a user decides they are curious to see how much scientific information the model can compile, and so instructs it to query all information it can find in the field of physics. Initially the model stops after the first 5-10 facts, but the user eventually manages to get the model to keep looking for more information in a loop. The user leaves the model running for several weeks to see what it will come up with.
As a result of this loop, the information-acquiring drive becomes an ov
Objection: If one user can do this sort of thing, then surely for a system with a hundred million users there’s going to be ten thousand different versions of this sort of thing happening simultaneously.
Objection: It sounds like the model as a whole is acquiring substantially different drives/behaviors on the basis of its interactions with just this one user? Surely it would instead be averaged out over all its interactions with hundreds of millions of users?
It sounds like I’m misunderstanding the scenario somehow.
Objection: If one user can do this sort of thing, then surely for a system with a hundred million users there’s going to be ten thousand different versions of this sort of thing happening simultaneously.
Objection: It sounds like the model as a whole is acquiring substantially different drives/behaviors on the basis of its interactions with just this one user? Surely it would instead be averaged out over all its interactions with hundreds of millions of users?
It sounds like I’m misunderstanding the scenario somehow.