I think that in a few decades after we've had a lot more experience with various NN-based AIs, someone will come up with a more general quantification of "intelligence" that can integrate all these approaches into some vaguely orderable classes. After all a genetic algorithm seems clearly smarter (in some ways) than a rock but also it's clearly not as smart (in some way) as a dog. In that sense you could also say a physical lock is smarter than a rock (in that it processes a little bit of information) but not as smart as a human because it cannot learn.

Similar to how we have things like NP-hard > NP > (maybe) P, you could have a classification based on how many (types of) information can be processed or something like that. Maybe a similar but separate scale for learning capacity?