But if on some absolute scale you say that AlphaZero is a design / search hybrid, then presumably you should also say the OpenAI Five is a design / search hybrid, since it uses PPO at the outer layer, which is a designed algorithm. This seems wrong.
I think I’m willing to bite that bullet; like, as far as we know the only stuff that’s “search all the way up” is biological evolution.
But ‘hybrid’ seems a little strange; like, I think design normally has search as a subcomponent (in imaginary space, at least, and I think often also search through reality), and so in some sense any design that isn’t a fully formed vision from God is a design/search hybrid. (If my networks use RELU activations ‘by design’, isn’t that really by the search process of the ML community as a whole? And yet it’s still useful to distinguish networks which determine what nonlinearity to use from local data, which which networks have it determined for them by an external process, which potentially has a story for why that’s the right thing to do.)
Total horse takeover seems relevant as another way to think about intervening to ‘control’ things at varying levels of abstraction.
[The core thing about design that seems important and relevant here is that there’s a “story for why the design will work”, whereas search is more of an observational fact of what was out there when you looked. It seems like it might be easier to build a ‘safe design’ out of smaller sub-designs, whereas trying to search for a safe algorithm using search runs into all the anthropic problems of empiricism.]
I think I’m willing to bite that bullet; like, as far as we know the only stuff that’s “search all the way up” is biological evolution.
But ‘hybrid’ seems a little strange; like, I think design normally has search as a subcomponent (in imaginary space, at least, and I think often also search through reality), and so in some sense any design that isn’t a fully formed vision from God is a design/search hybrid. (If my networks use RELU activations ‘by design’, isn’t that really by the search process of the ML community as a whole? And yet it’s still useful to distinguish networks which determine what nonlinearity to use from local data, which which networks have it determined for them by an external process, which potentially has a story for why that’s the right thing to do.)
Total horse takeover seems relevant as another way to think about intervening to ‘control’ things at varying levels of abstraction.
[The core thing about design that seems important and relevant here is that there’s a “story for why the design will work”, whereas search is more of an observational fact of what was out there when you looked. It seems like it might be easier to build a ‘safe design’ out of smaller sub-designs, whereas trying to search for a safe algorithm using search runs into all the anthropic problems of empiricism.]