Technology

This process is akin to how humans learn by reading widely and absorbing styles and techniques, rather than memorizing and reproducing exact passages.

Machine learning algorithms are not people and are not ingesting these works the same way a person does. This argument is brought up all the time and just doesn't ring true. You're defending the unethical use of copyrighted works by a giant corporation with a metaphor that doesn't have any bearing on reality; in an age where artists are already shamefully undervalued. Creating art is a human process with the express intent of it being enjoyed by other humans. Having an algorithm do it is removing the most important part of art; the humanity.

The issue here is that the cheese gets consumed for the sandwitch. Knowledge does not lost when it gets passed. Cheese does.

There is an easy answer to this, but it's not being pursued by AI companies because it'll make them less money, albeit totally ethically.

Make all LLM models free to use, regardless of sophistication, and be collaborative with sharing the algorithms. They don't have to be open to everyone, but they can look at requests and grant them on merit without charging for it.

So how do they make money? How goes Google search make money? Advertisements. If you have a good, free product, advertisement space will follow. If it's impossible to make an AI product while also properly compensating people for training material, then don't make it a sold product. Use copyright training material freely to offer a free product with no premiums.

As someone who researched AI pre-GPT to enhance human creativity and aid in creative workflows, it's sad for me to see the direction it's been marketed, but not surprised. I'm personally excited by the tech because I personally see a really positive place for it where the data usage is arguably justified, but we either need to break through the current applications of it which seems more aimed at stock prices and wow-factoring the public instead of using them for what they're best at.

The whole exciting part of these was that it could convert unstructured inputs into natural language and structured outputs. Translation tasks (broad definition of translation), extracting key data points in unstructured data, language tasks. It's outstanding for the NLP tasks we struggled with previously, and these tasks are highly transformative or any inputs, it purely relies on structural patterns. I think few people would argue NLP tasks are infringing on the copyright owner.

But I can at least see how moving the direction toward (particularly with MoE approaches) using Q&A data to support generating Q&A outputs, media data to support generating media outputs, using code data to support generating code, this moves toward the territory of affecting sales and using someone's IP to compete against them. From a technical perspective, I understand how LLMs are not really copying, but the way they are marketed and tuned seems to be more and more intended to use people's data to compete against them, which is dubious at best.

except that it can, and regularly does, regurgitate copyrighted works verbatim.

No but you would definitely design a car based on other designs made before.

Maybe if OpenAI didn't suddenly decide not to be open when they got in bed with Micro$oft, they could just make it a community effort. I own a copyrighted work that the AI hasn't been feed yet, so I loan it as training and you do the same. They could have made it an open initiative. Missed opportunity from a greedy company. Push the boundaries of technology, and we can all reap the rewards.

I rather think the point is being missed here. Copyright is already causing huge issues, such as the troubles faced by the internet archive, and the fact academics get nothing from their work.

Surely the argument here is that copyright law needs to change, as it acts as a barrier to education and human expression. Not, however, just for AI, but as a whole.

Copyright law needs to move with the times, as all laws do.