You’d be surprised. Every time I try to introduce static type hints to Python code at work there are some weirdos that think it’s a bad idea.

I think a lot of the time it’s people using Vim or Emacs or whatever so they don’t see half the benefits.

I think we still must call this an “open question”.

Not sure I agree. I do think you’re right - it’s hard to prove these things because it’s fundamentally hard to prove things involving people, and also because most of the advantages of static types are irrelevant for tiny programs which is what many studies use.

But I don’t think that means you can’t use your judgement about it and come to a conclusion. Especially with languages like Python and Typescript that allow an any cop-out, it’s hard to see how anyone could really conclude that they aren’t better.

Here’s another example I came across recently: should bitwise & have lower precedence than == like it does in C? Experience has told us that the answer is definitely no, and virtually every modern language puts them the other way around. Is it an open question? No. Did anyone prove this? Also no.

To what? They don’t really have any serious competition.

Just being open source doesn’t guarantee a project’s survival. If Google were to abandon it the most likely outcome would be a community fork that gets 100th of the development manpower it gets now, and most developers would abandon the platform leading to it’s effective death.

But I also think it’s unlikely Google will abandon it. It’s actually quite good and quite popular now.

Definitely a high usefulness-to-complexity ratio. But IMO the core advantage of Make is that most people already know it and have it installed (except on Windows).

By the time you need something complex enough that Make can’t handle it (e.g. if you get into recursive Make) then you’re better off using something like Bazel or Buck2 which also solves a bunch of other builds system problems (missing dependencies, early cut-off, remote builds, etc.).

However this does sound very useful for wrangling lots of other broken build systems - I can totally see why Buildroot are looking at it.

I recently tried to create a basic Linux system from scratch (OpenSBI + Linux + Busybox + …) which is basically what Buildroot does, and it’s a right pain because there are dependencies between different build systems, some of them don’t actually rebuild properly when dependencies change (cough OpenSBI)… This feels like it could cajole them into something that actually works.

They never gave people static IPs by default in general. Done did if you were lucky but most didn’t. (In the UK at least.) Hence the existence of things like dyndns.

Ah yeah I forgot about namespaces. I don’t think they’re a popular feature.

The other two only generate code for backwards compatibility. When targeting the latest JavaScript versions they don’t generate anything.

Ok decorators are technically still only a proposal so they’re slightly jumping the gun there, but the point remains.

Hmm I’m not sure if this is solid parametric CAD. It let me draw a rectangle and then extrude that giving a zero-width tube… There doesn’t seem to be any way to add dimensions either.

Definitely loads quickly though and feels snappy. But for actually getting stuff done FreeCAD is definitely the best FOSS option at the moment.

No they don’t. Enums are actually unique in being the only Typescript feature that requires code gen, and they consider that to have been a mistake.

In any case that’s not the cause of the difference here.

Private or obscure ones I guess.

Real-world (macro) benchmarks are at least harder to game, e.g. how long does it take to launch chrome and open Gmail? That’s actually a useful task so if you speed it up, great!

Also these benchmarks are particularly easy to game because it’s the actual benchmark itself that gets gamed (i.e. the code for each language); not the thing you are trying to measure with the benchmark (the compilers). Usually the benchmark is fixed and it’s the targets that contort themselves to it, which is at least a little harder.

For example some of the benchmarks for language X literally just call into C libraries to do the work.

Their measurements include invocation of the interpreter. And parsing TS involves bigger overhead than parsing JS.

But TS is compiled to JS so it’s the same interpreter in both cases. If they’re including the time for tsc in their benchmark then that’s an even bigger WTF.

It has no memory, for one.

It has very short term memory in the form of it’s token context. Especially with something like Meta’s Coconut.

What makes you think that it does know its in a conversation?

I don’t really. Yet. But I also don’t think that it is fundamentally impossible for LLMs to think, like you seem to. I also don’t think the definition of the word “think” is so narrow that it requires that level of self-awareness. Do you think a mouse is really aware it is a mouse? What about a spider?

Ah this ancient nonsense. Typescript and JavaScript get different results!

It’s all based on

https://en.wikipedia.org/wiki/The_Computer_Language_Benchmarks_Game

Microbenchmarks which are heavily gamed. Though in fairness the overall results are fairly reasonable.

Still I don’t think this “energy efficiency” result is worth talking about. Faster languages are more energy efficient. Who new?

Edit: this also has some hilarious visualisation WTFs - using dendograms for performance figures (figures 4-6)! Why on earth do figures 7-12 include line graphs?

Your comment doesn’t account for the fact that LLMs can generalise. Often not very well but they can produce outputs for inputs not seen in their training sets. Otherwise what would be the point?

You would not ask a piece of cardboard so solve a math problem, would you?

Uhhh you know LLMs can solve quite complex maths problems? Including novel ones.

And how do you know LLMs can’t tell that they are involved in a conversation?

Unless you think there is something non-computational in the human brain, then you must accept that computers are - in theory - capable of thinking. With the right software and sufficiently powerful hardware.

Given that truth (which I think you can only avoid through religion or quantum quackery), you can’t just say “it’s only maths; it can’t be thinking” because we know that maths can think.

Do LLMs “think”? The definition of “think” is wooly enough and we understand them little enough that it’s quite an assertion to say that they definitely don’t.

This argument makes no more sense than trying to say that a plant is thinking because brains are made of cells and so are plants.

By that logic we also conclude that the human brain doesn’t “think” about what it is saying.

It’s really amazing the number of people trying to argue that LLMs are useless, while simultaneously so many people are using them successfully. Makes me wonder if they’ve even tried them.

Well… isn’t it? If one’s daily or most frequent back-and-forth journeys don’t exceed 100 ㎞, then a 160 ㎞ range is indeed fine.

Uhm… No. Most people only have one car so if you get one that only works 95% if the time it’s going to be super inconvenient when you have to hire a car every time you go on holiday or visit your family or go to a distant concert or whatever.

That’s why low range electric cars are not very popular.

Ah yes the old pointless vague anecdote.

If your argument is “LLMs can’t do useful work”, and then I say “no, I’ve used them to do useful work many times” how is that a pointless vague anecdote? It’s a direct proof that you’re wrong.

Promoting pseudo-science.

Sorry what? This is bizarre.