One Marcus identifies is building a more flexible technology. Today’s algorithms work only on a narrow range of problems. The goal must be extremely well-defined and unchanging, and huge amounts of data must be available for training. Examples include translating text, recognizing speech and identifying faces in a photo. The algorithm has one job, and researchers supply it with the masses of perfectly organized data required to learn how to do it.
Humans regularly perform many tasks that are not so clearly delineated — where the nature of an answer, or what information might be needed to approach it, is not given. Tangle up some rope in a bicycle wheel, and any five-year-old can easily work out how to extract it — not because he has trained on thousands of wheels, but because he can understand the spatial relationships. People have an impressive ability to solve problems and gain insight using almost no data at all, by using abstract reasoning.
