I agree that Jaynes is using the robot as a literary device to get a point across.
If I understood you correctly it seems you’re sneaking an additional claim that a Bayesian AI is theoretically impossible due to computational concerns. That should be discussed separately, but the obvious counterargument is that while, say, complete inference in Bayes Nets has been proved intractable, approximate inference does well on good-size problems, and approximate does not mean it’s not Bayesian.
Sorry, I never tried to imply that an AI built on the Bayesian principles is impossible or even a bad idea. (Probably, using Bayesian inference is a fundamentally good idea.)
I just tried to point out that easy looking principles don’t necessarily translate to practical implementations in a straightforward manner.
I agree that Jaynes is using the robot as a literary device to get a point across.
If I understood you correctly it seems you’re sneaking an additional claim that a Bayesian AI is theoretically impossible due to computational concerns. That should be discussed separately, but the obvious counterargument is that while, say, complete inference in Bayes Nets has been proved intractable, approximate inference does well on good-size problems, and approximate does not mean it’s not Bayesian.
Sorry, I never tried to imply that an AI built on the Bayesian principles is impossible or even a bad idea. (Probably, using Bayesian inference is a fundamentally good idea.)
I just tried to point out that easy looking principles don’t necessarily translate to practical implementations in a straightforward manner.