Original by Paul Graham
Reading time: 20 minutes.
This is the latest work by Silicon Valley godfather Paul Graham, and it takes a deep dive into superlinear returns.
In the context of the economic downturn, there have been a lot of complaints on the Internet, why can Internet celebrities make so much money, while ordinary people can't even afford eyebrow pencils?
Please read this article carefully and you may find the answer!
This article does not judge from the moral level, but objectively studies the law of the development of things. Once someone is lucky enough to step on the job of super-linear returns, it may not take as hard work as they imagine to achieve super-linear returns.
And looking for this kind of super-linear return is worth thinking about for everyone!
Here is the body part:
When I was a kid, I didn't understand one of the most important facts in the world: that the rewards of performance are often super-linear.
Teachers and coaches always instill in us the idea that reward is proportional to effort.
They say, "You get as much as you give." "They have good intentions, but that's often not the case.
If the quality of your products is only half that of your competitors, you won't just lose half of your customers. More likely, you won't be able to retain a single customer and end up closing.
In business, the ultra-linear returns from performance are particularly pronounced.
Some people think that this is a flaw in capitalism, that as long as the rules are changed, this situation will disappear.
But in fact, the ultra-linear return on performance is a feature of the world, not a by-product of our rule-making. We can see this pattern in terms of fame, power, military victories, knowledge, and contributions to humanity. In all of these areas, successful people tend to be more and more successful.
Understanding the concept of superlinear returns is critical to understanding the world. If you have great ambitions, then you should understand it even more, because it will be your strength to ride the waves.
While there seem to be many cases where super-linear returns exist, at the end of the day, they stem from two main factors: exponential growth and thresholds.
The most typical example of superlinear returns is exponential growth, such as growing bacteria. When bacteria grow, their rate is exponential. But cultivating them can be challenging, so being skilled or not can make a huge difference in results.
The same is true for startups, which are also likely to achieve exponential growth.
Some companies have succeeded in achieving high growth rates, while most have not. This leads to very different results: companies with high growth rates may grow into valuable businesses, while companies with low growth rates may struggle to survive.
Y Combinator encourages founders to focus more on growth rates than absolute numbers, which not only prevents them from being discouraged by low absolute numbers in the early days, but also helps them decide where to focus on where to focus on growth rates. On top of that, focusing on growth rate often means you can grow exponentially.
While YC doesn't directly tell the founders that the growth rate is proportional to your investment, there is some truth to this statement. If the growth rate is indeed proportional to performance, then over time, the return on performance p will be proportional to pt.
Even after decades of deep thought, this idea still strikes me.
Exponential growth occurs when your performance is dependent on your past achievements.
However, neither our DNA nor our Xi are ready for this. Exponential growth is not intuitive to anyone, for example, children are amazed when they first hear a story about a man who asks for a grain of rice from a king on the first day and then doubles it every day.
We usually respond to things we don't understand naturally by developing Xi. However, there are few Xi about exponential growth, because there are few such examples in human history. In theory, grazing animals could have been an example: the more animals you have, the more offspring they have. In practice, however, grazing land has become a limiting factor, and there is no way to achieve exponential growth.
Or rather, there is no one-size-fits-all strategy.
In the past, there was a way to exponentially expand territory: and that was conquest. The larger the territory, the more powerful the military becomes, and the easier it is to conquer new lands. This is precisely the logic behind the endless empires that have emerged throughout history.
However, few people actually created or ruled empires, and their experiences had little impact on the daily lives and Xi of ordinary people. To ordinary people, the emperor is a distant and terrifying being, not a lesson to learn from in everyday life.
In the pre-industrial era, perhaps the most common example of exponential growth was learning. The more knowledge you have, the easier it will be to learn new things Xi. So, both in the past and now, there will always be people who are far more knowledgeable than others in a particular field. But this difference has not had much impact on traditional Xi. While "empires" of ideas can overlap with each other and have numerous "emperors", in the pre-industrial era such empires had little real influence.
However, this has changed dramatically in recent centuries.
Today, the "emperor" of thought is able to design a bomb capable of defeating the territorial "emperor". But this phenomenon is still so new that we have not yet fully understood and absorbed it. Even among those involved, few realize that they are benefiting from exponential growth or think about what they can learn from other similar situations.
The phrase "winner-takes-all" reveals another super-linear gain.
In sports, for example, there is a ladder between performance and return: the winning team can only win one game, regardless of their advantage or marginal advantage.
But this ladder effect does not only stem from the competition itself, but also from the "threshold" in the outcome. Such thresholds exist even in the absence of competition, such as proving a theorem or achieving a goal on its own.
In many cases, one factor that leads to a super-linear return is often accompanied by another. For example, crossing a certain threshold can often trigger exponential growth: in a battle, the winning side tends to lose less, which makes them more likely to win in the future.
Similarly, exponential growth helps to cross the threshold: in a market, if a company grows rapidly, it can effectively eliminate potential competitors.
Fame is a prime example of this, which combines the ** of two super-linear returns.
Fame grows exponentially because existing fans attract new ones. But the main reason for the concentration of fame is that people have limited attention spans, such as the fact that there are only so many a-lists in the minds of the public.
Learning Xi is probably the most important example that combines these two types of superlinear returns. Knowledge grows exponentially, but there are also some key thresholds, such as learning to Xi cycling. Some thresholds are like mechanical tools, and once you learn to read, other knowledge can be grasped more quickly. But the most critical hurdle is new discoveries. Knowledge is in a sense fractal: when you go deep into the boundaries of one field, you sometimes open up a whole new one. This is how masters like Newton, Dürer, and Darwin opened up new frontiers and explored new knowledge in the first place.
So, how do you find a general rule with a super-linear return situation?
One obvious way to do this is to look for jobs that can lead to compound growth.
There are two types of compound growth jobs:
One is direct compounding, which means that your good performance in the previous cycle will make you better in the next cycle.
This usually happens when you're building infrastructure or expanding your audience and brand.
The other is the compound growth achieved through learning Xi, after all, learning Xi itself can bring compound effects.
This situation is interesting because in the process, you may feel that you are not good enough to even achieve your current goals. But if you've learned a lot, you're still experiencing exponential growth.
This is one of the reasons why Silicon Valley is so tolerant of failure.
Silicon Valley people aren't tolerant of failure, and they will only continue to support you when they see you learn from your failures. But if you do, then you're actually a good choice: maybe your company isn't growing as much as you expected, but your personal growth will eventually pay off.
In fact, exponential growth without Xi is often closely intertwined with Xi and should be seen as the norm rather than the exception. This leads to another heuristic principle: to always keep learning Xi. If you stop Xi, then you may be off the path to super-linear returns.
But don't overdo it with the Xi you learn, and don't limit yourself to just learning Xi what you know to be valuable. After all, you're still in the Xi stage, and you're not sure what knowledge will be valuable in the future, and too strict standards may cause you to miss out on some unusual but potential areas.
When it comes to ladder functions, can we also find practical strategies like "looking for thresholds" or "looking for competition"?
It's a tricky question, and just because there's a threshold doesn't mean it's worth it.
For example, when playing a round of Russian roulette, while there are clear thresholds, even in the best of circumstances, your situation does not improve.
In the same way, "looking for competition" doesn't always work. What if the reward itself isn't appealing?In contrast, rapid exponential growth guarantees not only the shape of the yield curve, but also its size – because something that grows fast enough, even if it is insignificant at first, will eventually become large – while thresholds only ensure pattern.
To take advantage of thresholds, a test must be included to ensure that the game is worth playing. Here's an idea: if you find something mediocre but still popular, it might be a good idea to try replacing it.
For example, if a company makes a product that is not popular but people will buy it, then if you can make a better alternative, they are likely to switch to the new product.
It would be nice if there was a way to discover the intellectual threshold of potential. How can we determine which questions are hiding new areas of research?
While we may never be able to say this with complete certainty, given the enormous value of the potential, even slightly better than random methods can be useful, and hopefully we can find one.
To a certain extent, we can ** which research questions are unlikely to lead to new discoveries: those that seem plausible but are tedious. And the problems that lead to new discoveries often seem very mysterious, but may not seem important. (If they are both mysterious and obviously important, they become well-known major unsolved questions that attract the attention of many researchers.) ）
So one strategy here is to let curiosity rather than careerism drive you – let your curiosity run free instead of just doing the work that "should" do.
For those with big ambitions, the prospect of super-linear growth in performance is exciting. And, here's the good news: the field is constantly expanding, both in terms of the type of work and in the rewards themselves.
There are two reasons for this change, although they are closely linked, and they can be seen as almost the same reason: the rapid progress of technology and the diminishing importance of organizations.
Fifty years ago, joining an organization was almost a necessity to work on a grand project, because it was the only way to access resources, make friends, and broaden distribution channels.
So in 1970, your prestige was often determined by the prestige of the organization you belonged to.
This form of evaluation is quite accurate, as it is difficult for people who do not belong to any organization to achieve significant achievements. Of course, there are some exceptions, independent workers like artists and writers, who create with inexpensive tools and have their own brands. But they still rely on organizations to reach a wider audience.
In the past, an organization-dominated world limited the difference in performance returns. But in my lifetime, this has changed dramatically.
Now, more people can enjoy the freedom that 20th-century artists and writers have. There are a lot of ambitious projects that no longer require a huge initial investment, and at the same time, the avenues for learning Xi, making money, finding partners, and reaching audiences have become more diverse.
Although the Old World still exists, the rate of change is historically staggering, especially given its far-reaching implications. It's hard to imagine anything more fundamental than a change in performance returns.
Once the institutional constraints are freed, the diversity of results will be even more significant. This doesn't mean everyone will benefit: high-performing people will have greater success, while low-performing people may experience greater failure. This is very important and needs to be kept in mind!
Taking risks in pursuit of super-linear returns isn't for everyone. For most people, it would be better to be part of a whole. So, who should go after super-linear returns?There are two types of people:
One is people who are confident in their own strength and believe that they can achieve higher net returns in a world of greater change;
The other category is people who can take risks to try, especially young people, who are willing to take risks and see if they can succeed.
The shift away from institutional constraints does not simply mean the departure of current institutional members. Many of the new winners will be those who have never been accepted into the institution in the past. As a result, the democratization of opportunity will be broader and more real than any programme developed by the institutions themselves.
Not everyone is happy with this shift to unleash ambition. It challenges some vested interests and inherent ideologies. But if you're an aspiring individual, this is undoubtedly good news. So, how do you seize this opportunity?
The best way to take full advantage of ultra-linear returns is to deliver exceptional results.
At the top of the achievement curve, a little extra effort can pay off big rewards. And there's relatively little competition at the top – not just because it's so hard to do something exceptional, but also because people shy away from it, and so few actually try it. This means that it's not just the best work in itself that is a great value proposition, it's even just trying to do it.
There are so many factors that influence the outcome of your work, and to stand out, you need to be at the best in almost everything. For example, to make things to the extreme, you have to be interested in it. Mere diligence is not enough.
Therefore, in a world of super-linear returns, it is important to understand what interests you and look for opportunities to achieve it.
It's equally important to choose a job that fits your current living environment. For example, if a job is inherently a lot of time and effort, it will be more rewarding to do it when you are young and childless.
Skill is essential when it comes to achieving excellence. It's not just a matter of effort. I'll try to provide a way to do it in the following paragraph.
Choose jobs that you are naturally good at and that you are deeply interested in
Develop the Xi of working on individual projects independently, it doesn't matter what the project is, the key is to make you feel ambitious;
Work as hard as you can, but avoid overexertion, which will eventually lead you to the forefront of knowledge. These areas may seem flat, but when you look closely, they are full of gaps. Work hard and avoid overwork, which will eventually lead you to the forefront of knowledge;
Take as much risk as you can, if you've never failed, it probably means you're being too conservative;
Find the best partners, cultivate elegant taste, and learn from the best examples Xi. Be honest, especially with yourself;
Pay attention to exercise, diet and sleep, and stay away from dangerous drugs;
In times of hesitation, follow your curiosity. Curiosity never fools you, it knows better than you what deserves attention.
Of course, there's one more crucial thing: luck.
Luck is a factor that cannot be ignored at all times, especially when you are working independently rather than as part of an organization.
We often say that luck is a combination of preparation and chance, but in reality, there is also a part of pure chance that is beyond our control. The solution lies in multiple attempts, which is another reason to start the adventure early.
The field of science is probably the most typical example of superlinear returns. Its growth is exponential, and this growth is not only a process of learning Xi, but also a continuous breakthrough in the boundaries of knowledge, the limits of human knowledge.
As a result of this phenomenon, the level of inequality found by science is far greater than that of wealth inequality in the most divided societies. It can be said that Newton's discovery was greater than all his contemporaries combined.
This point, while seemingly obvious, is still worth elaborating. Super-linear returns imply inequality. The steeper the return curve, the greater the difference in outcomes.
In fact, the connection between super-linear returns and inequality is so strong that we can spot this type of work in a simple way: look for areas where the top few outperform the rest. In areas where everyone is performing similarly, there are often no super-linear returns.
So, what are the areas where a few people are far more than others?
Some obvious examples include: sports, politics, art, acting, directing, writing, math, science, entrepreneurship, and investing.
In the field of sports, this phenomenon is determined by external rules;In a race, you only need to be a little bit faster than everyone else to win the championship.
In the political realm, the pattern of power growth is similar to that of the ancient emperors. In some other fields, including politics, success is often associated with fame, which itself is a form of super-linear growth.
But if we exclude the influence of sports, politics and fame, we find an interesting pattern: the remaining areas are the ones that require independent thinking to succeed – areas where you not only think right, but also innovate.
In the scientific world, this is obvious, you can't just publish a ** that repeats someone else's point of view.
But in the world of investment, the situation is the same. It only makes sense for you to be bullish on a company when most other investors are not bullish on it;If everyone thinks a company has a bright future, then its share price already reflects that expectation, and the opportunity to make money is gone.
So, what else can we learn from these areas?
Regardless of the field, the initial effort is essential. The super-linear returns may seem insignificant at first, and at this rate, you might think, I'm not going to get there. However, since the reward curve rises dramatically in the later stages, it is well worth taking special measures to reach this goal.
In the startup world, this principle is known as "doing what isn't scalable."
If you can put a lot of attention into your few initial customers, ideally, you'll be able to spark exponential growth through word of mouth. Moreover, the same principle applies to any field that grows exponentially, such as Xi. When you first start learning Xi new things, you may feel at a loss. But, but in order to gain a foothold, it pays to make the initial effort because the process becomes easier as you learn more.
There's a deeper lesson in the field of super-linear returns: don't equate work with a career.
For most of the 20th century, the two were the same for most people. As a result, we have developed a Xi of equating productivity with having a job.
Even now, for most people, "your job" still means their profession.
But for writers, artists, or scientists, it refers to something they are currently researching or creating. For such people, their job is something they carry from one occupation to another, even if they don't have a regular job at all. The job may be done for the employer, but it's part of their portfolio.
Stepping into a field and facing a handful of top players is really daunting. Some people deliberately pursue this kind of competition, but it is not necessary. As long as you are gifted and intelligent enough to pursue your curiosity, you will naturally enter such a field. Your curiosity doesn't allow you to stop at mundane questions, and intriguing questions tend to breed super-linear rewards, even if they don't belong to any field in the first place.
The world of super-linear returns is not static. In fact, the biggest returns often come from expanding the field.
So, while ambition and curiosity can lead you to this field, curiosity is perhaps the more powerful motivator. Ambition may drive you to climb known peaks, but if you keep an eye on a question that is appealing enough, it may gradually rise right under your feet and become a majestic mountain.
It is challenging to precisely delineate effort, performance, and reward because, in practice, these concepts themselves have no clear boundaries. What is seen as a reward by one person may be a performance by another. While the boundaries of these concepts are somewhat blurred, they are not without meaning. I have tried my best to describe these concepts precisely and to avoid misunderstandings.