True, code for critical IT infrastructure should always be reviewed. But from what I understand, this is difficult because there is one full-time developer (paid by the Rust Foundation) and a small number of volunteers, who don't have the time to review all the employee's changes.
aloso
joined 2 years ago
When I searched "bitcoin", I found the bitcoin crate, but I had to scroll down a bit.
because it's really not that much better than crates.io and it has the downside of the results being biased.
I use its search, because it produces much better search results. The crates.io search is almost unusable, it rarely finds anything useful in the top search results.
You confused revenue and profit. You must subtract expenses to calculate the profit. For example, if you buy something for $20 and sell it for $21, your revenue is $21, but your profit is only $1.
Facebook reported a profit of $39 billion in 2021 and $23 billion in 2022. This takes their expenses (salaries, offices, data centres, etc.) into account.
Sure, but raw pointers and unsafe Rust are still covered in the official learning material, so I assume that most Rust devs know about raw pointers.
I can recommend Lua. It is easy to learn, and easy to embed in a Rust program. With LuaJIT, it should be pretty fast, too.
Of course you can also embed a JavaScript runtime, but then your executable will probably be 50 MB larger. And I'm not a fan of Python.
The reddit thread has some interesting discussion, and a solution using no SIMD intrinsincs that is more than 200x faster, by using .chunks_exact(), and letting the compiler auto-vectorize it.
That link just compares benchmarks with and without warmup, but not without startup. The JVM's startup can take upwards of 2 seconds, depending on the program.
Microsoft does collect a lot of data. But storing every keystroke is first of all impractical, because it would take a lot of disk space to store every keystroke of every user, and secondly not very useful unless they also knew when, in which application, and in what context each key was pressed.
I do not use AI to solve programming problems.
First, LLMs like ChatGPT often produce incorrect answers to particularly difficult questions, but still seem completely confident in their answer. I don't trust software that would rather make something up than admit that it doesn't know the answer. People can make mistakes, too, but StackOverflow usually pushes the correct answer to the top through community upvotes.
Second, I rarely ask questions on StackOverflow. Most of the time, if I search for a few related keywords, Google will find an SO thread with the answer. This is much faster than writing a SO question and waiting for people to answer it; and it is also faster than explaining the question to ChatGPT.
Third, I'm familiar enough with the languages I use that I don't need help with simple questions anymore, like "how to iterate over a hashmap" or "how to randomly shuffle an array". The situations where I could use help are often so complicated that an LLM would probably be useless. Especially for large code bases, where the relevant code is spread across many files or even multiple repositories (e.g. a backend and a frontend), debugging the problem myself is more efficient than asking for help, be it an online community or a language model.