GitHub Copilot is not infringing your copyright (2021) • Hacker News Board

Re: GitHub Copilot is not infringing your copyright (2021)

#151

Post by anticensor » Fri, Jul 12, 2024, 8:16 PM UTC

bluesign wrote: post #114

mzl wrote: post #91

Earlier quoted context omitted.

If one was sufficiently inspired by code A when writing code B, then it is a derivate work. This is a core tenet of copyright law. At what measure is one sufficiently inspired for it to be a derivate work? That is up to courts to decide.

yeah the problem here is there is no 'code A' usually, it is more like: 1000s of GPLed code (A1, A2, ... An ) Technically when you get a piece from each, there is no infringement legally. ( as they have all different copyright holders )

> Technically when you get a piece from each, there is no infringement legally.

False in ex-Commonwealth countries and Japan.

Re: GitHub Copilot is not infringing your copyright (2021)

#152

Post by kimixa » Fri, Jul 12, 2024, 11:32 PM UTC

elpocko wrote: post #134

kimixa wrote: post #40

Earlier quoted context omitted.

I've coded a JPEG compressor. It's clear the output of the machine isn't exactly the same of the input, being lossy, so I guess the output is not protected by copyright either.

The input to your JPEG compressor is an image that someone/something created, and the goal of your compressor is to replicate its input as closely as possible. It doesn't create new data, it merely encodes pre-existent data. The input to my algorithms is a single number, and the goal is to create something new and distinctive that is clearly different from anything that existed before, and that wouldn't exist without…

Really, the "input" to current deep learning algorithms includes all the training data. Which is where the root of the issue is.

There's a reason why compression comparisons tend to include the size of the decompressor in their comparisons - my "magic algorithm can compress wikipedia down to a single bye!" is less impressive with the "decompressor" contains a copy of wikipedia.

Re: GitHub Copilot is not infringing your copyright (2021)

#153

Post by [deleted] » Sat, Jul 13, 2024, 11:47 PM UTC

kimixa wrote: post #152

elpocko wrote: post #134

Earlier quoted context omitted.

The input to your JPEG compressor is an image that someone/something created, and the goal of your compressor is to replicate its input as closely as possible. It doesn't create new data, it merely encodes pre-existent data. The input to my algorithms is a single number, and the goal is to create something new and distinctive that is clearly different from anything that existed before, and that wouldn't exist without…

Really, the "input" to current deep learning algorithms includes all the training data. Which is where the root of the issue is. There's a reason why compression comparisons tend to include the size of the decompressor in their comparisons - my "magic algorithm can compress wikipedia down to a single bye!" is less impressive with the "decompressor" contains a copy of wikipedia.

[deleted]

Re: GitHub Copilot is not infringing your copyright (2021)

#154

Post by carom » Mon, Jul 15, 2024, 8:24 AM UTC

wakawaka28 wrote: post #150

carom wrote: post #20

This is missing the largest argument in my opinion. The weights are the derivative work of the GPL licensed code and should therefore be released under the GPL. I would say these companies release their weights or simply not train on copyleft code. It is truly amazing how many people will shill for these massive corporations that claim they love open source or that their AI is open while they profit off of the violat…

It would make no sense to release the weights under the GPL because machine-generated stuff is uncopyrightable. There should be an argument about the model generating derivative works without attribution as a consequence of how it works. But that machine-generated stuff is also uncopyrightable, even though it might be kept secret.

What about compiler outputs? Those were initially not copyrightable then it was legislated that they were. So there is some precedent there and I would not be surprised if we saw copyrightable weights in the future (as a "compilation" of the dataset).

Re: GitHub Copilot is not infringing your copyright (2021)

#155

Post by carom » Mon, Jul 15, 2024, 8:26 AM UTC

dist-epoch wrote: post #60

carom wrote: post #20

This is missing the largest argument in my opinion. The weights are the derivative work of the GPL licensed code and should therefore be released under the GPL. I would say these companies release their weights or simply not train on copyleft code. It is truly amazing how many people will shill for these massive corporations that claim they love open source or that their AI is open while they profit off of the violat…

> The weights are the derivative work of the GPL licensed code EU courts disagree: > Under European copyright law, scraping GPL-licensed code, or any other copyrighted work, is legal, regardless of the licence used.

The weights are not created by scraping. Sure, you can scrape it, but what you do with it matters.

#156

Post by wakawaka28 » Mon, Jul 15, 2024, 1:19 PM UTC

carom wrote: post #154

wakawaka28 wrote: post #150

Earlier quoted context omitted.

It would make no sense to release the weights under the GPL because machine-generated stuff is uncopyrightable. There should be an argument about the model generating derivative works without attribution as a consequence of how it works. But that machine-generated stuff is also uncopyrightable, even though it might be kept secret.

What about compiler outputs? Those were initially not copyrightable then it was legislated that they were. So there is some precedent there and I would not be surprised if we saw copyrightable weights in the future (as a "compilation" of the dataset).

It could be legislated of course. But the difference is pretty drastic. Almost nobody is creating binaries without a compiler. It is a mechanical process, but essentially everyone uses the same mechanical processes to generate binaries. I haven't looked at this issue in a while but I think compiled binaries are treated in a way similar to that of recorded music. For example, the particular bit patterns from a synthesizer might be generated from sheet music, and that is akin to code vs. binaries. But the bit patterns are copyrightable only so far as they are equivalent to or the direct manifestation of a creative work.

There are other problems with releasing model weights under the GPL. It just doesn't fit, in the same way as releasing non-software under the GPL doesn't make sense.

Calling the output of generative AI copyrightable violates the spirit of copyright, as it is neither creative nor labor-intensive. We could quibble about that, but I think we can at least agree that the point is that this generative AI stuff requires very little skill to use in most cases and can't operate without prior art to train on. Other lame stuff has been copyrighted before, like paint splatters and stuff, but even that type of art appears to involve more skill than entering a few words into a generative AI.