I really don't get those takes. AI is the best thing that ever happened to the Free Software world, it is basically turning any software into Free Software. You can just throw file formats, protocols or even plain binaries at the AI and it'll reverse engineer everything in a pinch. Users can finally modify software themselves, which was always the goal of the Free Software world, but very rarely happened in actuality, since it was just so damn complicated. AI lowered the barrier of entry tremendously, not just in terms of required knowledge, but especially time. Same with Creative Commons, sharing art and stuff, was a nice gesture, but rarely useful, since the level of work to modify a work to fit your project was pretty close to just doing it from scratch anyway. With AI everybody can toy around with image generators and get what they want.
Is a social contract being broken? Yeah, kind of, but the problems that that contract existed to solve are no longer a thing. Creation is now easy and commodified. We finally have computer we can interact with in natural language, something people tried to do for at least 70 years and never made any significant progress on until LLM arrived.
If you want to gatekeep or only create stuff to boost your own ego or portfolio, then AI might be an issue, if you actually want to build stuff, AI is godsend. We are essentially living in the StarTrek future with Holodecks and replicators and people still find reason to complain.
> If you want to gatekeep or only create stuff to boost your own ego or portfolio, then AI might be an issue, if you actually want to build stuff, AI is godsend.
Exactly this. I've been very confused by the free software advocates that seemed to hate AI until I realized their reasons for releasing software under an open source license were very different than what I assumed they were.
I release my code as free software for two reasons:
1. The credits for my code are protected (with the GPL you have to tell where your code originates from). That's the ego part. It's important to me because I'm not paid for my software. So credits are an important reward.
2. I want people to think twice about reusing my code. I use the GPL license because I think sharing software is the ultimate goal. So I force people to share my software by using the GPL. That may sound "extreme" (that's the whole open source vs free software debate) but, not being a full time politician, I can't change laws to push society in the direction I want. At my level, that "push" is the GPL choice. Maybe it's not noble enough, maybe it's cowardice, but it's my way (compare that with those who simply don't care).
AI severely weakens both of these. And for people like me, this forces us to reconsider our position. For my part, I accept the legal point of view that A.I. doesn't steal code, and just reproduces the ideas in the code. So, as far as ideas can flow in society, I'm OK with that (that's the principle behind copyright laws).
If AI has its way, one day one will not need to write software, we'll just ask the AI. In that case, software will be dead and free software will die with it too. By then I'll do my "local politics" another way and follow the next RMS.
> A.I. doesn't steal code, and just reproduces the ideas in the code
Then they don't need to train on github, no? Why not release a new model trained from Knuth's Art of Programming, Cormen's Introduction to Algorithms and the C specification.
Feel free to throw in any other published literature related to STEM, but stick to the code samples from the books.
I'm certain it'll be able to change the color of a CSS button, right?
What you said doesn't disagree with what the parent said.
LLM can be trained on a code and at the same time reproduce the core ideas. That's what LLMs do after all - they convert the training data into their own internal models and representations, and then reproduce the ideas.
Sure, some things/patterns, that were repeated multiple times, LLMs will tend to repeat verbatim as well, but that's not that big of a problem.
As a person who invented a few algorithms on my own I absolutely love LLMs and I don't mind them being trained on my work, but yeah - I've been way less likely to publish open source over the last year. In the past, if some of my stuff got traction, the credit was close to automatic (early adopters credited or at least knew where they got it from). Nowadays, LLMs will train on these ideas, rewrite them, and give no credit.
Still, I prefer this to having no LLMs at all.
> but stick to the code samples from the books.
> I'm certain it'll be able to change the color of a CSS button, right?
A good enough LLM will just decompile a browser, figure out CSS spec from it, and yes - figure out how to change the color of a CSS button from first principles. There is no point to do this with CSS, but with other things it's now easier to just dig through sorces or direct bytecode than to bother checking docs.
Plenty of software on the internet on fully open license (e.g. MIT, copyleft and so on) to train on.
Also, it would be relatively easy to build synthetic datasets for training.
I, for one, don’t mind models being trained on stuff I produced and shared publicly over the last 20 years. I did it for common good, including commercial uses, and this is one of them.
Plenty of people who never produced any open source trying to argue as if if they did.
grumbel · · focus · HN ↗
Is a social contract being broken? Yeah, kind of, but the problems that that contract existed to solve are no longer a thing. Creation is now easy and commodified. We finally have computer we can interact with in natural language, something people tried to do for at least 70 years and never made any significant progress on until LLM arrived.
If you want to gatekeep or only create stuff to boost your own ego or portfolio, then AI might be an issue, if you actually want to build stuff, AI is godsend. We are essentially living in the StarTrek future with Holodecks and replicators and people still find reason to complain.
rpdillon · · focus · HN ↗
Exactly this. I've been very confused by the free software advocates that seemed to hate AI until I realized their reasons for releasing software under an open source license were very different than what I assumed they were.
wiz21c · · focus · HN ↗
1. The credits for my code are protected (with the GPL you have to tell where your code originates from). That's the ego part. It's important to me because I'm not paid for my software. So credits are an important reward.
2. I want people to think twice about reusing my code. I use the GPL license because I think sharing software is the ultimate goal. So I force people to share my software by using the GPL. That may sound "extreme" (that's the whole open source vs free software debate) but, not being a full time politician, I can't change laws to push society in the direction I want. At my level, that "push" is the GPL choice. Maybe it's not noble enough, maybe it's cowardice, but it's my way (compare that with those who simply don't care).
AI severely weakens both of these. And for people like me, this forces us to reconsider our position. For my part, I accept the legal point of view that A.I. doesn't steal code, and just reproduces the ideas in the code. So, as far as ideas can flow in society, I'm OK with that (that's the principle behind copyright laws).
If AI has its way, one day one will not need to write software, we'll just ask the AI. In that case, software will be dead and free software will die with it too. By then I'll do my "local politics" another way and follow the next RMS.
za_creature · · focus · HN ↗
Then they don't need to train on github, no? Why not release a new model trained from Knuth's Art of Programming, Cormen's Introduction to Algorithms and the C specification.
Feel free to throw in any other published literature related to STEM, but stick to the code samples from the books.
I'm certain it'll be able to change the color of a CSS button, right?
kolinko · · focus · HN ↗
LLM can be trained on a code and at the same time reproduce the core ideas. That's what LLMs do after all - they convert the training data into their own internal models and representations, and then reproduce the ideas.
Sure, some things/patterns, that were repeated multiple times, LLMs will tend to repeat verbatim as well, but that's not that big of a problem.
As a person who invented a few algorithms on my own I absolutely love LLMs and I don't mind them being trained on my work, but yeah - I've been way less likely to publish open source over the last year. In the past, if some of my stuff got traction, the credit was close to automatic (early adopters credited or at least knew where they got it from). Nowadays, LLMs will train on these ideas, rewrite them, and give no credit.
Still, I prefer this to having no LLMs at all.
> but stick to the code samples from the books. > I'm certain it'll be able to change the color of a CSS button, right?
A good enough LLM will just decompile a browser, figure out CSS spec from it, and yes - figure out how to change the color of a CSS button from first principles. There is no point to do this with CSS, but with other things it's now easier to just dig through sorces or direct bytecode than to bother checking docs.
za_creature · · focus · HN ↗
Can it decompile a browser using a specification of x86 and the source code of the compiler?
e.g. without training on the source code and binaries of all software it was able to rip from the internet?
kolinko · · focus · HN ↗
Also, it would be relatively easy to build synthetic datasets for training.
I, for one, don’t mind models being trained on stuff I produced and shared publicly over the last 20 years. I did it for common good, including commercial uses, and this is one of them.
Plenty of people who never produced any open source trying to argue as if if they did.
za_creature · · focus · HN ↗
Feel free to put your code in the public domain, open source is a distinct contract.