AFAIK in general usage one popular argument is that genral LLM outputs only correspond a small percentage of infringing data due to dilution from their massive datasets (wish i could find the article this was from). A model can produce infringing content but in general its output likely doesnt infringe (or so the argument goes) so I think the current standard is verifying output is not infringing over copyright controls over all LLM outputs (aka the whole “you’re responsible for your code” thing)
This doesnt change the fact a non-negligible portion of their dataset was obtained illegally however…
AFAIK in general usage one popular argument is that genral LLM outputs only correspond a small percentage of infringing data due to dilution from their massive datasets (wish i could find the article this was from). A model can produce infringing content but in general its output likely doesnt infringe (or so the argument goes) so I think the current standard is verifying output is not infringing over copyright controls over all LLM outputs (aka the whole “you’re responsible for your code” thing)
This doesnt change the fact a non-negligible portion of their dataset was obtained illegally however…