And also recently we saw GPT that generates articles, waifulabs that generates ... waifus... to be honest I cannot perceive the difference since all of them are "learning" (in a mechanical way of human created knowledge.
And also recently we saw GPT that generates articles, waifulabs that generates ... waifus... to be honest I cannot perceive the difference since all of them are "learning" (in a mechanical way of human created knowledge.
I'm really waiting for this to blow up from the open source license angle. Freely combining code with different license is a hellish undertaking on its own. But already just re-using some, say, GPL code, even staying under the same license, but without proper attribution, is Forbidden with capital F.
More like a defect approach, behavior like that is well known(1) to be basically guaranteed to happen with GPT-3 and similar approaches.
(1): By people involved in the respective science categories (Representation Learning/Deep Learning, NLP, etc.).
It's an interesting question.
1) When a human being reads code or a CS text book, we think of them extracting general principles from the code and so not having to repeat that particular code again. In contrast, what GPT-3 and Copilot seem to do is just extract sequences of little snippets, something that apparently requires them to regurgitate the text they've been trained on. That seem rather permanently dependent on the training corpus.
2) Human beings have a natural urge, a natural ethos, to help people learn. It's understandable. The thing is, when suddenly you're not talking people but machines, the reason for this urge easily vanish. Even if github was extracting knowledge from the code, I wouldn't have a reason to help them do so since that knowledge would be their entirely private property. They expect to charge people whatever they judge the going rate would be - why should anyone be helping them without similar compensation? That this is being done by "OpenAI", a company which went from open-nonprofit to closed-for-profit in a matter of few years, should accent this point. We're nowhere near a system that could digest all the knowledge of humankind. But if we got there, one might argue the result should belong to humankind rather than to one genius entrepreneur. And having the result belong one genius entrepreneur has some clear downsides.
TL;DR: The AI doesn't know it can't just copy past (from perfect memory) and as such it learned to sometimes just copy past thinks.
The GPT model doesn't: "learn to understand the code and reproduce code based on that knowledge".
What it learns is a bit of understanding but more similar to recombining and tweaking verbatim text snipped it had seen before, without even understanding them or the concept of "not just copy/pasting code". (But while knowing which patterns "fit together").
This means that the model will "if it fits" potentially copy/past code "from memory" instead of writing new code which just happens to be the same/similar. It's like a person with perfect memory sometimes copy pasting code they had seen before pretending they wrote the code based on their "knowledge". Except worse, as it also will copy semantic irrelevant comments or sensitive information (if not pre filtered out before training).
I.e. there is a difference between "having a different kind of understanding" and "vastly missing understanding but compensating it by copying remembered code snippets from memory".
Theoretically it could be possible to create a GPT model which is forced to only understand programming (somewhat) but not memorize text snippets, but practically I think we are still far away from this, as it's really hard to say if a model did memorize copyright protected code.