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AlphaZero--an Updated Model of AI Soon after Garry Kasparov, the former world chess champion, lost h...
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AlphaZero--an Updated Model of AI
Soon after Garry Kasparov, the former world chess champion, lost his rematch against IBM’s Deep Blue in 1997, the short window of human-machine chess competition slammed shut forever. Unlike humans, machines keep getting faster, and today a smartphone chess app can be stronger than Deep Blue. However, as people see with the new AlphaZero system, machine dominance has not ended the historical role of chess as a laboratory of cognition.
Much as airplanes don’t flap their wings like birds, machines don’t produce chess moves like humans do. Based on a generic algorithm (算法), AlphaZero incorporates deep learning and other AI techniques like Monte Carlo tree search to play against itself to develop its own chess knowledge. Unlike the traditional program Stockfish, which employs many preset evaluation functions as well as opening and endgame moves, AlphaZero starts out knowing only the rules of chess, with no preset human strategies. In a few hours, it plays more games against itself than have been recorded in human chess history. It teaches itself the best way to play, reevaluating the relative values of the pieces. It quickly becomes strong enough to win 28, draw 72, and lose none in a victory over Stockfish. Since AlphaZero can program itself, this superior understanding allows it to outclass the world’s top traditional program despite calculating far fewer positions per second. It’s the typical example of the cliché, “work smarter, not harder”.
AlphaZero shows that machines can be the experts, not merely expert tools. Explainability is still an issue—it’s not going to put chess coaches out of business just yet. But the knowledge it produces is information humans can learn from. AlphaZero is surpassing humans in a profound and useful way, and researchers are working on transferring the knowledge acquired from AlphaZero to other fields.
Machine learning systems aren’t perfect. Even though great progresses have been achieved, AI algorithms are still struggling on open problems such as computer vision, natural language understanding... There will be cases where an AI will fail to detect exceptions to its rules. Therefore, as Kasparov writes, “We must work together to combine our strengths. I know better than most people what it’s like to compete against a machine. Instead of raging against them, it’s better if we’re all on the same side.”
Questions 1-5: Judge if the following statements agree with the information given in the passage.
Choose A for TRUE if the statements agree with it; choose B for FALSE if the statements don’t agree with it; choose C for NOT GIVEN if the information the statements carry is not mentioned anywhere in the passage.根据文章内容判断下列表述。如果表述与文章内容一致,选 A 项;表述与文章内容不一致,选 B 项;文章中未提及的信息,则选 C 项。
Questions 6-9: Choose the correct headings for Paragraphs 1-4 from the box. Note that there are two choices more than you need.请为文章的四段匹配小标题,从A—F中选择。(提示:6个选项中有2项是多余的)
A. The proper attitude to AI
B. The history of AlphaZero
C. The limitations of machines
D. The influences of AlphaZero
E. The working theory of AlphaZero
F. The fast development of machines
1.Machine dominance plays an important role in cognition study.
2.AlphaZero knows opening and endgame moves before playing.
3.AlphaZero develops chess strategies by playing against itself.
4.Chess coaches have already been laid off throughout the world.
5.Sometimes artificial intelligence may not discover exceptions to its rules.
6.Paragraph 1
7.Paragraph 2
8.Paragraph 3
9.Paragraph 4
10.The author uses the underlined sentence in the last paragraph to ______.
A. argue for the advantages of AI over humans
B. inform readers of machine dominance in chess
C. advise people to work together to fight against AI
D. call on people to combine strengths with the machines
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