[Dilettante_]

We would of course need to specify the behaviors to test for. The more precisely we specify these behaviors, the more complexly our end product would be able to behave. We might invent a formal language for writing down these behaviors, and some people might be better at thinking about what kind of tests would need to be written to coax a certain type of end result out of the machine.

But that's future music, forgive a young man for letting his imagination run wild! ;)

[asdff]

If we consider other fields such as biology, behaviors of interest are specified but I'm not sure a formal language is currently being used per say. Data are evaluated on dimensional terms that could be either quantitative or qualitative. meta analysis of some sort might be used to reduce dimensionality to some degree but that usually happens owing to lack of power for higher resolution models.

One big advantage of this future random walk paradigm is you would not be bound by the real world constraints of sample collection of biological data. datasets could be made arbitrarily large and cost to do so will follow an inverse relationship with compute gains.