It's definitely true (that "the discover ran contrary to traditional assumptions"), and they give supporting evidence for this in the article. The history of AI bears this out quite explicitly.
Also, the decision tree for chess might be intractable to exhaustively search, but a "dumb search" is exactly how it's done, and it is currently vastly more powerful than any competing method. And you really can't just jump from chess to face recognition and NLP -- they are completely different problems. To wit, chess has perfect information; the entire state of the game is known at all times, and the representation is clearly defined and compact, where none of this is true for sensory tasks. This means the range of techniques available to solve each type problem are completely disparate, and tat there is almost nothing that you can take from a chess program and apply to "lower level" AI tasks.
Also, the decision tree for chess might be intractable to exhaustively search, but a "dumb search" is exactly how it's done, and it is currently vastly more powerful than any competing method. And you really can't just jump from chess to face recognition and NLP -- they are completely different problems. To wit, chess has perfect information; the entire state of the game is known at all times, and the representation is clearly defined and compact, where none of this is true for sensory tasks. This means the range of techniques available to solve each type problem are completely disparate, and tat there is almost nothing that you can take from a chess program and apply to "lower level" AI tasks.