Both translation and subtitles have highly efficient tooling when in the hands of a professional. Translators nowadays use a mix and will build up a dynamic database as they go through a corpus that needs coherence. What's bad in this instance is not the usage of some AI, but of a badly adapted AI and ultimately of mediocre results which gives an amateurish impression.
luciole
No. February 12, 2015 actually was an extremely polluted day for Paris. The fine particles count was through the roof and you can find articles about it. Please don't pull stuff out of your ass.
having to wait for javascript to load, decompress, parse, JIT, transmogrify, rejimble and perform two rinse cycles
This is whole sentence is facetious nonsense. Just-in-time compilation is not in websites, it's in browsers, and it was a massive performance gain for the web. Sending files gzipped over the wire has been going on forever and the decompressing on receival is nothing compared to the gains on load time. I'm going to ignore the made up words. If you don't know you don't know. Please don't confidently make shit up.
EDIT: I'm with about the nags though. Fuck them nags.
Some non peer reviewed paper with a tiny sample size is hardly enough to go "The Science has spoken". On the other hand, one can make an appeal to the intuitive idea that lack of practice implies lack of skill.
This immediately points to the pernicious effects of touting LLMs as a machine to do all the thinking for you. Heck, the enthusiasts are even using LLMs to do their social interactions for them.
This is a warning to people as much as workplaces: is this task you're offloading to LLMs really a skill you want to see atrophied?
I know far too little about compilers & interpreters to have anything to say about performance so I’ll leave that subject to wiser programmers.
What I can say about the usage itself of dynamically vs statically typed languages is that I struggle with assessments that attempt to quantify the differences between the two paradigms. I’ve come to consider programming has a craft, and as such the qualitative properties of the tools, and especially the languages, matter significantly.
I’ve been switching back and forth between dynamic and static languages lately. Although dynamic languages do feel more straight to the point, static languages are easier to navigate through. All that typing information can be harnessed by intellisense and empower the non-linear reading needed to understand a program. That’s valuable for the whole life cycle of the software, not just the time to reach initial release. It’s kind of a rigid vs fluid dichotomy.
DUCKIES!! They so smol
I saw some wild geese a week ago and their offspring were pretty big and well into shedding their dawn. They were in that awkward age