> Here are a few thoughts I haven't formulated before:
> It seems clear enough to me that training AIs on copyrighted works is typically or commonly a fair use under existing law, because the AIs can and commonly do learn non-copyrightable elements and aspects of those works. It's very obvious from enormous numbers of examples that current AI systems are capable of learning much more abstract features of human culture (grammar, concepts, facts, cultural tropes, and many others).
I said it already in a previous discussion, I would be very careful with comparing ML with how humans learn. To me there are still a lot of examples that show that AIs don't understand prompts (see e.g. the discussions around the "horse riding astronaut" prompts för stable diffusion et al.) and it seems like they really are just doing sophisticated pattern matching. If that is what they do aren't they themselves covered by the licenses/ restrictions placed on the "patterns" they "choose" from?
I think any argument against generative AI should not hedge on there being a fundamental difference in how humans and generative models work.
I mean sure, maybe humans aren't "just" doing sophisticated pattern matching, but there are good reasons to suspect this is some part of what we are doing. (Even if its not implemented with back-prop).
e.g) consider the work of people like Anil Seth, who propose that our brain is basically a generative model of the world, which aims to minimize the likelihood of perceptual data. (see also: Karl Friston's free energy principle). What's up for debate is how it is structured, what priors are built in, what is the learning algorithm etc.
Anyway, for all their limitations, it seems clear that current artificial generative models can:
1. learn hierarchies of abstractions, which
2. explain the observed data in the fewest possible number of bits, and
3. generate new, novel data based on the patterns that have been learned
If you want to describe this as "just sophisticated pattern matching".. then sure I guess? But I think there's a clear qualitative difference between this and searching for code in a discrete database (which imo would not be okay).
The paper suggests that transformer work on a set of select, aggregate and element-wise operations. Which seems pretty close to the SQL statements i write from day to day.
AI copyright drama is my favorite gossip these days because it can’t be reconciled until we accept that intelligence is created and held by societies, not individuals. Recent AI is a new way to exercise that intelligence, but it presents a major conflict with capitalism.
Not a conflict with capitalism - it's another trajedy of the commons - the robber barons of old stole the owned commons land and started said 'capitalism'.
Capitalism is still very alive, and will continue to be. It's in conflict with the general welfare of the people...
I assume they meant “capitalism as it is currently implemented”. In any case, not like capitalism is suggested as being under threat - just that an economic model based on competitive markets will have a lot of issues with fairly allocating resources to all individuals, instead accumulating most of it to a few industry leaders.
Just about two-thirds of an octopus's neurons is found outside its central brain, distributed across its 8 arms. An octopus can be likened to a hive-mind of sorts.
> It seems clear enough to me that training AIs on copyrighted works is typically or commonly a fair use under existing law, because the AIs can and commonly do learn non-copyrightable elements and aspects of those works. It's very obvious from enormous numbers of examples that current AI systems are capable of learning much more abstract features of human culture (grammar, concepts, facts, cultural tropes, and many others).
I said it already in a previous discussion, I would be very careful with comparing ML with how humans learn. To me there are still a lot of examples that show that AIs don't understand prompts (see e.g. the discussions around the "horse riding astronaut" prompts för stable diffusion et al.) and it seems like they really are just doing sophisticated pattern matching. If that is what they do aren't they themselves covered by the licenses/ restrictions placed on the "patterns" they "choose" from?