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Illustration: Rebecca Zisser/Axios
JD.com, a Chinese e-commerce gargantuan, has built a big new Shanghai fulfillment center that can organize, pack and ship 200,000 orders a day. It employs four people — all of whom service the robots.
Welcome to the creeping new age of automation. When the talk turns to Chinese Big Tech — rivals to Google, Amazon and the rest of Silicon Valley — the names usually cited are Alibaba, Baidu and Tencent.
But scrappy JD, with a respectable $58 billion market cap, is investing aggressively to be added to the pantheon.
Why it matters: This is the future. Like JD, its fierce e-commerce competition Alibaba has also built an entirely automated warehouse, showing the way for how retail will probably be done everywhere.
JD's new mantra is "retail as a service," in which it will sell the efficient methods it's developed to other companies.
Go deeper: Read the whole post.
JD.com's Shanghai warehouse for luxury goods. Photo: Steve LeVine/Axios
I am inside a 28-meter-tall, 100,000-square-foot Shanghai warehouse stacked almost to the ceiling with boxes stored one atop the other on 60,000 pallets.
Math question: How many workers are needed to process the 50,000 to 100,000 orders that go out of the building every day?
The answer, says Pujiang Pu, manager of the warehouse, owned by JD: It depends on the size of the box — small, medium or large.
This particular warehouse handles only medium-size boxes: That means 12-by-24-inches. It’s increasingly automated but still has the most employees of any warehouse in the park — 500 workers split into two shifts.
What's next: This setup is just for now, according to Pu. He says:
For now, working here is a lifestyle. Pu said on a tour today that more than two-thirds of the workers — including himself — live in dormitory rooms on the site. He’s been doing so for eight years. We asked why, and he said with a smile, “I like to keep an eye on the operation.”
The new way of politics and business. Illustration: Greg Ruben/Axios
American and Chinese corporate titans share something in common: jittery slavishness to their president, and sometimes even each other's president.
In the U.S., President Trump's tweets — sometimes even the threat of one — send powerful CEOs scrambling to announce hiring sprees, factory openings and profit repatriation.
The bottom line: Beth Bao, a strategic planning executive with JD Logistics, says the company is sometimes deliberately aligning company strategy with Belt and Road. Others are doing the same. Among the examples:
Go deeper: Read the whole post.
Shanghai scored high in awareness of smartness. Photo: Artur Widak/NurPhoto/Getty
One of the most over-used slogans of recent years has been "smart cities," the vision of a connected, Jetsons-like future of streamlined metropolises where technology smoothly manages energy use, traffic, policing and more.
The big picture: Even so, a decade after the term first gained currency, we still have no truly smart cities, according to McKinsey Global Institute via its new study of 50 selected cities around the world.
What happened: One of the problems, say the study's authors, has been that cities have focused too much on the technology and too little on humans. The study emphasized that smart phones are the door to the smart city, providing all the information at one's fingertips for health, traffic, safety and news.
Go deeper: Read full story.
Knives are out for U.S. pork in trade war (Gregory Meyer – FT)
Suicide is up in almost every U.S. state (Chris Canipe/Haley Britzky - Axios)
Watch the World Cup through VR glasses (Erin Winick - MIT Technology Review)
Drone surveillance state, unplugged (Dave Gershgorn - Quartz)
Why our working memory stops at four (Jordana Cepelewicz - Quanta)
Betty? Susie? Photo: Nicolas Asfouri/AFP/Getty
One of the biggest advances in this early stage of working artificial intelligence is facial recognition — as seen via Facebook's ability to pick out individuals across its platform, and China's skill in nabbing suspected criminals out of a city crowd.
But last year, engineers working for JD Finance in Beijing wondered where such capabilities could go next. What about animals? Was AI sufficiently advanced, for instance, to reliably distinguish one piglet from another?
Soon afterwards, a contest unfolded, pitting three teams of JD Finance engineers against one another to adapt facial recognition programs to pigs.
How will the winner be selected?
This isn't entirely a lark: The pig inquiry has its roots in a prior JD Finance study of chickens that resulted in a way to systemize feed costs for a full-size bird.