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2bdb2 t1_j4f1d7p wrote

> If ChatGPT can generate code from simple prompts, then what's stopping OpenAI from setting up a positive coding feedback loop for it to work on its own fork of itself? > > I'll come right out and say it: why isn't ChatGPT the seed for a proto-AGI?

Being generous, the code written by ChatGPT is at best at the level of a mediocre first year IT student. It can write simple boilerplate based on solutions it's already seen, but has limited ability to actually solve complex problems.

This is still an incredibly impressive achievement and it blows my mind every time I see it in action. But it's about as likely to make the next major breakthrough in AI research as our imaginary mediocre first year IT student is.

It's hard not to imagine a point where AI is able to improve itself faster than humans can, thus essentially writing the next version of itself. But we're not there yet.

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__ingeniare__ t1_j4fry4r wrote

Even if it could code better than humans (like AlphaCode, that outperforms most humans in coding competitions), that's not the hard part.

The hard part is the science/engineering aspect of machine learning, programming is just the implementation of the ideas when they are already thought out. Actually coming up with useful improvements is significantly harder and requires a thorough grasp of the mathematical underpinnings of ML. ChatGPT is nowhere near capable of making useful contributions to the machine learning research community (or in other words, capable of writing a ML paper), and therefore it is incapable of improving its own software. AI most likely will reach that level at some point however, possibly in the near future.

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banuk_sickness_eater t1_j4hbc7w wrote

ChatGPT can't code better than a first year but DeepMind's AlphaCode can certainly code better than ever most median quality developers.

So let's rephrase the question to focus on AlphaCode instead of ChatGPT.

How does that change your response, if at all?

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2bdb2 t1_j4j3pep wrote

> DeepMind's AlphaCode can certainly code better than ever most median quality developers.

AlphaCode does well at solving quiz questions. From my own experience with those types of quizzes, they're mostly just maths questions solved with code.

Doing well at those types of questions has very little bearing on most real world software engineering.

Now to be fair, machine learning is a lot more math focused than typical software engineering. But if we're going with the assertion that "AlphaCode can certainly code better than ever most median quality developers" based on doing well at quiz questions, then I'm going to disagree.

> So let's rephrase the question to focus on AlphaCode instead of ChatGPT. > How does that change your response, if at all?

Not Really.

Don't get me wrong, AlphaCode is still mind blowing. I really don't want to understate how impressive it is. But I don't think it's at the level of being able to implement itself. Yet.

(Disclaimer: I am not an AI researcher, so take my opinion with a grain of salt).

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Nill444 t1_j4ff4gi wrote

>It can write simple boilerplate based on solutions it's already seen,

It can solve Advent of Code problems...

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manOnPavementWaving t1_j4fi6f0 wrote

Mediocre first year IT students can do that. But no way it's writing an efficient flash attention kernel without having seen one before.

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2bdb2 t1_j4fw5ty wrote

>It can solve Advent of Code problems...

Which is a collection of relatively simple problems, commonly solved by first year students, where the solutions are almost certainly in the training data set....

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Nill444 t1_j4gfcfx wrote

advent of code 2022 was ongoing when people were using ChatGPT for solving problems (although not all of them) it couldn't have been in the data set.

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2bdb2 t1_j4j84pp wrote

The specific questions may not have been in the data set, but it'll have seen the same types of questions before.

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