gnus_migrate

I mean if youre going to think of it that way any Turing complete language fits the bill, but what I mean by universal is a language you would reach for to solve any problem you have and it would be better than any other language. It's not a computer science problem it's a software engineering problem.

There can be a universal language in theory, but it's borderline impossible to achieve. Every domain has a different set of problems that it needs to solve, and language design involves tradeoffs that may make sense for one domain but not another. That's why I think language wars are silly, without context it's impossible to say which language is "better", because you could have different answers depending on what you're trying to do.

In the end you shouldn't be too concerned with it. There are lots of languages, but all of them fall under two or three paradigms where if you learn one language from that paradigm, your skills are mostly transferable.

DMD is the reference implementation as far as I know, so I don't think they have the same issue that C and C++ have with regards to needing to have a standard that pleases everyone. I agree that it has an issue positioning itself relative to other languages, but to me D is the good kind of boring. It has most of what you need, there is very little that is surprising in it, if you find yourself needing to do something, probably D has an easy-ish way of doing it.

By the way, what you claimed “research shows” is so ridiculous that it’s hilarious that you wrote it while being serious.

There is still no research that definitively shows that static types reduce defects more than dynamic types, this is a fact. Turns out we are incredibly bad at studying this, so I don't know how you can say definitively that it is the case when even the people who study this for a living are not able to make that case.

The thing is the way they motivate new students to learn programming is by having them write programs that do something. Making a test green isn't as motivating as visually seeing the output of your work, and test fixtures can be complex to set up depending on the language. I mean students don't learn how to factor their code into methods until later into such a course, they're learning if statements and for loops and basic programming constructs. Don't you think having to explain setting up test fixtures and dependency inversion is a bit too much for people at that level?

https://youtu.be/WELBnE33dpY

It's not that there is evidence that it doesn't matter, but there is no evidence showing that it does.

A good language matters. A good type system matters. A good use of a good language with its type system, patterns, abstractions, ecosystem, and all it got to offer matters.

Eh research shows otherwise. Rust eliminates defects for a very particular set of problems, but when it comes to logical correctness it isn't better or worse than other languages. If those problems are prominent in your domain(such as you have to write a ton of concurrent code), Rust makes sense. Otherwise being well rested will have a bigger impact on the quality of your code than the best type system in the world.

In terms of dev practices, the only practice demonstrated to have a consistent positive impact on code quality is code reviews. Testing as well, but whether it's TDD or other kinds of testing doesn't really matter.

If you wanted to introduce every industry best practice in an intro course you'd never get to the actual programming.

It would be good to have a 1 credit course(one hour a week) where you learn industry best practices like version control, testing and stuff like that. But it definitely shouldn't be at the start.

Yeah but will people still care about contributing that information if they're not going to be compensated for it in any way? Like people get something out of contributing to stack overflow, even if it's just recognition. This is gone with ChatGPT.

I can think of four aspects needed to emulate human response: basic knowledge on various topics, logical reasoning, contextual memory, and ability to communicate; and ChatGPT seems to possess all four to a certain degree.

LLM's cannot reason, nor can they communicate. They can give the illusion of doing so, and that's if they have enough data in the domain you're prompting them with. Try to go into topics that aren't as popular on the internet, the illusion breaks down pretty quickly. This isn't "we're not there yet", it's a fundamental limitation of the technology. LLM's are designed to mimick the style of a human response, they don't have any logical capabilities.

Regardless of what you think is or isn’t intelligent, for programming help you just need something to go through tons of text and present the information most likely to help you, maybe modify it a little to fit your context. That doesn’t sound too far fetched considering what we have today and how much information are available on the internet.

You're the one who brought up general intelligence not me, but to respond to your point: The problem is that people had an incentive to contribute that text, and it wasn't necessarily monetary. Whether it was for internet points or just building a reputation, people got something in return for their time. With LLM's, that incentive is gone, because no matter what they contribute it's going to be fed to a model that won't attribute those contributions back to them.

Today LLM's are impressive because they use information that was contributed by millions of people. The more people rely on ChatGPT, the less information will be available to train it on, and the less impressive these models are going to be over time.

Hey, if people are going to go back to reading manuals like we're in the 1980's again is it such a bad thing? /s

It's insane how a single tool managed to completely destroy the value collectively created by people in over a decade.

We're not able to properly define general intelligence, let alone build something that qualifies as intelligent.