Artificial Intelligence: Teaching Machines to Think Like People

Perspectives from Leading Practitioners in AI and Neuroscience

About this report

Artificial intelligence is beginning to take more than a superficial inspiration from neuroscience, allowing development in the field to speed up by tapping into advances made in another. That’s led to researchers taking cues from the brain in areas like memory, the hierarchical organization of thoughts, and the role of attention in vision, to build AI systems. At the same time, neuroscientists are taking note of the increasingly powerful analytical techniques made possible by AI and are beginning to use it themselves to further their own understanding of the brain. These intertwined phenomenons will speed the development of both AI and neuroscience, letting insights from one be rapidly translated into the other.

Based on a series of interviews with experts at the intersection of AI and neuro-/cognitive-science, this report will help readers understand how current neuroscience work will rapidly translate into AI tech, which will broaden capabilities and potential application areas of AI systems.

Jack Clark

About the author

Jack Clark is a writer and communicator focused on artificial intelligence. He works at OpenAI and previously covered AI for Bloomberg and BusinessWeek, and distributed systems for The Register. He writes a weekly newsletter on developments in AI, published at jack-clark.net/import-ai