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如何更有效地管理时间?

发布者: 五毒 | 发布时间: 2022-6-18 07:30| 查看数: 76| 评论数: 0|



In the summer of 1997, NASA's Pathfinder spacecraft landed on the surface of Mars, and began transmitting incredible, iconic images back to Earth. But several days in, something went terribly wrong. The transmissions stopped. Pathfinder was, in effect, procrastinating: keeping itself fully occupied but failing to do its most important work. What was going on?

在1997年的夏天,美国航天局探索者飞船降落在火星表面,向地球传输令人惊叹不已的,标志性的图像。但是几天后,出现了一些严重的问题。传输停止了。探索者出现了拖延现象:虽然排满了工作,但没做最重要的任务。这是怎么回事?

There was a bug, it turned out, in its scheduler. Every operating system has something called the scheduler that tells the CPU how long to work on each task before switching, and what to switch to. Done right, computers move so fluidly between their various responsibilities, they give the illusion of doing everything simultaneously.

原来在时刻表中有一个程序错误。每一个操作系统都有一个时刻表中央处理器,会在转换前通知处理时间段,以及切换到哪个任务。若处理得当,电脑会在不同任务间切换自如,因此会给人一种它在同时处理所有事物的幻觉。

But we all know what happens when things go wrong. This should give us, if nothing else, some measure of consolation. Even computers get overwhelmed sometimes. Maybe learning about the computer science of scheduling can give us some ideas about our own human struggles with time.

但是我们都知道如果操作不当会导致什么后果。如果别无其他,这至少能给我们稍许安慰。即便是电脑,有时也会崩溃。也许学习关于电脑科学的任务规划能给我们人类如何处理棘手的时间问题带来一些启发。

One of the first insights is that all the time you spend prioritizing your work is time you aren't spending doing it. For instance, let's say when you check your inbox, you scan all the messages, choosing which is the most important. Once you've dealt with that one, you repeat. Seems sensible, but there's a problem here.

第一:我们花在给事情做优先级排序的时间意味着我们一件具体的事情都没做。例如,假设当你查看收件箱时,你会浏览所有的信息,选出最重要的。一旦你处理完一个,你重复相同的动作。看上去非常合理,但是存在一个问题。

This is what's known as a quadratic-time algorithm. With an inbox that's twice as full, these passes will take twice as long and you'll need to do twice as many of them! This means four times the work. The programmers of the operating system Linux encountered a similar problem in 2003.

这就是计算机学科里著名的二次时间算法。当一个收件箱有两倍之多,它们需要两倍时间长来运行,你需要花两倍时间来处理!这意味着工作量是原来的四倍。操作系统雷尼克斯的程序员在2003年也遇到了类似的问题。

Linux would rank every single one of its tasks in order of importance, and sometimes spent more time ranking tasks than doing them. The programmers' counterintuitive solution was to replace this full ranking with a limited number of priority "buckets."

雷尼克斯会按照重要性顺序对其每一项任务进行排序,有时会花费更长的时间来排序而不是做事。程序员反直觉的做法是用有限数量的优先“桶”取代完整排名。

The system was less precise about what to do next but more than made up for it by spending more time making progress. So with your emails, insisting on always doing the very most important thing first could lead to a meltdown.

这个系统会降低下一步做什么的准确性但是却花了更多的时间来完成任务。因此关于你的邮件,总是坚持先完成最重要的会导致崩溃。

Waking up to an inbox three times fuller than normal could take nine times longer to clear. You'd be better off replying in chronological order, or even at random! Surprisingly, sometimes giving up on doing things in the perfect order may be the key to getting them done.

打开一个比平常多3倍的收件箱会花费长达九倍的时间来处理。你最好按时间顺序来回复,或者甚至随机回复!令人惊讶的是,有时放弃用完美的顺序来执行任务也许才是把事情完成的关键。

Another insight that emerges from computer scheduling has to do with one of the most prevalent features of modern life: interruptions. When a computer goes from one task to another, it has to do what's called a context switch, bookmarking its place in one task, moving old data out of its memory and new data in.

另一点出现在电脑排序时生活中最常见的问题之一:各种干扰。当电脑从一个任务进行到另一个任务时,它需要执行称为上下文切换的任务,给每一个任务标一个书签,将内存中之前的数据移出,导入新的数据。

Each of these actions comes at a cost. The insight here is that there's a fundamental tradeoff between productivity and responsiveness. Getting serious work done means minimizing context switches. But being responsive means reacting anytime something comes up.

这些行动中的每一项都是有代价的。此处有一个重要的权衡问题存在于生产效率和反应能力之间。完成重要任务意味着要减少上下文切换。但是反应迅速则意味着对随时发生的任务进行反馈。

These two principles are fundamentally in tension. Recognizing this tension allows us to decide where we want to strike that balance. The obvious solution is to minimize interruptions. The less obvious one is to group them. If no notification or email requires a response more urgently than once an hour, say, then that's exactly how often you should check them.

这两个原则孰轻孰重令人难以取舍。意识到这个取舍难题让我们决定在哪取得这样的平衡。显而易见的解决方式就是减少各类干扰。退而其次的方式是分组。如果一小时内没有推送通知或者需要回复的邮件,这是你通常查看它们的频次。

No more. In computer science, this idea goes by the name of interrupt coalescing. Rather than dealing with things as they come up – Oh, the mouse was moved? A key was pressed? More of that file downloaded?– the system groups these interruptions together based on how long they can afford to wait.

不会更多了。在电脑科学中,这个概念被命名为中断合并。与其处理随时出现的事情,比如,喔,鼠标动了?摁了个键?下载更多的文件?系统分组会根据它们能等多久将这些干扰问题放在一起。

In 2013, interrupt coalescing triggered a massive improvement in laptop battery life. This is because deferring interruptions lets a system check everything at once, then quickly re-enter a low-power state. As with computers, so it is with us.

在2013年,中断合并极大地延长了笔记本电池的寿命。这是因为推迟处理干扰可以让系统一次性检查完毕,然后快速重新进入低电量模式。就像电脑一样,我们也是如此。

Perhaps adopting a similar approach might allow us users to reclaim our own attention, and give us back one of the things that feels so rare in modern life: rest.

也许采用一个相似的方式能让我们用户重新集中注意力,让我们还给我们一件在现代生活中感觉如此罕见的事情:休息。


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