If you want to see what cortical columns actually look loke, see http://brainmaps.org In some of these images you can clearly see what appear to be neurons stacked on top of each other perpendicular to the cortical plane. However, unlike the architecture of a computer there are no clear divisions between functional units.
On the functional homogeneity or otherwise it's probably too early to say, but there do appear to be substantial similarities between tasks such as visual and auditory processing. Both of these involve a kind of spatio-temporal analysis of the incoming data stream. The cortex at least appears fairly homogeneous, but it's not until we're able to get detailed structural models for entire brains that we'll be able to see the fine wiring and make statements such as "vision involves different circuitry from speech". On 30/11/2007, Dennis Gorelik <[EMAIL PROTECTED]> wrote: > Matt, > > > > And some of the Blue Brain research suggests it is even worse. A mouse > > cortical column of 10^5 neurons is about 10% connected, > > What does mean 10% connected? > How many connections does average mouse neuron have? > 10000? > > > but the neurons are arranged such that connections can be formed > > between any pair of neurons. Extending this idea to the human brain, with > > 10^6 columns of 10^5 neurons > > each, each column should be modeled as a 10^5 by 10^5 sparse matrix, > > Only poor design would require "10^5 by 10^5 matrix" if every neuron > has to connect only to 10000 other neurons. > > One pointer to 2^17 (131072) address space requires 17 bits. > 10000 connections require 170000 bits. > If we want to put 4 bit weighting scale on every connection, then it > would be 85000 bytes. > 85000 * 10000 neurons = 8.5 * 10^9 bytes = 8.5 GB (hard disks of that > size were available on PCs ~10 years ago). > > > But in fact mouse's brain does way more than AI has to do. > For example, mouse has strong image and sound recognition ability. > AGI doesn't require that. > Mouse has to manage its muscles in a very high pace. > AGI doesn't need that. > All these unnecessary features consume lion's share of mouse brain. > Mouse must function in way more stressful environment, than AGI must. > That again makes mouse brain bigger than AGI has to be. > > > > Perhaps there are ways to optimize neural networks by taking advantage of > > the > > reliability of digital hardware, but over the last few decades researchers > > have not found any. > > Researchers have not found appropriate intelligent algorithms. That > doesn't mean that hardware is not sufficient. > > > For narrow AI applications, we can usually find better algorithms than > > neural > > networks, for example, arithmetic, deductive logic, or playing chess. But > > none of these other algorithms are so broadly applicable to so many > > different > > domains such as language, speech, vision, robotics, etc. > > Do you imply that intelligent algorithm must be universal across > "language, speech, vision, robotics, etc"? > In humans it's just not the case. > Different algorithms are responsible for vision, speech, language, > body control etc. > > > > > ----- > This list is sponsored by AGIRI: http://www.agiri.org/email > To unsubscribe or change your options, please go to: > http://v2.listbox.com/member/?&; > ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=8660244&id_secret=70674002-45ee58
