'We support the work of those who are trying to limit the harm generative AI is doing to videogames and our world, and apologise that Big Walk’s LLM usage may not meet their standards'
Speaking as a software engineer, code sits in a weird spot in terms of copyright. The exact code as written can be protected by copyright. But the mechanics of it cannot. Furthermore, code that performs a task that is so generic or even necessary for the mechanism it serves also cannot be protected. I can’t copyright a for-loop that iterates through an array, for example. Nor can I copyright the use of libraries built and freely published by others. Boiler plate code and importance tools are never protected.
There are so many libraries of tools, and fully, freely available code as open source, so much raw code content and understanding in forums and textbooks that, honestly, the only real protection any code has is the actual source code as written for commercial products. And you simply do not need those examples for training. And that is if you can even get direct access to those things. They’re not exposed to the public by design.
I would imagine that little, if any, actually copywritten code was ever used in training LLMs. That isn’t to say that there isn’t an element of use without credit to sources and individuals. But really that problem existed well before LLMs and, again, is morally grey when it comes to matters of mechanics.
Code is a unique beast. It is essentially mechanical. It works or it doesn’t. It is a quantitative measure, not a qualitative one like music, art, film, etc. You can train LLMs not just on code examples, but on concrete outcomes, pass-fail requirement conditions. And it is made of a finite set of operations, like math. It is only in its patterns of these operations that actual meaning and work is derived. LLMs can find such patterns iteratively without copying someone else’s work.
But even for code it has used, to me, coding has always felt collaborative. How many thousands of memes have been made about programmers googling everything in their work. It’s true. Coding has always been community-driven and open-source by default, at least in my academic and professional life, and so training LLMs on this data also feels less offensive to me. And I say that as an engineer who both uses Claude as a tool in my work now, and one who is likely to be laid off in the next year, in part because of this. But I blame corporate greed and lack of integrity for that, not the fact that this tool exists. I have other problems with AI coders, and AI in general, not the least of which is just about every aspect and consequence of these data centers, as you said. But not because of “theft” of freely available code.
Speaking as a software engineer, code sits in a weird spot in terms of copyright. The exact code as written can be protected by copyright. But the mechanics of it cannot. Furthermore, code that performs a task that is so generic or even necessary for the mechanism it serves also cannot be protected. I can’t copyright a for-loop that iterates through an array, for example. Nor can I copyright the use of libraries built and freely published by others. Boiler plate code and importance tools are never protected.
There are so many libraries of tools, and fully, freely available code as open source, so much raw code content and understanding in forums and textbooks that, honestly, the only real protection any code has is the actual source code as written for commercial products. And you simply do not need those examples for training. And that is if you can even get direct access to those things. They’re not exposed to the public by design.
I would imagine that little, if any, actually copywritten code was ever used in training LLMs. That isn’t to say that there isn’t an element of use without credit to sources and individuals. But really that problem existed well before LLMs and, again, is morally grey when it comes to matters of mechanics.
Code is a unique beast. It is essentially mechanical. It works or it doesn’t. It is a quantitative measure, not a qualitative one like music, art, film, etc. You can train LLMs not just on code examples, but on concrete outcomes, pass-fail requirement conditions. And it is made of a finite set of operations, like math. It is only in its patterns of these operations that actual meaning and work is derived. LLMs can find such patterns iteratively without copying someone else’s work.
But even for code it has used, to me, coding has always felt collaborative. How many thousands of memes have been made about programmers googling everything in their work. It’s true. Coding has always been community-driven and open-source by default, at least in my academic and professional life, and so training LLMs on this data also feels less offensive to me. And I say that as an engineer who both uses Claude as a tool in my work now, and one who is likely to be laid off in the next year, in part because of this. But I blame corporate greed and lack of integrity for that, not the fact that this tool exists. I have other problems with AI coders, and AI in general, not the least of which is just about every aspect and consequence of these data centers, as you said. But not because of “theft” of freely available code.