日本日立在2015年开发了工厂机器人，约有复印机大小，可穿过仓库地板，两只手臂在升降机上自行升高或降低，每只手臂上都有一个相机。它不仅是一个可以从架子上取下瓶子的机器人，快速而精湛地执行看似简单的任务。现在，人类和机器一起管理仓库。总有一天，这样的机器人可能完全取代仓库工人。
亚马逊也配置了仓库Kiva机器人,把货物从货架上拿走，并把货架运送给人类，将效率提高到四倍，和人类在工厂中并肩工作。机器人被严格地与人类工作人员隔离 ，一方面是为了保护人类，另一方面是为了地防止机器人混淆其工作，以严格控制机器人。
机器人可以做的越来越多 ，可以是生菜选择者、调酒师、医院搬运工等。由于机器人硬件技术升级了，具有更好且更便宜的传感器，实质上改善了机器人的“眼睛”、“指尖触摸”。
过去几年里，人工智能（AI）进步真正开始加速。在狭义AI算法中，可以过滤电子邮件垃圾邮件，或者识别Facebook照片中的脸。处理器变得更快，数据集更大，更好地学习如何改进自己的算法。IBM的沃森，在比赛中击败人类冠军的头条新闻Jeopardy，已经比诊断肺癌的医生更好了。
世界机器人“人口”迅速扩大，工业机器人的销售额每年增长约13％，这意味着机器人“出生率”每五年就会翻一番。长期以来，美国以外的制造业到新兴市场去寻用的廉价工人， 现在机器人将令生产返回到美国。很多经济学家认为，机器人和AI必将带来了一个新奇的经济趋势，发达国家和新兴市场国的经济发展比较,人工智能应用率将是一个重要指标。
Rise of the robots: What advances mean for workers
It's about the size and shape of a photocopier.
Emitting a gentle whirring noise, it travels across the warehouse floor while two arms raise or lower themselves on scissor lifts, ready for the next task.
Each arm has a camera on its knuckle. The left one eases a cardboard box forward on the shelf, the right reaches in and extracts a bottle.
Like many new robots, it's from Japan. Hitachi showcased it in 2015 and hopes to be selling it by 2020.
50 Things That Made the Modern Economy highlights the inventions, ideas and innovations which have helped create the economic world we live in.
It is broadcast on the BBC World Service. You can find more information about the programme's sources and listen online or subscribe to the programme podcast.
It's not the only robot that can pick a bottle off a shelf - but it's as close as robots have yet come to performing this seemingly simple task as speedily and dextrously as a good old-fashioned human.
One day, robots like this might replace warehouse workers altogether.
For now, humans and machines run warehouses together.
In Amazon depots, Kiva robots scurry around, not picking things off shelves, but carrying the shelves to humans for them to select things.
In this way, Kiva robots can improve efficiency up to fourfold.
Robots and humans work side-by-side in factories, too.
Factories have had robots since 1961, when General Motors installed the first Unimate, a one-armed automaton that was used for tasks like welding.
But until recently, robots were strictly segregated from human workers - partly to protect the humans, and partly to stop them confusing the robots, whose working conditions had to be strictly controlled.
With some new robots, that's no longer necessary.
Take Rethink Robotics' Baxter.
'Reshoring' trend
Baxter can generally avoid bumping into humans, or falling over if humans bump into it. Cartoon eyes indicate to human co-workers where it's about to move.
Historically, industrial robots needed specialist programming, but Baxter can learn new tasks from its co-workers.
The world's robot population is expanding quickly - sales of industrial robots are growing by around 13 per cent a year, meaning the robot "birth rate" is almost doubling every five years.
There has long been a trend to "offshore" manufacturing to cheaper workers in emerging markets. Now, robots are part of the "reshoring" trend that is returning production to established centres.
They do more and more things - they're lettuce-pickers, bartenders, hospital porters.
But they're still not doing as much as we'd once expected.
In 1962 - a year after the Unimate was introduced - the American cartoon The Jetsons imagined Rosie, a robot maid doing all the household chores. That prospect still seems remote.
The progress that has happened is partly thanks to improved robot hardware, including better and cheaper sensors - essentially improving a robot's eyes, the touch of its fingertips, and its balance.
But it's also about software: robots are getting better brains.
And it's about time, too. Machine thinking is another area where initial high expectations encountered early disappointments.
Attempts to invent artificial intelligence are generally dated to 1956, and a summer workshop at Dartmouth College for scientists with a pioneering interest in "machines that use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves".
Processors have become faster, data sets bigger, and programmers better at writing algorithms that can learn how to improve themselves.
That capacity for self-improvement worries some thinkers like Bostrom. What will happen if and when we create artificial general intelligence - a system which could apply itself to any problem, as humans can?
Will it rapidly turn itself into a superintelligence? How would we keep it under control?
That's not an imminent concern, at least. Human-level artificial general intelligence is still about, ooh, 20 years away.
But narrow AI is already transforming the economy.
For years, algorithms have been taking over white-collar drudgery in areas like book-keeping and customer service. And more prestigious jobs are far from safe.
IBM's Watson, which hit the headlines for beating human champions at the game show Jeopardy!, is already better than doctors at diagnosing lung cancer.
Software is getting to be as good as experienced lawyers at predicting what lines of argument are most likely to win a case.
'Secular stagnation'
Robo-advisers dispense investment advice.
Algorithms routinely churn out news reports on the financial markets and sports - although, luckily for me, it seems they can't yet write feature articles about technology and economics.
Some economists reckon robots and AI explain a curious economic trend.
Erik Brynjolfsson and Andrew McAfee argue there's been a "great decoupling" between jobs and productivity - how efficiently an economy takes inputs, like people and capital, and turns them into useful stuff.
Historically, better productivity meant more jobs and higher wages.
But Brynjolfsson and McAfee argue that's no longer the case in the United States. Since the turn of the century, US productivity has been improving, but jobs and wages haven't kept pace.
Some economists worry that we're experiencing "secular stagnation" - where there's not enough demand to spur economies into growing, even with interest rates at or below zero.
Technology destroying jobs is nothing new - it's why, 200 years ago, the Luddites went around destroying technology.
"Luddite" has become a term of mockery because technology has always, eventually, created new jobs to replace the ones it destroyed. Better jobs. Or at least, different jobs.
What happens this time remains debatable. It's possible that some of the jobs humans will be left doing will actually be worse.
That's because technology seems to be making more progress at thinking than doing: robots' brains are improving faster than their bodies.
Martin Ford, author of Rise Of The Robots, points out that robots can land aeroplanes and trade shares on Wall Street, but still can't clean toilets.
So perhaps, for a glimpse of the future, we should look not to Rosie the Robot but to another device now being used in warehouses: the Jennifer Unit.
It's a computerised headset that tells human workers what to do, down to the smallest detail.
If you have to pick 19 identical items from a shelf, it'll tell you to pick five, then five, then five, then four. That leads to fewer errors than saying "pick 19".
If robots beat humans at thinking, but humans beat robots at picking things off shelves, why not control a human body with a robot brain?
It may not be a fulfilling career choice, but you can't deny the logic.
Tim Harford writes the Financial Times's Undercover Economist column. 50 Things That Made the Modern Economy is broadcast on the BBC World Service. You can find more information about the programme's sources and listen online or subscribe to the programme podcast.