Anything you try to improve will have a growth curve.Imagine you ran everyday and you tracked your speed to finish a 5-mile course.Smoothing out the noise, over enough time you’d probably get a graph like this:
任何你试图提高水平的东西都有一个增长曲线。想象一下，你每天都跑步，并记录下跑完五公里的速度。在足够长时间之后，经过平滑降噪处理，你很可能得到这样的增长曲线:
Here, improvement works on a logarithmic scale.As you get better, it gets harder and harder to improve.Elite athletes expend enormous effort to shave seconds off their best times.Novice athletes can shave minutes with just a little practice.
这里，水平提高以对数曲线的形式发生。随着你变得更强，提高也越来越难。精英运动员付出巨大的努力也只能把最好成绩提高几秒，而新手运动员只需稍加练习就可以提高几分钟。
Logarithmic growth is the first type of growth.This is where you see a lot of progress in the betginning, but continuing progress is more difficult.
对数增长是第一种类型的增长。一开始进步很快，但持续提高很难。
Now imagine a different graph.This time you’ve build a new website you update regularly and you’re measuring subscribers.This graph would likely look very different:
现在想象另一种曲线。这回你搭建了一个新网站，定期更新并且监测订阅用户数。增长曲线可能看上去与之前的很不一样:
This is exponential growth, the second type of growth.Website traffic is often exponential because as a blog attracts more readers, there are more opportunities for word about the blog to spread.A blog with zero traffic also has zero word of mouth.
这是第二种类型的增长:指数增长。网站流量通常是指数增长的，因为随着博客吸引更多读者，博客的内容也就得到了更多的传播机会。零流量的博客通常也是零口碑。
I’ve noticed most things tend to be either logarithmic or exponential growth.Despite this, linear progress is what most people expect.We tend to expect things to move in the same direction or rate as they have in the past.This violation of our expectation leads to some mistake in how we set goals and act on them.
我注意到大多数事物往往是对数增长或指数增长的。尽管如此，线性增长却是大部分人所期望的。我们倾向于期望事物按照与过去相同的方向或速度前进。实际增长情形与预期不符会导致我们在设定目标并采取行动时犯一些错误。
The Logarithmic Growth Mistake
在对数型增长时常犯的错误
The first kind of mistake is assuming straight-line growth, when reality is actually logarithmic.There are many situations which usually fit this pattern:
第一类错误是实际情形是对数增长，我们却以为是线性增长。 有许多情况符合这种模式:
Athletic performance r
运动表现
Weight gain/loss r
增重/减肥
Learning a new language r
学习一门新语言
Productivity
生产力
Mastery of a complex skill
掌握复杂的技能
Assuming straight-line growth means overconfidence in long-term progress.As a result, it is easy to hit plateaus if the difficulty isn’t deliberately tuned to break your confortable rhythm.
线性增长的假设意味着对长期进步过于自信。因此，如果不刻意调整难度来打破舒适的节奏，则很容易陷入平台期。
Logarithmic growth also implies it is easier to slide back down the hill.Since it is so steep in the beginning, carelessness can mean those immediate gains are ofthen easily lost.Losing weight quickly may be more desireable than losing it slowly, but it also risks putting it back on again quickly if you stop your efforts.
对数型增长也意味着更容易滑下山坡。由于一开始的增长曲线十分陡峭，一不留神，那些迅速取得的进步也很容易再次丢失。快速减肥可能比慢慢减肥更为理想，但这也意味着一旦停止努力，就有很大风险反弹。
Logarithmic mistakes are common, but so to are mistakes when reality is in the other type of growth curve.
在对数增长中易犯的错误很常见，但指数增长中的错误也不少见。
The Exponential Growth Mistake
在指数型增长时常犯的错误
Once again, people view progress linearly when it is, in fact, exponential.Some examples which usually follow exponential curves for at least part of their lifecycle are:
同样，当实际情形是指数增长时，人们也会将进步看成是线性的。至少在一段时期符合指数增长的例子有:
Technological improvement (e.g.Moore’s Law)
技术进步(例如:摩尔定律)
Business growth
企业成长
Wealth
财富积累
Rewards to talent/career
才能/事业回报
Unlike logarithmic curves, almost nothing is consistently exponential.Most are only exponential over some range of values, outside of which they are logarithmic again.
与对数曲线不同，几乎没有什么能持续保持指数增长。通常指数增长只发生在一定范围内，超出这个范围则又回到对数增长。