4月12日，据外媒报道，杰夫·贝索斯(Jeff Bezos)周四发布了亚马逊的年度股东信，他在信中呼吁竞争对手提供与亚马逊相同的薪酬和福利。
贝索斯还警告称，由于亚马逊拥有如此庞大的规模，因此股东们应该料到，随着亚马逊尝试新的举措，该公司可能会遭遇“数十亿美元的失败”。
以下是这封股东信的中文全文：
致股东：
在过去20年时间里，发生了一些奇怪而不寻常的事情。看看以下这些数字：
1999年3%；2000年3%；2001年6%；
2002年17%；2003年22%；
2004年25%；2005年28%；
2006年28%；2007年29%；
2008年30%；2009年31%；
2010年34%；2011年38%；
2012年42%；2013年46%；
2014年49%；2015年51%；
2016年54%；2017年56%；
2018年58%。
这些百分比代表了独立第三方卖家(主要是中小型企业)在亚马逊实体商品销售总额中所占的份额，而不是亚马逊零售公司自己的第一方销售额。第三方销售额已从占总销售额的3%增长到了58%。不妨直截了当地这么说：
第三方卖家正在踢我们第一方的屁股，而且踢得非常狠。
而且，第三方卖家的这种增长也代表着一个很高的标准，因为在此期间，我们的第一方业务大幅增长，从1999年的16亿美元增长到去年的1170亿美元。在此期间，我们第一方业务的复合年增长率为25%。但与此同时，第三方销售额从1亿美元增长到了1600亿美元——复合年增长率为52%。在这里提供一个外部对比基准：同期eBay商品销售总额的复合年增长率为20%，从28亿美元增长到了950亿美元。
为什么独立卖家在亚马逊平台上的销售表现要比在eBay平台上好得多呢？为什么独立卖家能够比亚马逊自己高度组织化的第一方销售组织增长得快得多呢？虽然并无确切的答案，但我们确实知道答案中一个极其重要的部分：
我们帮助独立卖家与自己的第一方业务竞争，对他们进行了投资，并为他们提供了我们所能想象和打造的最好的销售工具。这样的工具有很多，其中包括帮助卖家管理库存、处理付款、跟踪发货、创建报告和跨境销售的工具——我们每年都在发明更多的工具，其中Fulfillment by Amazon和Prime会员计划尤其重要。这这项计划结合在一起，大幅改善了客户从独立卖家购物的体验。随着这两个计划的成功，现在大多数人很难完全理解它们在我们刚刚推出的时候有多么不同凡响。我们在这两个计划上的投资都是在巨大的财务风险下进行的，而且经过了大量的内部辩论。随着时间的推移，我们不得不继续进行重大的投资，因为我们尝试了各种不同的想法和迭代。我们当时不能肯定地预见到这些计划最终会变成什么样子，更不用说它们是否会取得成功了，但我们还是凭着直觉和热诚推动了这些计划的发展，并以乐观的态度为其提供了滋养。
直觉、好奇心和徘徊的力量
在亚马逊成立之初，我们就知道自己想要创造一种建设者——拥有好奇心的人，或者说是探险家——的文化。他们喜欢发明，哪怕他们是专家，还是抱有跟初学者一样“新鲜的”心态。他们认为，我们做事的方式应该是专注于当下。建设者的心态能帮助我们以一种谦卑的信念来对待巨大的、难以解决的机会，明白可以通过迭代的方式来取得成功：发明、启动、重新发明、重新启动、重新开始、抹除、重复、一次又一次地重复。他们知道，通往成功的道路绝不是一帆风顺的。
在商业活动中，有些时候（经常是在实际上）你知道自己要去哪里，这样你就可以变得更有效率，制定计划并加以执行。相反，在商业活动中“徘徊”（wandering）并不是有效的……但也不是随机的，而是由直觉、好奇心和强烈的信念所引导的，这种信念认为顾客的价值是足够大的。为了找到去路，我们有必要保持一点混乱和不那么切题的态度。“徘徊”是对效率的一种必要的制衡，你需要同时采用两者。超大的发现——也就是那些“非线性”的发现——很可能是需要“徘徊”的。
AWS（亚马逊网络服务）拥有数以百万计的客户，从初创企业到大型企业，从政府实体到非营利组织，它们都希望为最终用户构建更好的解决方案。我们花了很多时间来思考这些组织想要什么，以及他们内部的人员——开发人员、开发经理、运营经理、首席投资官、首席数字官、首席信息安全官，等等——想要什么。
我们在AWS业务中构建的大部分东西都是以倾听客户声音为基础的。询问客户他们想要什么，仔细聆听他们的回答，并想出一个计划来思虑周到而又迅速（速度在商业活动中是很重要的！）地提供他们想要的东西，这是至关重要的。没有这种对客户的痴迷，任何企业都不可能兴旺发达，但这还不够。最重要的是客户自己都不知道他们需要的东西，而我们必须为他们发明出来。我们必须发掘自己的内在想象力，去想象有哪些东西是能被发明的。
AWS本身——作为一个整体而言——就是个例子。以前没人想要AWS，真的没人。但事实证明，其实那时候这个世界已经准备好了，而且是渴望得到像AWS这样的服务，只是并不知道这一点而已。我们有了一种预感，然后跟随着我们的好奇心，承担了必要的财务风险，并开始建设——在前进的过程中，我们进行了无数次的返工、试验和迭代。
在AWS中，同样的模式已经多次重现。举例来说，我们发明了DynamoDB，这是一个具有高度可扩展性的、低延迟的键值数据库，现在已被成千上万的AWS客户所使用。在仔细倾听客户的方面，我们听到了很大的声音，也就是很多公司都觉得自己受到了商业数据库可选性的限制，并且几十年来一直都对他们的数据库提供商感到不满——这些产品价格昂贵，具有专有性，还有高度锁定的、惩罚性的许可条款。我们花了几年时间构建自己的数据库引擎Amazon Aurora，这是一项管理完善的兼容MySQL和PostgreSQL的服务，具有与商业引擎相同乃至更好的耐用性和可用性，但成本只有商业引擎的十分之一。当这种服务起作用时，我们并不感到意外。
对于针对特定工作负载的专用数据库，我们也同样抱有乐观态度。在过去的20到30年中，公司使用关系数据库来运行它们的大部分工作负载。开发人员普遍都很熟悉关系数据库，从而使得这项技术成为了首选，尽管它并不理想。虽然不是最优选择，但数据集的大小通常足够小，而可接受的查询延迟时间也足够长，因此还是可行的。但时至今日，许多应用程序都存储了非常大的数据量，要用TB和PB来计量，因此对应用程序的要求也就发生了变化。现代应用程序正在推升公司对低延迟的、实时处理的、每秒能够处理数百万请求的处理能力的需求。现在的数据库已经不是只有DynamoDB这样的键值数据库，还有Amazon ElstriCache这样的内存数据库、Amazon Timstream这样的时间序列数据库、以及Amazon QuantumLedger Database这样的分类帐解决方案——这种工具可以节省资金，并让你们的产品更快地进入市场。
我们还致力于帮助公司使用机器学习技术，已经在这个方面从事了很长时间的工作。跟其他重要的进展一样，我们最初试图将早期的一些内部机器学习工具外部化的尝试都失败了。经过多年的“徘徊”——实验、迭代和改进，以及来自客户的宝贵见解——我们才找到了SageMaker，这项服务已在18个月前推出。SageMaker从机器学习过程的每一步中消除了繁重的负担、复杂性和猜测——这就令人工智能（AI）变得大众化。今天，成千上万的客户正在使用SageMaker在AWS上构建机器学习模型。我们正在继续加强这项服务，包括增加新的强化学习能力等。强化学习有着陡峭的学习曲线和许多“活动件”，这在很大程度上意味着，只有那些资金最充足、技术最强的组织才能开发这种能力。如果没有一种充满好奇心的文化和为客户尝试全新事物的意愿，那么这一切都是不可能做到的。客户正在响应我们以客户为中心的“徘徊”和倾听——AWS现在已经成为了一项年收入高达300亿美元的业务，并且正在快速增长。
敢于想象看似不可能的事
今天，亚马逊在全球零售业中仍是一个小角色。我们在零售市场中所占的百分比很低，而且在我们经营的每个国家里都有大得多的零售商。这在很大程度上是因为将近90%的零售交易依然还在线下，是在实体商店中进行的。多年以来，我们一直在考虑如何在实体店中为顾客服务；但我们认为，首先需要发明一种能够真正让顾客在这种环境中感到高兴的东西。随着亚马逊的发展，我们有了一个清晰的愿景，那就是让顾客摆脱实体零售中最糟糕的一件事：结账。没人喜欢排队，而我们设想了一种商店，在那里你们可以走进店里，拿起你们想要的东西，然后离开。
这要做到这点是很难的，需要攻克技术难关，需要世界各地数以百计聪明而又敬业的计算机科学家和工程师付出努力。我们必须设计和制造我们自己的专有摄像头和货架，发明新的计算机视觉算法，包括将数百台协作摄像头的图像拼接在一起的能力等。我们还必须做好技术工作，以至于使其消失在背景之中，不会被顾客看见。顾客已经用他们的反应给我们带来了奖励，他们形容在Amazon Go购物的体验是“神奇的”。目前我们在芝加哥、旧金山和西雅图有10家分店，并对未来充满期待。
失败也是需要规模的
随着公司的发展，任何事情都需要扩展，包括失败实验的规模。如果失败的规模没有扩大，那就无法以一种真正能让指针移动的规模进行发明。亚马逊将以适当的规模进行试验，而以我们的公司规模来看，偶尔遭遇数十亿美元的失败是正常的。当然，我们不会轻率地进行这样的实验。我们会努力作出好的押注，但并不是所有好的押注最终都会得到回报。作为一家大公司，这种大规模的冒险行为是我们可以为客户和社会提供的服务的一部分。对股东来说，好消息是，只要能赢得一次大规模的押注，就能弥补多次输掉的押注所带来的损失。
Fire手机和Echo的开发大约是在同一时间开始的。虽然Fire手机失败了，但我们(以及开发人员)得以学到了经验教训，并加快我们的努力来打造Echo和Alexa。Echo和Alexa的愿景是受到“星际迷航”计算机的启发。这个想法也起源于我们多年来一直都在建设和“徘徊”的另外两个领域：机器学习和云服务。从亚马逊早期开始，机器学习就是我们产品推荐的重要部分，而AWS为我们提供了云功能的“前排座位”。经过多年的开发，Echo于2014年首次亮相，由AWS云内部的Alexa提供支持。
那时候没有客户想要Echo，那对我们来说绝对是一次“徘徊”。市场调查也帮不上忙，因为如果你在2013年去找一位顾客说：“你想不想在厨房里放一个品客罐头大小的黑色圆柱体呢？你可以和它交谈和提问，它还可以打开你的灯和播放音乐。”我可以保证，他们会奇怪地看着你说：“不想，谢谢。”
自第一代Echo以来，客户已经购买了超过1亿台支持Alexa的设备。去年，我们将Alexa理解请求和回答问题的能力提高了20%以上，同时为其添加了数十亿条信息，从而令Alexa变得比以往任何时候都更有知识。与2017年相比，2018年里开发人员将Alexa技能的数量提高了一倍，达到了8万以上，客户与Alexa通话的次数增加了数百亿次。2018年中，内置Alexa的设备数量翻了一番还多。现在已有150多种不同的产品可以内置Alexa，其中包括耳机、个人电脑、汽车和智能家居设备等，而以后还会有更多！
接下来是我要说的最后一件事。正如我在20多年前发出的第一封股东信中所说，我们的重点是要招聘和留住那些多才多艺的、能像老板一样思考的员工。要做到这一点，就需要对我们的员工进行投资。就像亚马逊的许多其他事情一样，我们在这个方面也不仅需要分析，还需要直觉和热诚来找到前进的道路。
去年，我们将全美所有全职员工、兼职员工、临时员工和季节性员工的最低工资提高到了每小时15美元，此次加薪令25万名以上的亚马逊员工从中受益，而去年假期在全美各地亚马逊网站工作的10万多名季节性员工也一样获得了好处。我们坚信，对员工进行投资将会有利于我们的业务，但这并不是促使我们做出这一决定的原因。一直以来，我们提供的工资都是很有竞争力的。但我们认为，现在已经到了该要抢先一步的时候，提供不仅仅是具备竞争力的工资。我们这么做是因为，这似乎是正确的选择。
今天，我要挑战我们最大的零售竞争对手（你们知道自己是谁！），他们应该追平我们的员工福利和15美元的最低工资。赶紧做起来吧！或者你们该做到更好，把最低工资提高到16美元来反击我们。这是一种对每个人都有利的竞争。
我们为员工推出的许多其他计划都是发自内心的，也是经过思考的。我之前提到过“职业选择”计划，内容是为符合资格的学习领域中的证书或文凭支付高达95%的学费和费用，从而为我们的同事带来他们需要的事业，哪怕这种事业将让他们离开亚马逊。目前已有1.6万多名员工参与了这项计划，而且人数还在继续增加。同样，我们的职业技能项目也在关键工作技能(如简历撰写、如何有效沟通和计算机基础)方面对小时工进行了培训。去年10月，为了继续履行这些承诺，我们签约加入了特朗普总统的“对美国工人的承诺”（Pledge to America’s Workers）行动，并宣布将通过一系列创新培训计划来加强5万名美国雇员的技能。
我们的投资并不局限于现有员工，甚至并不局限于现在。为了培训明天的劳动力，我们已经承诺将投入5000万美元——包括通过我们最近宣布的“亚马逊未来工程师”（Amazon Future Engineer）计划——来支持全美各地的小学、高中和大学生接受STEM和CS教育，重点是吸引更多的女孩和少数民族从事这些职业。我们还将继续利用退伍军人的优秀才能，正在履行到2021年时雇用2.5万名退伍军人和军人配偶的承诺。通过“亚马逊技术退伍军人学徒”（Amazon Technical Veterans Apprenticeship）计划，我们正在云计算等领域为退伍军人提供在职培训。
非常感谢客户允许我们为你们提供服务，并不断挑战我们来让我们做得更好。感谢股东的持续支持，感谢世界各地所有员工的辛勤工作和开拓精神。亚马逊各地的团队都在倾听客户的声音，并代表他们四处“徘徊”！
一如以往，在此我谨附上1997年第一封股东信的副本一份。我们仍旧保持着“第一天”的心态。
此致
亚马逊公司创始人兼首席执行官
杰弗里·贝索斯
以下是这封股东信的英文全文：
To our shareowners:
Something strange and remarkable has happened over the last 20 years. Take a look at these numbers:
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 third-party 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:
Third-party sellers are kicking our first party butt. Badly.
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.
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:
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.
Intuition, curiosity, and the power of wandering
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.
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.
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.
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 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.
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 listening carefully-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.
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.
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.
Imagining the impossible
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.
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.
Failure needs to scale too
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.
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.
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.”
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!
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.
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.
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.
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.
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.
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!
As always, I attach a copy of our original 1997 letter. It remains Day 1.
Sincerely,
Jeffrey P. Bezos
Founder and Chief Executive Officer
Amazon.com, Inc.
