1. That we are unimpressed.
I'm gobsmacked.
2. That we don't think these are significant advances.
They're obviously huge advances.
3. That we don't think these models will have practical applications.
It's hard to imagine they won't.
4. That we think these systems are rubbish because they get things wrong.
I'm a programmer. I make mistakes all the time.
Having countered those views, the article then seems to imply that it follows that "we’ve now entered a world where 'programming' will look different." As someone who makes a living writing software I obviously have an interest in knowing whether that's true. I don't see much evidence of it yet.
These systems are certainly not (yet) capable of replacing a human programmer altogether, and whether they could ever do so is unknown. I'm interested in the implications of the technologies that have been developed so far - i.e. with the claim that "we've now entered a world..." So the question is about how useful these systems can be for human programmers, as tools.
The reason I'm skeptical of it is that the only model I've seen so far for such tooling is "have the machine generate code and have the human review it, select from candidate solutions and fix bugs". The problem is that doing so is, I expect, harder for the human than writing the code in the first place. I've mentioned this concern several times and not seen anybody even attempt to explain to me why I'm wrong about it. For example, at [1] I pointed out why some generated solutions for a particular problem would have only made my job harder and got accused of "screaming at a child for imperfect grammar."
Reviewing and fixing code is harder than writing it. Please explain why I'm wrong about that (it's certainly true for me, but maybe most people don't feel that way?), why it won't be a problem in practice or what planned applications there are for these technologies that would avoid the problem.
Please don't accuse me of cruelty to dogs or children.