Building Machines That Learn and Think Like People

Understand

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people.

• Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects.
• Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways.
• We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it.