• So will we be using the internet for video on-demand, will that be the killer app? Will millions of people wide watch this video right when they want to watch it?

    所以我们使用互联网实现随需视频么,那成为杀手应用么?有数百万人,就在他们想看的时候看到视频么?

    麻省理工公开课 - 媒体、教育、市场课程节选

  • We have seen log, linear, quadratic, and exponential.

    平方的和指数复杂度的方法,再说一遍,可能有些常量。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • This chart, very boring and uninteresting but useful to say there are very well defined rules as to when you're writing code, what operators, like what syntax should get evaluated first.

    这个图表,看起来很烦,很无趣,但是它很有用,有非常明确的规定,譬如,当你写代码时,就涉及操作符的优先

    哈佛公开课 - 计算机科学课程节选

  • And if you have conjunct motion, that makes it easier.

    如果用进,就更容易

    耶鲁公开课 - 聆听音乐课程节选

  • If I'm running a linear algorithm, it'll take one microsecond to complete.

    算法在1微秒内完成,如果是一个平方的方法。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • It is certainly possible, for example, that a quadratic algorithm could run faster than a linear algorithm. It depends on what the input is, it depends on, you know, what the particular cases are. So it is not the case that, on every input, a linear algorithm is always going to be better than a quadratic algorithm.

    一个二次平方复杂度的算法,当然也是可能跑的比线性复杂度算法快的,这取决于,你知道的,输入以及特定的案例,因此并不是对于每个输入,线性复杂度就一定,比二次平方复杂度的算法的表现要好,只是通常来说是这样的。

    麻省理工公开课 - 计算机科学及编程导论课程节选

  • If I'm running at nanosecond speed, 1000 n, the size of the problem, whatever it is, is 1000, and I've got a log algorithm, it takes 10 nanoseconds to complete.

    如果这个问题的规模,也就是n,是,如果这个问题是对数的,这将占据10纳秒的时间,你一眨眼的时间。

    麻省理工公开课 - 计算机科学及编程导论课程节选

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