Enlarging in his talk upon the favourite example of chess-playing, Alan claimed that
说到他最喜欢的机器对弈问题，图灵说：
It would probably be quite easy to find instruction tables which would enable the ace to win against an average player.
编写一份指令表使ACE战胜普通人类棋手也许并不难，
Indeed Shannon of Bell Telephone Laboratories tells me that he has won games playing by rule of thumb; the skill of his opponents is not stated.
贝尔实验室的香农告诉我，他已经用这样的方法战胜了人类，但他没说清楚，对手是个什么水平的人。
This was probably a misunderstanding.
实际上这可能是个误解。
Shannon had been thinking about mechanising chess-playing, since about 1945, by a minimax strategy requiring the 'backing up' of search trees—the same basic idea as Alan and Jack Good had formalised in 1941.
大约在1945年之后，香农确实在思考机器对弈问题，他的想法也是基于"最大值最小化"原理，对搜索树进行"回溯"，这与图灵和杰克·古德在1941年时的基本思想是一致的。
But he had not claimed to have produced a winning program.
但是香农并没有说，他已经做出了这样的对弈程序。
In any case, however, Alan would not consider such a victory very significant.
不管怎样，图灵继续说：这场胜利的结果本身并不重要，
What we want is a machine that can learn from experience.
重要的是机器的自动学习能力。
The possibility of letting the machine alter its own instructions provides the mechanism for this, but this of course does not get us very far.
机器可以改变自己的指令，这是一个基础性的机制，但我们仍然还有很长的路要走。