Google Created an AI That Can Learn Almost as Fast as a Human

Deep Learning, Fast

Deep learning machines have been generating incredible amounts of buzz in recent months. Their extensive abilities can allow them to play video games, recognize faces, and, most importantly, learn. However, these systems learn 10 times more slowly than humans, which has allowed us to keep the creeping fears of a complete takeover at bay. Now, Google has developed an AI that is capable of learning almost as quickly as a human being.

Claims of this advancement in speed come from Google’s DeepMind subsidiary in London. They say that not only can their machine assimilate and act on new experiences much more quickly than previous AI models, it will soon reach human-level speeds.

If you’re unfamiliar with how works, it uses layers of to locate trends or patterns in data. If one layer identifies a pattern, that information will be sent to the next layer. This process continues until all the information is collected.

Systems can be taught to learn differently depending on many different variables, such as the strength of the connection between layers. Significant changes in one layer can dramatically change how information is transmitted in other layers, or how it is “learned.” Deep neural networks have many layers, so when changes are present, the process of learning can take an incredibly long time.

However, Alexander Pritzel, one of the researchers at Google DeepMind, and his colleagues seem to have figured out a way around this issue. They call it “neural episodic control.”

“Neural episodic control demonstrates dramatic improvements on the speed of learning for a wide range of environments,” the team told MIT Technology Review. “Critically, our agent is able to rapidly latch onto highly successful strategies as soon as they are experienced, instead of waiting for many steps of optimization.” Their method mimics the processes of learning that occur in human and animal brains, replicating what happens first in the prefrontal cortex and then, as a backup, in the hippocampus.

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