The subtle difference between simulating brains and number of cells

By Massimiliano Versace | November 19, 2009

091019122647-largeIEEE Spectrum has published an interesting article titled "IBM Unveils a New Brain Simulator: A big step forward in a project that aims for thinking chips". The post describes IBM’s Almaden Research Center latest simulation effort announced at the Supercomputing Conference (SC09), where they unveiled that "that they have created the largest brain simulation to date on a supercomputer. The number of neurons and synapses in the simulation exceed those in a cat’s brain; previous simulations have reached only the level of mouse and rat brains." There is a subtle, but important, difference between simulating the "number of neurons and synapses of a cat’s brain", and "simulating the cat's brain". To put it simply, it's like "simulating a car" by putting together the same number of screws, pieces of metal, plastic, rubber, etc that a car has. There is no guarantee, actually there is strong argument to the contrary, that all those pieces will work as a car. Another approach, as Modha himself notices, is to ”to demonstrate brainlike visual perception, decision [making], planning, and navigation in virtual environments”. In order to achieve these tasks, you do not need a whole brain (and the nuclear power plant that goes with the simulator). This is fortunate, and very detailed models of brain areas that ACTUALLY DO SOMETHING exist, and continue to be produced, at a very high rate. Bottom line: I would love to see an article that talks about the "next step", namely having the simulated brain actually do something, rather than simulating an even larger, and more expensive, bag of neurons whose "intelligence", or ability to do anything adaptive, is inferior to the brain of an insect.

About Massimiliano Versace

Massimiliano Versace is co-founder and CEO of Neurala Inc. and founding Director of the Boston University Neuromorphics Lab. He is a pioneer in researching and bringing to market large scale, deep learning neural models that allow robots to interact and learn real-time in complex environments. He has authored approximately forty among journal articles, book chapters, and conference papers, holds several patents, and has been an invited speaker at dozens of academic and business meetings, research and national labs, and companies, including NASA, Los Alamos National Laboratory, Air Force Research Labs, Hewlett-Packard, iRobot, Qualcomm, Ericsson, BAE Systems, Mitsubishi, and Accenture, among others. His work has been featured in over thirty articles, news programs, and documentaries, including IEEE Spectrum, New Scientist, Geek Magazine, CNN, MSNBC and others. Massimiliano is a Fulbright scholar and holds two Ph.Ds: Experimental Psychology, University of Trieste, Italy; Cognitive and Neural Systems, Boston University, USA. He obtained his BS from University of Trieste, Italy.

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