This kind of experiment will be hard to do with the HBP’s bottom-up architecture. Even if that simulation shows properties like intelligence, it will be difficult to understand where those came from. It won’t be a simple matter of tweaking one part of the simulation and seeing what happens. If you are trying to understand the brain and you do a really good simulation, the problem is that you end up with... the brain. And the brain is very complicated.
Besides, Izhikevich points out that technology is quickly outpacing many of the abilities that our brains are good at. “I can do arithmetic better on a calculator. A computer can play chess better than you,” he says. By the time a brain simulation is sophisticated enough to reproduce brain’s full repertoire of behaviour, other technologies will be able to do the same things faster and better, and “the problem won’t be interesting anymore,” says Izhikevich.
So, simulating a brain isn’t a goal in itself. It’s an end to some means. It’s a way of organising tools, experts, and data. “Walking the path is the most important part,” says Izhikevich.