I don't think the result is as clear either as the "Moloch" commenter, nor you, seem to think.
I agree that the result is not a "Moloch trap": as you say, the new technology actually does de-fang Google Search and empowers many smaller people to be able to do things they would never otherwise have been able to do. The contrary ruling would certainly have been enjoyed by "copyright maximalists" like Disney extracting value from the public domain without giving anything back.
But there are more people affected than just greedy copyright maximalists. Individual artists who have spent years developing a distinctive style and making it popular are seeing their style copied ad-infinitum for free. Organizations like the NYT that invest money doing investigative journalism are having their results slurped up and regurgitated.
To your comment:
> If a person is allowed to read training material acquired legally, then so too must their LLM experiment be allowed to read it. The LLM reading it creates no new copies.
In the past, each copyrighted work seen might train a single BNN (biological neural network). Only a small percentage of BNNs would actually study such work to learn to emulate it; only a handful would achieve parity or exceed the quality of the work. Each BNN was expensive to employ, would only work for a certain number of hours per day, and a certain number of years before retiring.
Now a single ANN (artificial neural network) can study works to emulate them in a month or two. That ANN is far less expensive to employ than a BNN; can be deployed 24/7 indefinitely; and can be duplicated to as many GPUs as someone can get their hands on.
Currently legally, it may be that an ANN learning from an artist's work is the same as a BNN learning from an artist's work. But from a practical perspective, from the case of individual artists, it's clearly not the same.
Now maybe that's the inevitable price of progress; but 1) I don't think that's the inevitable conclusion, and 2) even if it is, we need to be honest about it.