When a very young child looks at a picture, she can identify simple elements: "cat," "book," "chair." Now, computers are getting smart enough to do that too. What's next? In a thrilling talk, computer vision expert Fei-Fei Li describes the state of the art  -- including the database of 15 million photos her team built to "teach" a computer to understand pictures -- and the key insights yet to come.

How we're teaching computers to understand pictures

Computers are rapidly learning to interpret images, a feat that took nature over 500 million years to evolve in the human brain. By building a database of 15 million labeled photos, researchers have allowed algorithms to make sense of the visual world, much like a child learning from experience. Today, machines can identify objects in photos and even generate human-like sentences about what they see. This progress promises smarter tools and new forms of human–machine collaboration, but true visual understanding is still unfolding.