Obviously, many of the challenges highlighted deal with energy and pollution issues that we've created for ourselves. And of course many also involve education, health, and improving society. But one stands out - reverse engineering the human brain.

Basically that means "understanding better how the brain works." But the semantics are critical: Artificial Intelligence researchers have spent so much time trying to mimic how the brain seems to work without understanding how the brain actually works.

Being able to recreate the brain accurately would of course help us to fight dysfunctions of the brain such as Alzheimer's, Parkinson's, and Tourette's. But what gets AI folks excited are the cognitive implications. Right now computers can understand information from only a binary approach. A human being views and learns fluidly - we see an object and have multiple interpretations of that object based on our experience. We can see a cow and think "Cow," naturally. A computer could do the same because it might be programmed to look at objects in the world and say either "Cow" or "Not Cow." But a human being can also see a cartoon of a cow, a black and white pattern, a bottle of milk, or a cowbell, and all of those objects can make us think "Cow."

This is an example of the human neuron's gray area. According to the committee "if engineers could replicate neurons’ ability to assume various levels of excitation," we could have stronger machines, and human-machine interactions.