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.
> 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.
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.
Also being able to prove the relationship between different parts of the code enables a lot of productivity tooling like IDEs. Simple things like renaming a class or a struct become chores at best in a statically typed language, whereas in dynamic languages there is an element of risk in refactorings like that.
Sorry about that, it seems I unintentionally created a bit of controversy and am being a bit defensive.
I don't know, SQLite it's something that makes sense in theory, but I think its easier for ops people to just use a proper database. If you need to move the database to a separate machine, limit permissions, etc. its just easier to do.
SQLite is great for local apps that need a structured way to store their data, but I'm not really comfortable using it for more than that.
The fact that you have to operate a VM on your machine in order to use it is a no go for me. Either use Linux as your OS in that case, or spend the time to make a dev environment that actually works. Even just mounting a directory is a painful exercise, and something that comes with performance limitations. I've had to deal with networking problems, drive problems, all sorts of issues that you really don't want to waste your time fixing when you have a deadline coming up.
Multiple levels of virtualization, meaning you have the containerization part which is virtualizing the userspace of the VM, and the virtualization of the VM itself. Your development environment consists of multiple layers of complex, not to mention fragile technologies which is an incredibly bad idea for something you rely on heavily for your day to day work.
The people I know who have to use it run a fully fledged Linux VM and do all their work on that. That is how bad the developer experience is on Windows.
Also I'm a bit insulted that you immediately assumed that I'm speaking from a lack of experience, as opposed to years of experience supporting docker dev environments on windows and failing to find a solution that doesn't come with severe drawbacks.
This works great, assuming you're using Linux. On Windows this kind of a setup is a nightmare to maintain, since if something goes wrong you have to troubleshoot through several layers of virtualization and weird OS integrations to understand what's happening. Venv is a much better solution for that.
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.