[alganet]

> I think a huge reason why LLMs are so far ahead in programming

Are they? Last time I checked (couple of seconds ago), they still made silly mistakes and hallucinated wildly.

Example: https://imgur.com/a/Cj2y8km (AI teaching me about the Coltrane operator, that obviously does not exist).

[gcanko]

You're using the worst model when it comes to programming, not sure what point you're trying prove here. That's why when someone starts ranting how useless ai models are when it comes to coding I always assume they're just using inferior models.

[alganet]

My question was very simple. Suitable for a simpler model.

I can come up with prompts that make better models hallucinate (see post below).

I don't understand your objection. This is a known fact, LLMs hallucinate shit regardless of the model size.

[CamperBob2]

LLMs are getting better. Are you?

Nothing matters in this business except the first couple of time derivatives.

[alganet]

Maybe I'm not.

However, I'm discussing this within the context of the study presented in the paper, not some future yet-to-be-achieved performance expectation.

If we step outside the context of the paper (not advised), I think any average developer is better than an LLM at energy efficiency. LLMs cheat by consuming more resources than a human. "Better" is quite relative. So, let's keep reasonable.

[aoeusnth1]

Are you intentionally sandbagging the LLMs to prove a point, or do you really think 4o-mini is good enough for programming?

Even 2.5 flash easily gets this https://imgur.com/a/OfW30eL

[alganet]

The point is that I can make them hallucinate quite easily. And they don't demonstrate knowing their own limitations.

For example, 2.5 Flash fails to explain the difference between the short ternary operator (null coalescing) and the Elvis operator.

https://imgur.com/a/xKjuoqV

Even when I specify a language (therefore clearing the confusion, supposedly), it still fails to even recognize the Elvis operator by its toupe, and mixes it up the explanation (it doesn't even understand what I asked).

https://imgur.com/a/itr87hM

So, the point I'm trying to make is that they're not any better for programming than they're for chemistry.

[CamperBob2]

Flash is the wrong model for questions like that -- not that you care -- but if you'd like to share the actual prompt you gave it, I'll try it in 2.5 Pro.

[alganet]

"explain me the difference between the short ternary operator and the Elvis operator"

When it failed, I replied: "in PHP".

You don't seem to understand what I'm trying to say and instead is trying to defend LLMs for a fault that is a fact known in the industry at large.

I'm sure that in short time, I could make 2.5 Pro hallucinate as well. If not on this question, on others.

This behavior is inline with the paper conclusions:

> many models are not able to reliably estimate their own limitations.

(see Figure 3, they tested a variety of models of different qualities).

This is the kind of question a junior developer can answer with simple google searches, or by reading the PHP manual, or just by testing it on a REPL. Why do we need a fancy model in order to answer such a simple inquiry? Would a beginner know that the answer is incorrect and he should use a different model?

Also, from the paper:

> For very relevant topics, the answers that models provide are wrong.

> Given that the models outperformed the average human in our study, we need to rethink how we teach and examine chemistry.

That's true for programming as well. It outperforms the average human, but then it makes silly mistakes that could confuse beginners. It displays confidence in being plain wrong.

The study also used manually curated questions for evaluation, so my prompt is not some dirty trick. It's totally inline with the context of this discussion.

[CamperBob2]

It's better than it was a year ago, as you'd have discovered for yourself if you used current models. Nothing else matters.

See if this looks any better (I don't know PHP): https://g.co/gemini/share/7849517fdb89

If it doesn't, what specifically is incorrect?

[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.

--

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.

--

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.

[CamperBob2]

They aren't getting any better at programming, so they naturally assume the LLMs aren't, either.