In Scientific American's "Too Hard for Science" feature, SFI External Professor Luis Bettencourt describes the difficulty, and promise, of simulating the human brain.
"If we ask the best computer algorithms to look at natural objects or images to identify them, they approach a success rate of 70 to 90 percent. That may sound good, but if you're crossing streets and you only have a 90 percent chance of identifying a car, you won't live long," he says.
"The more knowledge we have from neuroscience on how the brain works, the more we can create systems-level models, test them on computers, tinker on them and test them again, for a continuous loop of experimentation and progress," Bettencourt says. "That will make a big difference."
Read the complete Scientific American article (May 10, 2011)