The Pentagon’s outside-the-box research group thinks pushing AI forward requires better understanding of how our own brains work.

Background: DARPA has developed human-computer interfaces that let paralyzed patients learn to move robotic limbs. But there’s a problem: the brain never stops learning and experimenting with new ways to carry out tasks, and the software that translates brain signals into commands for robotic limbs can’t keep up. In an op-ed in the Wall Street Journal, a director at DARPA says AI could help.

How to do it: DARPA wants to use reinforcement learning, a process whereby machines learn by trial and error, to improve their software. Reinforcement learning has proved great at playing video games, but everyday movements like grabbing a cup are much more complicated. To create AI that can accomplish DARPA’s goals, we will need more insight into how the brain accomplishes these tasks and others so effortlessly.

But: At the moment this kind of tech is a dream, not a reality. Tech companies are spending billions on AI, but for the most part interfacing with the brain isn’t on their agenda. And we still don’t understand much about how the brain achieves its incredible ability to keep learning and adapting. So yeah, there’s a long way to go before AI-powered robotic limbs are commonplace.