Because you don't know how much more time you've got-- You can make a guess based on statistics, but as we saw, there's wild unpredictability.

因为你不知道你剩下多少时间-,你可以根据数据进行猜测，但是我们都知道，不可预见性太难把握。

耶鲁公开课 - 死亡课程节选

You know ,why am I wasting time passing things around.

你们知道，为什么我在浪费时间传递数据。

哈佛公开课 - 计算机科学课程节选

But if you imagine making these measurements more and more and more quickly, in the end, you can measure what you can say is the acceleration now.

但如果你想越来越短的时间内,测量这些数据,最终,你会测量出你所说的现在的加速度

耶鲁公开课 - 基础物理课程节选

And it's a topic I want to pick up on today, we're going to do for the next few lectures, and it's a topic I want to spend some time on because this idea of capturing data and methods, the term we're going to use for it, but data and functions that belong to that data, things that can be used to manipulate them, is a really powerful one.

我们会在今天讲这个话题,在后面几节课还会讲这个,这是个我愿意花点时间，在上面的话题因为这是个,捕获数据和方法的思想,我们用这个术语来形容它，数据中包括了数据和函数等，能用来操作它们的东西,真的是很强大的工具，我们真正要讲的东西是，我们要学会如何把信息。

麻省理工公开课 - 计算机科学及编程导论课程节选

You could take weights on people measured over a period of many years and look at the variability over time in weight and then link it to things like heart disease and cancer, and I'll come back later and talk about the results of that particular study.

我们还可以得到人们很长一段时间里,每年的体重数据,观察体重随着时间变化的变动,并将观察结果与心脏疾病和癌症联系起来,我等一下会告诉大家这项研究的结果

耶鲁公开课 - 关于食物的心理学、生物学和政治学课程节选

So we're to assume we can get to any piece of data, any instruction in constant time, and the second assumption we're going to make is that the basic primitive steps take constant time, same amount of time to compute. Again, not completely true, but it's a good model, so arithmetic operations, comparisons, things of that sort, we're all going to assume are basically in that in that particular model.

因此如果我们假设在恒定的时间内,我们可以取得任何一块数据,任何一种数据结构的话,我们要做的第二个假设就是,基本的原始操作计算花费的时间是恒定的,这个假设也不是完全正确的，但这个模型其实挺不错的，因此算法操作，比较，这一类的事情，我们在这个特定的模型中都假设是基本的,操作，花费的时间是恒定相同的。

麻省理工公开课 - 计算机科学及编程导论课程节选