BSD and MIT license still require attribution of the used source code (there exists a MIT No Attribution License, though: https://en.wikipedia.org/w/index.php?title=MIT_License&oldid...).

Which in this scenario could be accomplished by starting that “this software contains algorithmically generated code that was trained using MIT derived code from X, Y, and Z.

This attribution list would be very long, but it could be done.

I think the interesting thing here would be to compare the generated code with the original training data after the fact. If the generated code does not already exist (with some degree of similarity), then it would be okay to use. Otherwise, if it did already exist, you’d then need to attribute the authors of the chunk of code — which you’d now know.

I’m not discounting the hurdles involved, but there might be ways to overcome them.

On the other hand, open source licenses haven’t been tested thoroughly in court, so maybe the result would be to throw out such attribution requirements entirely. The main relevant case to date is https://en.wikipedia.org/wiki/Jacobsen_v._Katzer

In reality through, we'll all just end up using the MIT No Attribution License copilot.

Great, so GPL code would be left alone. I don't see how that's a bad thing.

Surely the solution would be to give credit to every author from the training corpus. I am looking forward to the 10 000 lines of copyrights in every header. :P

If Microsoft had trained it on its own code, there would be no such problems. Surely a company as large as Microsoft has produced enough code over the years to create a large enough training dataset.

I keep seeing this sentiment from the GPL/"laundering" side of the debate.

Believe me, Microsoft wouldn't have released this thing (after what, 6 months of beta testing?) if they thought they had any "problems" at all.

I'm not saying I don't sort of agree with you, but is there no room for what's actually _likely_ to happen in this debate? Because as best as I can tell, they aren't going to see any real legal issues from this.

(There's also an option to remove generations that result in a collision with actual GitHub code, just fyi)

I feel like when the singularity happens HN is going to be flooded with programmers mad that they got automated away despite it very much being one of the primary goals of computer science and software engineering. This stuff is a kind of just a fact of life now.

Salesforce trained models (on GitHub) competitive with copilot without needing to own GitHub. I would spend less time worrying about how to lawyer up and more time figuring out how you're going to adapt to these new tools. That's the gig.

The simply way to test the legal theory behind copilot would be to write a AI that write music notes, using music scraped from youtube or any other large music library. The idea that one can train on "public available material" and produce algorithms that output large chunk of copyrighted material is a bit untested in court, but go against the wrong target and we will quickly see a response. We have actually seen some traces of this with news bots that scrapes news site and produce "novel" interpretation of existing news, especially sports news.

No, we're not. Further, Amazon just announced a similar product and Salesforce has literally _released weights_ for their code models. You can't put the genie back in the bottle.

Actually enforcing any action when the representations are learned rather than hard-coded just seems impossible to me. They have a check box that removes any predictions matching existing code - that basically makes it impossible to discern the source since this will be based on some subjective "semantic closeness" BS.

They would. Did you just forget TAI? Microsoft didn't consider 4chan would train her to be the ultimate racist.

Do you work in marketing? Do you program?

I'm a machine learning engineer, amateur researcher and open source contributor. Before that I was a software engineer for 8 years.