Yeah and not having to do precise prompt engineering is a major advantage of GPT-4 vs other models.
A skilled human will distinguish themselves from a less skilled human by also thinking about the overall problem and helping make sure the specification is correct. This far, I have not seen an AI meet that bar unless the problem is something well-covered already on the web.
I have seen ChatGPT (3.5 and 4) output code that is syntactically correct, executes without errors, and does the wrong things in ways that are not entirely obvious to me until I read the docs myself.
I've only used Bard so far, but indeed, it has never replied to my question with a clarifying question. Only with a statement. This seems like an obvious evolution of the chatbot concept...
edit: I guess GPT-4 has better reading comprension than me!
I think I might give this one to Guanaco. I’m moderately familiar with SQL, and I can’t really understand your question. You’re faking the reader out by using “join” to mean something which is not JOIN.
So do you mean to concatenate a string in a column (coming from a single row) to a “string separated with a comma”? If so (and assuming “separated” means starting or ending with), then Guanaco nailed it. If you meant to join (in the Python sense) the values from a given column in _multiple_ rows, then GPT-4 is doing better.
But GPT-4 gave no explanation, and my general experience with it is that it’s happy to write code that does _something_ vaguely related to the prompt. As the prompt gets more complex or unusual, the degree to which the code doesn’t actually do something useful increases. And I have had quite poor results getting ChatGPT to generate code along with some explanation such that the code actually matches the explanation.