第二十二封信中英文对照：

To our shareowners:

致我们的股东：

Something strange and remarkable has happened over the last 20 years. Take a look at these numbers:

过去的20年里，发生了一些奇怪而令人惊讶的事情。请看这些数字：

1999 3%

2000 3%

2001 6%

2002 17%

2003 22%

2004 25%

2005 28%

2006 28%

2007 29%

2008 30%

2009 31%

2010 34%

2011 38%

2012 42%

2013 46%

2014 49%

2015 51%

2016 54%

2017 56%

2018 58%

The percentages represent the share of physical gross merchandise sales sold on Amazon by independent thirdparty sellers – mostly small- and medium-sized businesses – as opposed to Amazon retail’s own first party sales. Third-party sales have grown from 3% of the total to 58%. To put it bluntly:

百分比数字代表第三方卖家（主要是中小型企业）在Amazon上销售的总销售额百分比。第三方销售额从总销售额的3％增长到58％。说清楚一点就是：

Third-party sellers are kicking our first party butt. Badly.

第三方卖家正全方位地击败作为官方的Amazon，他们大大胜出。

And it’s a high bar too because our first-party business has grown dramatically over that period, from $1.6 billion in 1999 to $117 billion this past year. The compound annual growth rate for our first-party business in that time period is 25%. But in that same time, third-party sales have grown from $0.1 billion to $160 billion – a compound annual growth rate of 52%. To provide an external benchmark, eBay’s gross merchandise sales in that period have grown at a compound rate of 20%, from $2.8 billion to $95 billion.

这建立起很高的门坎，因为在此期间，我们的官方业务也急剧增长，从1999年的16亿美元增长到去年的1170亿美元，复合年增长率为25％。与此同时，第三方销售额从1亿美元增长到1600亿美元，复合年增长率为52％。提供一个对目标外部基准，eBay在同时期的商品销售总额以20％的复合增长率增长，从28亿美元增长到950亿美元。

Why did independent sellers do so much better selling on Amazon than they did on eBay? And why were independent sellers able to grow so much faster than Amazon’s own highly organized first-party sales organization? There isn’t one answer, but we do know one extremely important part of the answer:

为什么第三方卖家在Amazon上的销售成绩比在eBay上好得多？为什么第三方卖家能够比Amazon官方增长得更快？没有一个确切答案，但是我们对答案略知一二。

We helped independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. There are many such tools, including tools that help sellers manage inventory, process payments, track shipments, create reports, and sell across borders – and we’re inventing more every year. But of great importance are Fulfillment by Amazon and the Prime membership program. In combination, these two programs meaningfully improved the customer experience of buying from independent sellers. With the success of these two programs now so well established, it’s difficult for most people to fully appreciate today just how radical those two offerings were at the time we launched them. We invested in both of these programs at significant financial risk and after much internal debate. We had to continue investing significantly over time as we experimented with different ideas and iterations. We could not foresee with certainty what those programs would eventually look like, let alone whether they would succeed, but they were pushed forward with intuition and heart, and nourished with optimism.

我们提供最好的销售工具给第三方卖家，帮助第三方卖家可以跟官方竞争。这样的工具提供的服务包括库存管理、付款流程、物流追踪、报告生成和跨境销售，而且还在持续发明新工具。然而，更重要的是Amazon配送服务和Prime会员服务。结合这两项服务，可以大大改善和第三方卖家购买商品的客户体验。如今这两项服务已经很成功，因此大家很难想象当初推出它们时，这两种产品的发展有多么艰难。经过内部成员大量讨论之后，我们投资于这两项具有重大财务风险的服务。在我们尝试不同的想法并多次迭代后，我们继续加码大笔投资。我们无法预见这些服务最终会长成什么样子，更不用说它们会不会成功。这两项服务被直觉推动，被乐观滋润。

Intuition, curiosity, and the power of wandering

直觉、好奇心和漫步的力量

From very early on in Amazon’s life, we knew we wanted to create a culture of builders – people who are curious, explorers. They like to invent. Even when they’re experts, they are “fresh” with a beginner’s mind. They see the way we do things as just the way we do things now. A builder’s mentality helps us approach big, hard-to-solve opportunities with a humble conviction that success can come through iteration: invent, launch, reinvent, relaunch, start over, rinse, repeat, again and again. They know the path to success is anything but straight.

从一开始，我们就知道我们想营造一种创造者文化，也就是一种属于好奇者、探险者的文化。他们喜欢发明。即使已经是专家，他们还是具备初学者的好奇心。他们看待做事的价值观，正是我们现做事的原则。创造者心态能帮助我们以谦虚来把握重大的机会和难以解决的问题。我们相信成功可以透过迭代来实现：发明、推出、再发明、再推出、从头来过、一次又一次重复。他们知道成功的道路绝不可能一帆风顺。

Sometimes (often actually) in business, you do know where you’re going, and when you do, you can be efficient. Put in place a plan and execute. In contrast, wandering in business is not efficient … but it’s also not random. It’s guided – by hunch, gut, intuition, curiosity, and powered by a deep conviction that the prize for customers is big enough that it’s worth being a little messy and tangential to find our way there. Wandering is an essential counter-balance to efficiency. You need to employ both. The outsized discoveries – the “non-linear” ones – are highly likely to require wandering.

有时（通常是实际上）在业务中，你确实清楚自己要的是什么，于是你可以很有效率地往前迈进。制定计划，然后执行。相比之下，在企业中漫步不前（Wandering）并不高效。漫步不是随机的，而是受预感、直觉和好奇心引导，坚信一点混乱和偏离正轨能带给客户更大的好处。漫步是必要的平衡，你需要同时兼顾效率和漫步。大的发明－尤其是「非线性」的发明，极需要漫步才有机会出现。

AWS’s millions of customers range from startups to large enterprises, government entities to nonprofits, each looking to build better solutions for their end users. We spend a lot of time thinking about what those organizations want and what the people inside them – developers, dev managers, ops managers, CIOs, chief digital officers, chief information security officers, etc. – want.

数百万名AWS客户遍及初创公司到大企业，从政府到非营利组织，每名客户都希望提供终端消费者更好的解决方案。我们花费大量时间思考这些组织的需求以及组织内部人员的需求－开发人员、开发经理、运营经理、CIO、首席数字长和首席信息安全长想要的东西。

Much of what we build at AWS is based on listening to customers. It’s critical to ask customers what they want, listen carefully to their answers, and figure out a plan to provide it thoughtfully and quickly (speed matters in business!). No business could thrive without that kind of customer obsession. But it’s also not enough. The biggest needle movers will be things that customers don’t know to ask for. We must invent on their behalf. We have to tap into our own inner imagination about what’s possible.

AWS的大部分功能都奠基于客户的意见。询问客户他们想要什么是至关重要的事，认真听他们的回答，并制定出计划，周到且迅速提供服务（速度是关键！）。没有这种对客户的专注，任何企业都无法蓬勃发展。但这样还不够，最大的推动力是那些客户不知道怎么提出需求的事情。我们必须为他们发明。我们必须从想象出发，化可能为真实。

AWS itself – as a whole – is an example. No one asked for AWS. No one. Turns out the world was in fact ready and hungry for an offering like AWS but didn’t know it. We had a hunch, followed our curiosity, took the necessary financial risks, and began building – reworking, experimenting, and iterating countless times as we proceeded.

AWS本身就是一个例子。没有客户要求AWS这样的东西。没有任何一名客户。事实证明，世界已经做好了准备并渴望AWS的出现，只是世界并不知道这件事。我们有预感并跟随好奇心，承担必要的财务风险，然后开始建构、重来、试验和迭代，就这样进行了无数次。

Within AWS, that same pattern has recurred many times. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And on the listeningcarefully-to-customers side, we heard loudly that companies felt constrained by their commercial database options and had been unhappy with their database providers for decades – these offerings are expensive, proprietary, have high-lock-in and punitive licensing terms. We spent several years building our own database engine, Amazon Aurora, a fully-managed MySQL and PostgreSQL-compatible service with the same or better durability and availability as the commercial engines, but at one-tenth of the cost. We were not surprised when this worked.

这样的模式已经在AWS重复多次。例如，我们发明了DynamoDB，这是一种可扩展、低延迟的键值（Key-Value）数据库，已经有成千上万名AWS客户在使用。认真聆听客户需求，我们听到许多公司对自己使用的商业数据库感到束缚，数十年来一直对数据库提供商感到不满意－这些产品昂贵、专用、高度限制，又经常带有惩罚授权使用条款。我们花费了数年时间，构建自己的数据库引擎Amazon Aurora，这是一种全托管的服务，兼容MySQL和PostgreSQL，拥有和其他商用引擎相同，甚至更好的耐用性和可用性，但成本仅为商用引擎的十分之一。当AWS表现得很好时，我们并不感到讶异。

But we’re also optimistic about specialized databases for specialized workloads. Over the past 20 to 30 years, companies ran most of their workloads using relational databases. The broad familiarity with relational databases among developers made this technology the go-to even when it wasn’t ideal. Though sub-optimal, the data set sizes were often small enough and the acceptable query latencies long enough that you could make it work. But today, many applications are storing very large amounts of data – terabytes and petabytes. And the requirements for apps have changed. Modern applications are driving the need for low latencies, real-time processing, and the ability to process millions of requests per second. It’s not just key-value stores like DynamoDB, but also in-memory databases like Amazon ElastiCache, time series databases like Amazon Timestream, and ledger solutions like Amazon Quantum Ledger Database – the right tool for the right job saves money and gets your product to market faster.

我们也对用于特殊工作的专用数据库的前景感到乐观。在过去的20到30年间，企业使用关系数据库来处理大部分业务需求。开发人员对关系数据库的选择，主要取决于他们是否了解该技术，而不是技术本身是否优异。尽管没那么好，但因为数据集的大小通常很小，所以查询等待时间还是在可接受的范畴。但是今天，许多应用程序的数据量级在TB和PB，而且需要满足低延迟、实时处理以及并发处理的需求。每秒处理数百万个请求是常见的需求。它需要是DynamoDB这样的键值数据库，而且也要是Amazon ElastiCache这样的内存数据库、Amazon Timestream这样的时间序列数据库、Amazon Quantum Ledger Database这样的分类账解决方案－用上正确的工具可以节省金钱，提升产品推向市场的速度。

We’re also plunging into helping companies harness Machine Learning. We’ve been working on this for a long time, and, as with other important advances, our initial attempts to externalize some of our early internal Machine Learning tools were failures. It took years of wandering – experimentation, iteration, and refinement, as well as valuable insights from our customers – to enable us to find SageMaker, which launched just 18 months ago. SageMaker removes the heavy lifting, complexity, and guesswork from each step of the machine learning process – democratizing AI. Today, thousands of customers are building machine learning models on top of AWS with SageMaker. We continue to enhance the service, including by adding new reinforcement learning capabilities. Reinforcement learning has a steep learning curve and many moving parts, which has largely put it out of reach of all but the most well-funded and technical organizations, until now. None of this would be possible without a culture of curiosity and a willingness to try totally new things on behalf of customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run rate business and growing fast.

我们也致力于帮助其他公司利用机器学习。我们已经为机器学习进行了长时间的研究，与其他重要进展一样，我们最初尝试将内部学习工具向外推广的尝试是失败的。经过数年的漫步－实验、迭代、优化，以及来自客户的宝贵建议，我们找到SageMaker，并在18个月前正式推出。SageMaker减少了机器学习过程中的繁重复杂的工作，从而使AI能够普及。如今，成千上万名客户使用SageMaker在AWS上建构机器学习模型，我们将继续加强服务，添加新的强化学习功能（Reinforcement learning）。强化学习的学习曲线陡峭，并不容易掌握。目前为止，除资金最雄厚的技术组织外，其他人都无法接触它。出于好奇心文化，以及乐意为客户尝试新事物，我们开始以客户为中心进行漫步和聆听－AWS现在是年营业额300亿美元的业务，而且还在快速增长。

Imagining the impossible

想象那些不可能的事

Amazon today remains a small player in global retail. We represent a low single-digit percentage of the retail market, and there are much larger retailers in every country where we operate. And that’s largely because nearly 90% of retail remains offline, in brick and mortar stores. For many years, we considered how we might serve customers in physical stores, but felt we needed first to invent something that would really delight customers in that environment. With Amazon Go, we had a clear vision. Get rid of the worst thing about physical retail: checkout lines. No one likes to wait in line. Instead, we imagined a store where you could walk in, pick up what you wanted, and leave.

如今，Amazon在全球零售业中仍然只是小人物。我们在零售市场中所占的比例较低，而且我们开站的每个国家里都有规模更大的零售商，近90％的零售仍然发生在线下。多年以来，我们一直在思考如何在实体店中提供服务，但我们认为首先需要一款让客户真正满意的产品。有了Amazon Go，我们有了明确的愿景－摆脱实体零售最糟糕的事情：结账台。没有人喜欢排队等候结账。我们设想了一家商店，你可以走进去，拿起想要的东西，然后直接离开。

Getting there was hard. Technically hard. It required the efforts of hundreds of smart, dedicated computer scientists and engineers around the world. We had to design and build our own proprietary cameras and shelves and invent new computer vision algorithms, including the ability to stitch together imagery from hundreds of cooperating cameras. And we had to do it in a way where the technology worked so well that it simply receded into the background, invisible. The reward has been the response from customers, who’ve described the experience of shopping at Amazon Go as “magical.” We now have 10 stores in Chicago, San Francisco, and Seattle, and are excited about the future.

要实现真的很难，技术上很难。需要全球数百名聪明敬业的计算器科学家和工程师的努力。必须设计和制造专用相机和架子，发明新的计算器视觉算法，合并数百个协作相机中的图像。而且必须以一种运行良好的方式实现，让技术退入背景，客户看不见也无须看见。成就感来自于客户的响应，他们称Amazon Go的购物经历为「神奇」。我们在芝加哥、旧金山和西雅图有10家Amazon Go，我们对未来感到兴奋。

Failure needs to scale too

就算练习失败，也需要放大规模

As a company grows, everything needs to scale, including the size of your failed experiments. If the size of your failures isn’t growing, you’re not going to be inventing at a size that can actually move the needle. Amazon will be experimenting at the right scale for a company of our size if we occasionally have multibillion-dollar failures. Of course, we won’t undertake such experiments cavalierly. We will work hard to make them good bets, but not all good bets will ultimately pay out. This kind of large-scale risk taking is part of the service we as a large company can provide to our customers and to society. The good news for shareowners is that a single big winning bet can more than cover the cost of many losers.

随着公司的成长，一切都需要扩张，也包括失败实验的规模。如果失败的规模没有跟着长大，就无法取得真正有进展的进步。如果我们偶尔遇到数十亿美元的失败，我们还是会持续进行适当规模的试验。当然，我们不会轻蔑地低估试验。我们会努力使他们成为好赌注，但并非所有好赌注最终都能得到回报。作为一家大公司，这种大规模试验是我们可以为客户和社会提供的服务。对于股东来说，好消息是，一个成功的大赌注可以弥补许许多多失败的损失。

Development of the Fire phone and Echo was started around the same time. While the Fire phone was a failure, we were able to take our learnings (as well as the developers) and accelerate our efforts building Echo and Alexa. The vision for Echo and Alexa was inspired by the Star Trek computer. The idea also had origins in two other arenas where we’d been building and wandering for years: machine learning and the cloud. From Amazon’s early days, machine learning was an essential part of our product recommendations, and AWS gave us a front row seat to the capabilities of the cloud. After many years of development, Echo debuted in 2014, powered by Alexa, who lives in the AWS cloud.

Fire Phone和Echo的开发始于同一时期。Fire Phone失败后，我们（包括开发人员）吸取教训，因此加快了Echo和Alexa的工作。Echo和Alexa的构想受到《Star Trek》中计算器的启发。这个想法起源于我们已经耕耘多年的另外两个领域：机器学习和云技术。 从Amazon成立之初，机器学习就成为产品推荐功能必不可少的一部分，而AWS使我们在云技术领域处于领先位置。经过多年的研发，Echo于2014年首次亮相，并可使用透过Echo使用Alexa服务。

No customer was asking for Echo. This was definitely us wandering. Market research doesn’t help. If you had gone to a customer in 2013 and said “Would you like a black, always-on cylinder in your kitchen about the size of a Pringles can that you can talk to and ask questions, that also turns on your lights and plays music?” I guarantee you they’d have looked at you strangely and said “No, thank you.”

没有客户直接提出他们需要Echo。这是我们漫步的结果，市场调查无济于事。如果你在2013年去问任何一位客户：「你是否想在厨房里使用一个不断运转的黑色圆筒，差不多是一罐品客的尺寸。你可以与之交谈或要求它打开灯光和播音乐。」我向你保证，他们会用奇怪的眼神看着你说：「不用了，谢谢。」

Since that first-generation Echo, customers have purchased more than 100 million Alexa-enabled devices. Last year, we improved Alexa’s ability to understand requests and answer questions by more than 20%, while adding billions of facts to make Alexa more knowledgeable than ever. Developers doubled the number of Alexa skills to over 80,000, and customers spoke to Alexa tens of billions more times in 2018 compared to 2017. The number of devices with Alexa built-in more than doubled in 2018. There are now more than 150 different products available with Alexa built-in, from headphones and PCs to cars and smart home devices. Much more to come!

自从第一代Echo以来，客户已经购买了超过1亿个支持Alexa的设备。去年，我们将Alexa的理解请求和回答问题的能力提高20％，同时增加了数十亿个知识点，使Alexa比以往任何时候都更加知识渊博。开发人员将Alexa的技能数量增加一倍，达到8万项技能。与2017年相比，客户在2018年与Alexa交流的次数增加了数百亿次。内置Alexa的设备数量在2018年增加一倍以上。现在有150多种产品内置Alexa，从耳机、PC到汽车和智能家居设备。未来还会更多！

One last thing before closing. As I said in the first shareholder letter more than 20 years ago, our focus is on hiring and retaining versatile and talented employees who can think like owners. Achieving that requires investing in our employees, and, as with so many other things at Amazon, we use not just analysis but also intuition and heart to find our way forward.

结束前的最后一件事。正如我在20多年前的第一封股东信中所说，我们的重点是招聘和留住能像主人一样思考的人才。要做到这一点，需要向员工进行投资。和Amazon的其他事情一样，我们不仅分析，也会使用直觉和毅力来寻找前进的道路。

Last year, we raised our minimum wage to $15-an-hour for all full-time, part-time, temporary, and seasonal employees across the U.S. This wage hike benefitted more than 250,000 Amazon employees, as well as over 100,000 seasonal employees who worked at Amazon sites across the country last holiday. We strongly believe that this will benefit our business as we invest in our employees. But that is not what drove the decision. We had always offered competitive wages. But we decided it was time to lead – to offer wages that went beyond competitive. We did it because it seemed like the right thing to do.

去年，我们将全美所有全职、兼职、临时和季节性雇员的最低工资提高到每小时15美元。这次加薪使超过25万名Amazon员工以超过10万名季节性员工受益。我们坚信投资在员工身上有利于我们的业务。但这不是决定的原因。我们一直提供有竞争力的工资，但是我们现在认为是时候站出来－提供超乎其他人才竞争公司的工资。我们这样做，是因为我们认为这是正确的。

Today I challenge our top retail competitors (you know who you are!) to match our employee benefits and our $15 minimum wage. Do it! Better yet, go to $16 and throw the gauntlet back at us. It’s a kind of competition that will benefit everyone.

今天，我挑战顶级零售竞争对手（你知道我们在说谁！），提供和我们一样的员工福利和15美元最低工资。来吧！最好能给16美元，再把挑战抛回来给我们。这是一场使所有人受益的竞争。

Many of the other programs we have introduced for our employees came as much from the heart as the head. I’ve mentioned before the Career Choice program, which pays up to 95% of tuition and fees towards a certificate or diploma in qualified fields of study, leading to in-demand careers for our associates, even if those careers take them away from Amazon. More than 16,000 employees have now taken advantage of the program, which continues to grow. Similarly, our Career Skills program trains hourly associates in critical job skills like resume writing, how to communicate effectively, and computer basics. In October of last year, in continuation of these commitments, we signed the President’s Pledge to America’s Workers and announced we will be upskilling 50,000 U.S. employees through our range of innovative training programs.

我们为员工推出的许多计划。我之前提到过职业选择计划，此计划预付最高95％的学杂费，让员工可以取得学习领域的证书或文凭，从而给他们尝试新职业的机会，即使这些职业会不在Amazon。现在已有超过1.6万名员工从此计划中受益且人数持续。同样的，我们的职业技能计划（Career Skills）对员工进行关键工作技能的短期培训，例如简历写作、有效沟通和计算器基础知识。去年10月，为兑现这些承诺，我们签署了《President’s Pledge to America’s Workers》，宣布将透过一系列培训计划，提高5万名美国员工的技能。

Our investments are not limited to our current employees or even to the present. To train tomorrow’s workforce, we have pledged $50 million, including through our recently announced Amazon Future Engineer program, to support STEM and CS education around the country for elementary, high school, and university students, with a particular focus on attracting more girls and minorities to these professions. We also continue to take advantage of the incredible talents of our veterans. We are well on our way to meeting our pledge to hire 25,000 veterans and military spouses by 2021. And through the Amazon Technical Veterans Apprenticeship program, we are providing veterans on-the-job training in fields like cloud computing.

我们的投资不仅限于现有员工，甚至不局限于当下。为了培训明天的劳动力，我们已承诺投资5000万美元，包括Amazon未来工程师计划，这是一项支持全国小学、高中和大学生STEM和CS教育的计划，将会特别着重于吸引更多女孩和少数民族。我们将继续招聘退伍军人，让他们发挥绝佳的才能。我们正在努力实现承诺，在2021年前雇用2.5万名退伍军人及其配偶。透过Amazon的退伍军人技术培训计划（Technical Veterans Apprenticeship），我们将在云计算等领域提供退伍军人在职培训。

A huge thank you to our customers for allowing us to serve you while always challenging us to do even better, to our shareowners for your continuing support, and to all our employees worldwide for your hard work and pioneering spirit. Teams all across Amazon are listening to customers and wandering on their behalf!

非常感谢我们的客户，在为你们提供服务时，你们始终敦促我们做得更好。非常感谢我们的股东，谢谢你们持续给予我们支持。感谢全球Amazon员工的辛勤工作和开拓精神。Amazon各地的团队都在倾听客户的意见，并以客户为中心寻求提供更好的服务！

As always, I attach a copy of our original 1997 letter. It remains Day 1.

如同往常，我把我们在1997年写的致股东信附在文末。我们的价值观依然不变，今天依旧是Day 1。

Sincerely,

Jeffrey P. Bezos

真诚的

杰夫·贝佐斯

Jeffrey P. Bezos

Founder and Chief Executive Officer

Amazon.com, Inc.

杰夫·贝索斯

Amazon创始人暨CEO

我的观点

这封信，贝索斯说，亚马逊的第三方卖家从开始的3%增长到了58%，第三方卖家正在击败官方，还说这是一个好的现象，说明他们的第三方服务做得很好。

创造者文化

亚马逊一开始想要营造一种创造者文化。

创造者文化是一种好奇者，探险者的文化，是喜欢发明的文化。即使已经是专家，他们还是具备初学者的好奇心。

创造者心态能帮助亚马逊以谦虚来把握重大的机会和难以解决的问题。相信成功可以透过迭代来实现：发明、推出、再发明、再推出、从头来过、一次又一次重复。

确实这就是创新者的整个创新流程，在你确定知道自己想要什么的时候，高效去做就行了。如果不清楚，那就去用直觉，预感和好奇心的引导，去漫步。 大的发明－尤其是「非线性」的发明，极需要漫步才有机会出现。

宽容的环境，好奇的人心，确实可以激励创新。