem that most people weren’t even paying attention to, because the accepted wisdom said it was impossible.