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Usage is rising because corporate executives started getting kickbacks and thinking they could cut staff by implementing it. But developers who have actually had to use it have realized it can be useful in a few scenarios, but requires a ton of review of anything it writes because it rarely understands context and often makes mistakes that are really hard to debug because they are subtle. So anyone trying to use it for a language or system they don't understand well is going to have a hard time.
It never understands context.
And it cannot understand context because it does not think, it’s just an expensive prediction tool
It's just Markov chains running on a heap of poorly governed sources. Expensive because Markov chains are brutish to process. The only intelligence is in the source they calculate on. Literally a basic "what goes in comes out" math process.
Counterpoint: they want number go up.
Pro Tip: it doesn't even matter if number go up, when they know how to suck up to even higher-ups.
Executives are getting kickbacks? I've gotta do some research here.
This is a true statement.
That's not true. If you give it context, it understands and retains context quite well. The thing is that you can't just say "write code for me" and expect it to work.
Also, certain models are better than certain tasks than others.