The main argument behind the article is that only Big AI can afford to pay for licensed materials to train their AI, so this will hurt the small developers.
Does small/indie AI even exist? I was under the impression that it requires massive amounts of processing power to even run these AI.
It’s possible to run small AIs on gaming PCs. For Stable Diffusion and small LLMs (7, maybe 13B), a GPU with 4GB (or even 2GB?) VRAM is sufficient. A high-end gaming PC can also be used to modify them (ie make LoRas, etc.). Cloud computing is quite affordable, too.
Stable Diffusion, which had such an impact, reportedly cost only 600k USD to train. It should be possible to make a new one for a fraction of that today. Training MPT-7B cost MosaicML reportedly 200k USD. Far from hobbyist money, but not big business, either.
I think a big picture view makes the problem clearer.
Licensing material means that you must pay the owner of some intellectual property. If we expand copyright to require licensing for AI training, then that means that the owners can demand more money for no additional work.
Where does the wealth come from that flows to the owners? It comes from the people who work. There is nowhere else it could possibly come from.
That has some implications.
Research and development progress slower because, not only do we have to work on improving things, but also to pay off property owners who contribute nothing. If you zoom in from the big picture view, you find that this is where small devs and open source suffer. They have to pay or create their own, new datasets; extra work for no extra benefit.
It also means that inequality increases. The extra cash flow means that more income goes to certain property owners.
