Having spend hours upon hours with image snythesis for artistic hobby purposes, it is indeed an awesome tool. If you get into it you might learn about its limitations though.
Real knowledge here is often absend from the strongest AI prosletisers, others are more realistic about it. It still remains an awesome tool, but a limited one.
AIs today are not creative at all. They find statistical matches. They perform a different work than artists do.
But please, replace all your artwork with AI generated ones. I believe the forced "adapt" phase with that approach would realize itself rather quickly.
> It still remains an awesome tool, but a limited one.
And that's enough to drive significant industry-wide change. Just because it can't fully automate everything doesn't mean companies aren't going to expect (and, indeed, increasingly require) their employees to learn how to effectively utilize the technology. The CEO of Shopify recently made it clear that refusal to learn to use AI tools will factor directly into performance evaluations for all staff. This is just the beginning. It's best to be wise and go where the puck is headed.
The article gives several examples of where these tools are used to rapidly accelerate experimentation, pitches, etc. Supposedly this is a bad thing and should be avoided because it's not sufficiently artisan, but no defensible argument was presented as to why these use cases are illegitimate.
In terms of writing code, we're entering an era where developers who have invested in learning how to utilize this technology are simply better and more valuable to companies than developers who have not. Naysayers will find all sorts of false ways to nitpick that statement, yet it remains true. Effective usage means knowing when (and when not) to use these tools -- and to what degree. It also, for now at least, means remaining a human expert about the craft at hand.