itd be fantastic if it turns out that all we need to do is take current algorithms and run them bigger but my gut feeling is that we still dont quite have the right algorithm yet andrew ng told the new york times this approach of modelling computers on the human brain is gaining increasing popularity and some modicum of success the seat of thinking language motor functions spatial and sensory perception in the brain lies in the neocortex the uppermost layer of the brain consisting of grey cells it is found only in mammals and the biggest neocortex in relation to the rest of the brain is found in humans the neocortex is made of six layers and it is thought that this is a hierarchical system neurons start reacting at the lowest most inside layer and each succeeding layer refines the activity to produce the final thought one of the leading figures in the field of building neural network based machines is geoffery hinton a professor at the university of toronto who spends half his time at google he has developed simple models of virtual neurons connected to each other and layered like the human neocortex of course neuroscience itself is still a bit like physics before newton as bruno olshausen director of the redwood center for theoretical neuroscience at the university of californiaberkeley put it in the journal scientific american scientists think that they have understood only about 15 of how the visual cortex works and that is just one of the functions of the brain but as the functioning of the brain is revealed spurred by advances in imaging technology the feedback loop with computer scientists will expand rapidly and so will the prospect of thinking machines