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7 New Robots Designed to Do Human Jobs

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Will robots take all of the jobs? A new report from Pew Research reveals that experts are divided on this topic: some think robots will displace vast numbers of workers by 2025. Others think that yes, robots will indeed take some of our jobs, but we’ll be smart enough to create new forms of work to make up for the losses. Only time will tell exactly what long term impact artificial intelligence will have on the workforce, but already, robots are being designed to do jobs only humans could before.

1. Bellhops

Starting August 20, the Aloft hotel in Cupertino, California will have a new employee. “Boltr” the robotic bellhop will independently roam the hotel’s hallways at a top speed of four mph, delivering items to customers in under three minutes. Starwood insists its robotic room service isn’t meant to replace any human employees. Instead, it is “an enhancement to our customer service,” Brian McGuinness, Starwood Hotels’ senior vice president for its Specialty Select brands, told the New York Times.

2. Tour guides

The Tate Britain museum is letting members of the public enjoy nighttime tours of the artworks without leaving the comfort of their living rooms. From their computer screens, people online can take control one of four robots that will walk around the museum and show off the galleries. Using keyboard buttons, tour members can make the robot move around or look in different directions. Art lovers, fear not: the robots are fitted with sensors that forbid them from getting too close to an artwork.

3. Fast food workers

Would you trust a robot to prepare your burger? A company called Momentum Machines is working on a machine that “does everything employees can do except better.” It is its own assembly line: slicing vegetables, cooking meat, and producing one “gourmet” burger every 10 seconds, all while providing additional sanitation and food safety. The company knows the robot will put line cooks out of work; in fact, this seems to be the goal. “The labor savings allow a restaurant to spend twice as much on high quality ingredients,” the company’s website says. To help displaced employees, Momentum Machines wants to offer them “discounted technical training” to essentially help them become technicians that maintain the robots that just took their jobs.

4. Government job screeners

If you want to work for the government, your first step may soon be enduring a long list of questions from a computer-generated interviewer. To speed the process of handing out security clearances, the National Center for Credibility Assessment is developing an avatar that would interview applicants about their past (drug use, health issues, etc). The goal of outsourcing this stuff to a machine is to save the government time and money, and an initial study found that the robots made interviewees more likely to open up about their history. The robots could also help solve a problem of gender and cultural bias in government jobs.

5. Farmers

An EU project called “Crops” is creating smart robots for crop and forestry management. Developed so far: a sweet pepper-picking robot, an apple harvesting robot, and crop-spraying robots. And for the livestock? A farm in Massachusetts uses a robot to milk its dairy cows. 

6. Librarians

Sydney’s University of Technology has a vast underground library where 325,000 books are stored. When a student wants a book, robots find it for them. The librarians actually seem quite pleased with the innovation, which they’ve dubbed the “bookBot.” The books selected for underground storage were the library’s least-read and were gathering dust and taking up valuable shelf real estate. Now they’re stored in clean galvanised steel bins, safe and secure and available with the touch of a button.

7. Pharmacists

Two hospitals at the University of California, San Francisco no longer have humans manning their pharmacies. Instead, robots receive medication orders and retrieve and package the doses. Nervous about letting a machine dole out powerful pills? At launch in 2011, the university boasted that the robots had prepared more than 350,000 doses so far without a single problem.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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iStock
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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

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