tailieunhanh - Báo cáo khoa học: "Learning and Translating by Machines"

To translate well, a machine must be furnished with rules that relate meaning to words. These rules may be expressed in terms of probabilities, if they cannot be expressed precisely. Less useful are descriptive rules, particularly those using concepts of psychology. | Mechanical Translation August 1963 Learning and Translating by Machines by John F. Tinker Research Laboratories Eastman Kodak Company Rochester New York To translate well a machine must be furnished with rules that relate meaning to words. These rules may be expressed in terms of probabilities if they cannot be expressed precisely. Less useful are descriptive rules particularly those using concepts of psychology. That these rules can be satisfactorily formulated is strongly suggested by the fact that a child of four can adequately manipulate language. To learn a machine must be furnished with rules besides those for performance for critically evaluating its performance and for modifying the performance rules. Learning is the process of successfully modifying the performance. Creativity in humans is an example of this learning process. A human cannot perform better than his teacher if his rules of critical evaluation are identical with his teacher s. If he is to perform creatively he must be able to modify all three elements of learning performance critique improvement rules not merely the first element. To teach a student to be creative the teacher must specify the rules heuristically not precisely. This is the same problem as programming a machine to learn. That the former can be done suggests that the latter is possible. A good guide to the maximum amount to bet is the product of the probability of winning and the amount won. Spending on research is similar to wagering and a sensible maximum to a research budget is the product of the probability of successful outcome during the budget time and the expected profit. If the probability of outcome is zero the research budget should be zero regardless of the profit. Learning and translating by machine it has been suggested are fields in which the probability of successful outcome is zero. But is this so A computer can do anything that you can explain carefully and patiently to a child of four. A child of .