Comment by alganet
What I expect from a human is to ask "in which language?", because it makes a difference. If no language was supplied, I expect a brief summary of null coalescing and shorthand ternary options with useful examples in the most popular languages.
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The JavaScript example should have mentioned the use of `||` (or operator) to achieve the same effect of a shorthand ternary. It's common knowledge.
In PHP specifically, `??` allows you to null coalesce array keys and other types of complex objects. You don't need to write `isset($arr[1]) ? $arr[1] : "ipsum"`, you can just `$arr[1] ?? "ipsum"`. TypeScript has it too and I would expect anyone answering about JavaScript to mention that, since it's highly relevant for the ecosystem.
Also in PHP, there is the `?:` that is similar to what `||` does in JavaScript in an assignment context, but due to type juggling, it can act as a null coalesce operator too (although not for arrays or complex types).
The PHP example they present, therefore, is plain wrong and would lead to a warning for trying to access an unset array key. Something that the `??` operator (not mentioned in the response) would solve.
I would go as far as explaining null conditional acessors as well `$foo?->bar` or `foo?.bar`. Those are often called Elvis operators coloquially and fall within the same overall problem-solving category.
The LLM answer is a dangerous mix of incomplete and wrong. It could lead a beginner to adopt an old bad practice, or leave a beginner without a more thorough explanation. Worst of all, the LLM makes those mistakes with confidence.
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What I think is going on is that null handling is such a basic task, that programmers learn it in the first few years of their careers and almost never write about it. There's no need to. I'm sure a code-completion LLM can code using those operators effectively, but LLMs cannot talk about them consistently. They'll only get better at it if we get better at it, and we often don't need to write about it.
In this particular elvis operator thing, there has been no significant improvement in the correctedness of the answer in __more than 2 whole years__. Samples from ChatGPT in 2023 (note my image date): https://imgur.com/UztTTYQ https://imgur.com/nsqY2rH.
So, _for some things_, contrary to what you suggested before, LLMs are not getting that much better.
Having read the reply in 2.5 Pro, I have to agree with you there. I'm surprised it whiffed on those details. They are fairly basic and rather important. It could have provided a better answer (I fed your reply back to it at https://g.co/gemini/share/7f87b5e9d699 ), but it did a crappy job deciding what to include in its initial response.
I don't agree that you can pick one cherry example and use it to illustrate anything general about the progress of the models in general, though. There are far too many counterexamples to enumerate.
(Actually I suspect what will happen is that we'll change the way we write documentation to make it easy for LLMs to assimilate. I know I'm already doing that myself.)