I honestly think that the most extreme take that "any output of an LLM falls under all the copyright of all its training data" is not really defensible, especially when contrasted with human learning, and would be curious to hear conflicting opinions.

My view is that copyright in general is a pretty abstract and artificial concept; thus corresponding regulation needs to justifiy itself by being useful, i.e. encouraging and rewarding content creation.

/sidenote: Copyright as-is barely holds up there; I would argue that nobody (not even old established companies) is significantly encouraged or incentivised by potential revenue more than 20 years in the future (much less current copyright durations). The system also leads to bad ressource allocation, with almost all the rewards ending up at a small handful of most successful producers-- this effectively externalizes large portions of the cost of "raising" artists.

I view AI overlap under the same lense-- if current copyright rules would lead to undesirable outcomes (by making all AI training or use illegal/infeasible) then law/interpretation simply has to be changed.

Anyone can very easily avoid training on GPL code. Yes, the model might be not be as strong as one that is trained that way and released under terms of the GPL, but to me that sounds like quite a good outcome if the best models are open source/open weight.

Its all about whose outcomes are optimized.

Of course, the law generally favors consideration of the outcomes for the massive corporations donating hundreds of millions of dollars to legislature campaigns.