I think the exact opposite, ML is good for automating away the trivial, repetitive tasks that take time away from development but they have a harder time with making a coherent, maintainable architecture of interconnected modules.
It is also good for data analysis, for example when the dynamics of a system are complex but you have a lot of data. In that context, the algorithm doesn’t have to infer a model that matches reality completely, just one that is close enough for the region of interest.
Gets me soooo hard
I think I know what you meant but be aware that this can be very misinterpreted.
And you can use it on GNU Not Unix!
If you pick one at random, I’d say it’s about 50/50 of finding a racist.
Oh, look it’s the bearded racist man!
maybe we should not be building our world around the premise that it is
I feel like this is a really important bit. If LLMs turn out to have unsolvable issues that limit the scope of their application, that’s fine, every technology has that, but we need to be aware of that. A fallible machine learning model is not dangerous; AI-based grading, plagiarism checking, resume-filtering, coding, etc. without skepticism is dangerous.
LLMs probably have very good applications that could not be automated in the past but we should be very careful of what we assume those things to be.
“Quick! Eject the warp core engineers!”
I would just like to give props to you for owning up and listening to the information. I do not in any way think that you were wrong in your reasoning, just that there was more context that is likely relevant which you hadn’t been privy to, and once you were informed of it you reevaluated. Not everyone does that and I think a very valuable part of this community is when people do that (I know I’m not always particularly good at it myself).
literally killed xmpp a decade ago
This was Google/Alphabet.
I thought right-hand rule with Z up as thumb was standard in science? You usually project on the xy-plane, for example when calculating the distance to objects on a flat surface.
C++ is unironically my favorite language, especially coding in python feels so ambiguous and you need to take care of so many special cases that just wouldn’t even exist in C++.