An army of robots is on the move.
一大波机器人正在步入我们的生活。
In warehouses, hospitals and retail stores, and on city streets, industrial parks and the footpaths of college campuses, the first representatives of this new invading force are starting to become apparent.
“The robots are among us,” says Steve Jurvetson, a Silicon Valley investor and a director at Elon Musk’s Tesla and SpaceX companies, which have relied heavily on robotics. A multitude of machines will follow, he says: “A lot of people are going to come in contact with robots in the next two to five years.”
在仓库、医院、零售店中、城市街道上、工业园区和大学校园内，机器人这一新型「入侵力量」正开始成为越来越常见的现象。硅谷投资人、Tesla 和 SpaceX 公司主任 Steve Jurvetson 说：“机器人就在我们身边。”Jurvetson 所在的这两家公司都高度依赖机器人。大批的机器将会出现，他说，许多人将会在未来 2-5 年接触到机器人。
The arrival of the robots — and their potentially devastating effect on human employment — has been widely predicted. Now, the machines are starting to roll or walk out of the labs. In the process, they are about to tip off a financing boom as robotics — and artificial intelligence — becomes one of the hottest new markets in tech.
机器人的到来和它对人类就业潜在的摧毁性影响，已经成为广为人知的预测。现在，这些机器正开始转动轮子或迈开脚步走出实验室。在这个过程中，他们正悄然成为投资热潮，因为机器人和人工智能成为了科技领域最热门的新兴市场。
After growing at a compound rate of 17 per cent a year, the robot market will be worth $135bn by 2019, according to IDC, a tech research firm. A boom is taking place in Asia, with Japan and China, which is in the early stages of retooling its manufacturing sector, accounting for 69 per cent of all robot spending.
根据 IDC 科技调查公司的报告显示，在以 17% 年复利率增长的情况下，到 2019 年，机器人市场总值将达到 1,350 亿美元。这一繁盛景象将出现在亚洲，日本和中国正处于重新装备制造部门的早期阶段，这两个国家的花费将占据全球机器人消费总额的 69%。
Although the amount of money flowing into a new robotics industry is still at a relatively early stage, all the lead indicators of the innovation economy are pointing up. Patent filings covering robotics technology — one sign of the expected impact — have soared. According to IFI Claims, a patent research company, annual filings have tripled over the past decade. China alone accounted for 35 per cent of robot-related patent filings last year — more than double nearest rival Japan.
尽管这些资金流入新兴的机器人领域还处于相对早期的阶段，但这一创新经济的所有先行指标正在逐渐显露。覆盖机器人技术的专利申请数量——一个预期影响的标志——正在飙升。一家专利调查公司 IFI 指出，年度专利申请在过去十年中翻了三倍。在去年，中国一个国家机器人相关专利申请量就占据了 35%，是其对手日本的两倍。
In another sign of the expected boom, venture capital investments more than doubled last year to $587m, according to research firm CB Insights.
另一个预期繁荣的标志是，根据调查公司 CB Insights 资料显示，机器人风险投资金额已经超过去年的两倍，达到 5.87 亿美元。
Other investors are also piling in, says Manish Kothari of SRI International, a Silicon Valley research and development lab that has spun off robot companies. From private equity investors looking to build portfolios of robot investments, to new “incubators” such as Playground, started by former Google robotics chief Andy Rubin, the investment options have been proliferating rapidly.
其它投资者也开始涌入，斯坦福国际咨询研究所（SRI International）的 Manish Kothari 说，这家位于硅谷的研究发展实验室已经衍生出了机器人公司。从构建机器人投资组合的私人股权投资者，到 Playground 这样的新的孵化器，投资选择正在快速激增。
到2019 年，整个机器人市场的价值将达到 1,350 亿美金
But in many cases, the amounts being invested still seem disarmingly modest. Like other disruptive technologies, the seeds of this revolution can be seen in start-ups that operate on a shoestring but have grandiose aims.
然而在许多案例中，投资数量好像仍然非常谨慎。像其它颠覆性技术一样，这场变革萌芽于依靠零星资本运行的创业公司，但这些创业公司有着非常宏大的目标。
They include companies such as Dispatch, a Silicon Valley company that is testing an autonomous delivery vehicle — a smart-box on wheels — on two college campuses in the US. The start-up has raised only $2m but is riding the wave in collapsing costs of sensors and advances in artificial intelligence that are making autonomous machines a reality.
Dispatch 就是这样的一家公司，这家位于硅谷的公司正在美国校园内测试一台自动送货工具（带有轮子的智能盒子）。这家创业仅仅募集到 200 万美元，但是它们赶上了传感器成本骤降和人工智能（这使自驾机器成为可能）急剧发展的浪潮。
“There is an exponential pace of improvement in hardware and machine learning algorithms,” says co-founder Uriah Baalke. “The computational power required has gone down a lot.” The result is a new class of machines that can operate by themselves in human space, the advance guard of a new robot industry.
「硬件和机器学习算法正在以指数级别的速度发展，」 Dispatch 的联合创始人 Uriah Baalke 说。「对于计算能力的要求已经下降了很多。」这产生的结果就是能在人类环境中自我运行的新级别机器，这种机器是新兴机器人产业的先头军。
Until now, most robots have taken the form of expensive, high-precision industrial machines. Usually found operating in protective cages on automobile assembly lines, they have carried out preprogrammed tasks, with no need or scope to adapt to changing conditions.
直到现在，大多数机器人依然采用高成本、高精密工业设备的形式。通常，它们会在汽车装备流水线的保护箱里执行预编程序任务，没有需要或没有多余空间根据条件进行调整。
Your opinionThe cheaper, flexible machines that are emerging are designed to be more adaptive. From driverless cars and drones to the “cobots” that work alongside humans in industrial settings, they try to sense and adapt to their surroundings. Like Tug (a robot that moves supplies around hospitals), Savioke (which handles deliveries to hotel rooms) and Locus Robotics (which operates in warehouses), they are moving into the service industries. In industrial settings — still the main venue for robot investment — they are moving out of the cages and into a far wider range of roles.
更便宜、更灵活的新型机器更具有适应性。从无人驾驶汽车和无人机再到那些在工业环境中与人类协同工作的「协同机器人（cobots）」，机器人正试图对周围环境进行感知和适应。像 Tug（一个在医院内运送物资的机器人）、Savioke（一个向酒店房间送货的机器人）和 Locus Robotics （在库房中工作）这些机器人正在进入服务产业。在仍然是机器人投资主场的工业环境中，机器人正离开保护箱的限制，开始扮演越来越多的角色。
Like the arrival of PCs, the new era promises to take the technology into many more areas of working life. “The traditional industrial robots are mainframes — what we’re doing are PCs,” says Scott Eckert, chief executive of Rethink Robotics, a US company whose robots help with packing or tend machines. Rethink says that the all-in cost of its Sawyer robotic arm amounts to about $1 an hour, a price at which many of the jobs that have been beyond the reach of automation could be affected.
就像个人电脑（PC） 时代的到来一样，新机器人纪元有希望把机器人技术带入到我们工作生活的更多领域。Rethink Robotics 公司的首席执行官 Scott Eckert 说「传统工业机器人就像大型主机，而我们正在做的机器人就是 PC 机」。这家公司的机器人能够帮助包装或养护机械。Rethink 描述它们的产品 Sawyer 机器人手臂的总成本大约为 1 美元/小时，这个价格可能影响到很多自动化还未能触及到的工作领域。
2015 年机器人风投资金额达到 5.87 亿美元，是2014 年的两倍
The technology advances behind this wave of innovation have come together remarkably quickly. Funding over the past five years by Darpa, the research arm of the US defence department, has brought breakthroughs in mechanical areas such as robotic limbs, says SRI International’s Mr Kothari.
这波浪潮背后的技术进展以相当快的速度一起爆发。斯坦福国际咨询研究所的 Kothari 先生说，过去 5 年在 DARPA 资金的支持下，美国国防部下面的研究机构在机器人肢体这些机械领域已经取得很多突破。
But the biggest advances have come in software. Improvements in computer vision, for instance, have made possible many companies like Dispatch, whose machines rely on being able to “see” the world around them, says Chris Dixon, a partner at venture capital firm Andreessen Horowitz.
但最大的进步来自于软件。风险投资公司 Andreessen Horowitz 的一位合伙人 Chris Dixon 说，例如，计算机视觉的发展催生了 Dispatch 这样的许多公司，这些公司的机器就是依靠计算机视觉「看」周围的世界。
Machine learning algorithms, which are designed to adapt through an endless process of trial and error, play the biggest part in teaching robots how to navigate a world beyond the normal rules-based systems that computers are designed to handle.
机器学习算法通过不断的反复试验进行适应性调整。在教授机器人打破计算机设计的常规规则导向系统、学习如何自主运行上，机器学习算法起到非常大的作用。
全球机器人专利申请量
“You won’t have to programmatically tell it what to do; it will figure it out,” says Vinod Khosla, a venture capitalist who has backed robot companies in markets including agriculture and healthcare. “Today, it’s really dumb intelligence — but that will change quickly.”
一位投资了数家农业、医疗健康机器人公司的风险投资人 Viod Khosla 说，「你不再需要编程告诉机器人做什么了，它会自己明白。如今，机器人确实还很低能，但进步的速度非常快。」
When it comes to designing the machines for this emerging industry, most robot entrepreneurs and investors are following a similar formula.
但说到为这一新兴产业设计机器时，大部分机器人企业和投资人都遵循相似的准则。
One element is to build low-cost machines that tackle specific tasks, rather than attempt to create general-purpose machines — let alone fully humanoid robots — that try to take on too much.
其中一个要素是设计完成特定任务的低成本机器，而不是试图创造广泛应用的机器，更不要说完全的人形机器人了，这种机器人承担成本更高。
The goal is to build “single-purpose robots that do one thing very well”, says Dmitry Grishin, a Russian who recently raised a $100m fund to invest in robots and other hardware. If they succeed, these machines quickly lose their status as “robots” and become more part of the fabric of everyday life, he says — like automated vacuum cleaners or cash machines.
最近刚筹得 1 亿美金准备投资机器人和其他硬件的俄罗斯大亨 Dmitry Grishin 说设计目标是为了建立「在一件事上做的很好的单用机器人」。如果成功了，这些机器就摆脱了「机器人」形象，成为我们日常生活的一部分，他说就像自动真空吸尘器或自动提款机一样。
Another design feature of many of the early robots is to operate alongside people, making humans more productive rather than replacing them altogether. Many of these robots, for instance, hand over decision-making to a human operator when they encounter situations they cannot understand or navigate.
早期机器人的另一个设计特征是陪同人类工作，让人类工作效率更高，而不是取代人类。例如，很多这样的机器人会把它们无法理解或驾驭的情况交给人类操作员做决策。
“The truth is, anyone who works in robotics knows the limitations of what they’re working with, and they’re pretty extensive,” says Mr Kothari. Robot companies also want to keep “the human in the loop” because they believe it will make their machines more socially acceptable and less threatening, he says. Most people operating in the robot industry say humans will have an important role to play in directing the machines for decades to come.
Kothari 先生说「事实上，制作机器人的人都知道与人类一起工作的机器人的缺陷，而且这是相当广泛的问题。」机器人公司其实也想要保留「人类在决策圈内」，因为他们相信这能让他们的产品更容易被社会接受、有更少的威胁。很多经营机器人产业的人都说在接下来的数十年中，人类在指导机器人中将扮演非常重要的角色。
That does not change the long-term threat to jobs, however. “There isn’t a single mechanical or physical thing a human will be able to do better than a robot,” says Tesla and SpaceX’s Mr Jurvetson.
然而，这并未改变机器人对人类工作的长期威胁。特斯拉和 SpaceX 公司的 Jurvetson 先生说，「在机械事物或物理事物上，将没有一件人类比机器人做的更好的事情。」
Another feature the robot makers are counting on is to be able to use the learning capabilities of their initial products to achieve rapid improvements and gain an advantage over rivals that are slower to get their machines into the market.
另一个机器人制作者应该关注的特征是能够使用他们初始产品的学习能力从而获得对机器人的快速改进，如此在对抗产品市场化慢的对手上就能获得优势。
“Once you ship the device, you can apply more and more intelligence and machine learning,” says Mr Grishin, the Russian robot investor. The trick, he says, will be to find a task that the relatively dumb machines are able to handle, then use knowledge gained in the field to rapidly add to their capabilities and usefulness. “First put them in consumers’ hands, then learn from their behaviour.”
这位俄罗斯投资者 Grishin 先生就说，「一旦你出售了设备，你能应用越来越多的智能和机器学习。」他说里面的窍门是，你将能找到一个相对低能机器能够处理的任务，然后将从这一领域获得的知识快速加入到新一代机器的性能和有效性中。「首先把产品交到顾客手中，然后从它们的行为中再学习。」
This is the secret weapon that all robot companies rely on. “Everything gets better over time,” says Mr Jurvetson. “This is happening in almost every hardware product: they are becoming minimal vessels for software.”
这是机器人公司依赖的秘密武器。「每件事会随着时间变得越来越好。」Jurvetson 先生说，「硬件产品中基本上都是这样：硬件产品正在成为软件的毛细血管，容纳着软件的发展。」
This technological shift has set traditional robotics leaders in Japan and Germany against nascent industries in countries such as the US and China.
这一技术转变已经让传统的日本、德国机器人领导者与新生的美国、中国这样国家的机器人产业对立起来。
“Right now, the US is definitely the leader” when it comes to software, says Mr Grishin. He adds, however, that the hardware manufacturing expertise of China makes that country a contender, particularly since robotics has become a national priority. As a result, the rise of a new robot industry is about to trigger a global race for leadership.
在软件上，Grishin 先生说，「现在美国无疑是领导者」。然而，他补充道，中国的硬件制造专业性使其成为了一大竞争者，特别是机器人已经成为中国优先发展的产业。最终结果是，新兴机器人产业的崛起即将触发全球领导权的竞争。
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