As the WSJ points out, until AI can learn on the fly as our brains do, it will never be truly intelligent. One avenue to teaching AI to act like the brain is to study the brain itself which the Defense Advanced Research Projects Agency is doing by developing brain-computer interfaces—devices that sit directly in or on the brain and record cell activity.
That’s what we want our brain-computer interfaces to accomplish. The goal is for the software to work in concert with the brain and adapt as quickly as the brain does. To achieve this, we’re using reinforcement learning, a process by which we, as humans, evaluate the outcomes of our actions based on feedback both tangible (some physical reward) and intangible (a sense of accomplishment). Our brains use this knowledge to guide us through life, and a simple version has been implemented in AI. It was through reinforcement learning that a computer taught itself to master the Atari game “Breakout.” By reviewing its actions, it adjusted its performance to accomplish its preprogrammed goal: achieve the highest score possible.