robinson@sagpd1.UUCP (Rob Robinson) (02/18/89)
Suppose the brain actually has 10 billion neurons, each having an average of 1000 connections with other neurons. Also assume that the average firing rate is 100/second. 10^10 * 10^3 * 10^2 = 10^15 ------- Now imagine a system having 1 million neural type units, each having only 10 connections to neighboring units. Using available technology, assume a firing speed of say 100 Mhz. 10^6 * 10 * 10^8 = 10^15 ------- Would the two systems be "equivalent" as far as processing power is concerned? If so, then using current VLSI methods the proposed system might look like a 100 x 100 x 100 matrix of 1mm cubed units. In other words, it might be constructed in a 4 inch cube!
Krulwich-Bruce@cs.yale.edu (Bruce Krulwich) (02/21/89)
In article <316@sagpd1.UUCP>, robinson@sagpd1 (Rob Robinson) writes: >Suppose the brain actually has 10 billion neurons, each having >an average of 1000 connections with other neurons. Also assume >that the average firing rate is 100/second. > >10^10 * 10^3 * 10^2 = 10^15 > ------- >Now imagine a system having 1 million neural type units, each having >only 10 connections to neighboring units. Using available technology, >assume a firing speed of say 100 Mhz. > >10^6 * 10 * 10^8 = 10^15 > ------- >Would the two systems be "equivalent" as far as processing power is >concerned? Depends what you mean by "processing power." What you're saying seems to be that the number of neuron firings (transmission across synapses) would be the same for the two. However, the problem is in the way the information in the net is used. The way most neural net models are set up, the amount of information it could process would drop by 4 orders of magnitude (the number of neurons) and the amount of information it could remember would drop by a 6 orders of magnitude (the number of synapses). Even if you quibble with my descriptions of the uses of neurons and synapses, it is clear that the information content would decrease by many orders of magnitude. Bruce Krulwich krulwich@cs.yale.edu