Path: utzoo!utgpu!news-server.csri.toronto.edu!rpi!zaphod.mps.ohio-state.edu!wuarchive!mit-eddie!media-lab!minsky From: minsky@media-lab.MEDIA.MIT.EDU (Marvin Minsky) Newsgroups: comp.ai.neural-nets Subject: Re: Gibson's escape from computational impossibility. Message-ID: <5541@media-lab.MEDIA.MIT.EDU> Date: 23 Mar 91 16:59:07 GMT References: Reply-To: minsky@media-lab.media.mit.edu (Marvin Minsky) Distribution: comp.ai.neural-nets comp.ai.philosophy Organization: MIT Media Lab, Cambridge MA Lines: 24 In article pja@cis.ohio-state.edu writes: >In article bradski@park.bu.edu (Gary Bradski) writes: > If the [Ecological View of J. J. Gibson] is correct, then the nervous system > is relieved of an immense computational burden. AND, the types of machines > >Wait, aren't the computations you're talking about really the same hard >computations that everyone is trying to do? Why is the nervous system relieved >of any computational burdens simply by recognizing that the information is >apparent in the "ambient array"? How are you planning to identify the >invarients in the environement if you're not going to concentrate on >"computation" just "extracting and tuning"? > -pete angeline That sounds right -- and may be supported by considering how large are the brain regions involved with wisual processing; substantial portions of the posterior brain for sensory processing, and substantial portions of the anterior brain for oculomotor control -- and who knows how much more in between. Clearly the computational burden is very large. The question could be put the other way. Is the brain computing those invariants by brute force, because it has not evolved better ways? We won't know the answer, of course, until we have better theories of what computations are actually required for human vision -- and then, of bounding the requisite computation complexity.