Monthly Archives: July 2017

7-Eleven Drone Deliveries to Rise in 2017

A dozen lucky 7-Eleven customers have already gotten to taste the possibilities of drone food delivery in Reno, Nevada. In November 2016, these customers experienced the futuristic thrill of placing 7-Eleven orders through an app and then watching a hovering delivery drone drop off their order within 10 minutes. Next year, 7-Eleven plans to expand on such drone deliveries in partnership with a company calling itself the “Uber of drone delivery.”

That self-proclaimed “Uber of drone delivery” is not a tech giant such as Amazon or Google, but a delivery drone startup called Flirtey. The startup aims to beat its bigger rivals to the punch by working closely with regulators and large companies around the world to expand its early foothold in the drone delivery market. In the long term, Flirtey is betting that its delivery drones can deliver more convenience at a similar price point as traditional drones.

“Flirtey’s pricing is comparable to current last-mile delivery services,” says Matt Sweeney, CEO of Flirtey. “So Flirtey is a faster and more convenient service at a price point competitive with traditional delivery prices.”

The idea of making drone deliveries as cheap for customers as traditional delivery services is easier said than done. Delivery drones also face certain hurdles in making successful deliveries to customers spread across a wide delivery area on a timely schedule. For example, most smaller drones have a fairly limited range before they need to land and recharge their batteries. Delivering packages to homes or businesses surrounded by tall trees and power lines also poses its own challenge.

Why Amazon Dreams of Flying Warehouses

Amazon gets to play full-time Santa Claus by delivering almost any imaginable item to customers around the world. But the tech giant does not have a magical sleigh pulled by flying reindeer to carry out its delivery orders. Instead, a recent Amazon patent has revealed the breathtaking idea of using giant airships as flying warehouses that could deploy swarms of delivery drones to customers below.

Many patent filings related to new technology often indulge in fantastical flights of fancy. But it’s worth taking a moment to appreciate some of the truly wilder scenarios being imagined within this Amazon patent filing. One scene envisions human or robot workers going to work busily sorting packages aboard airships hovering 45,000 feet above major cities. Another scene imagines the airship’s kitchen whipping up hot or cold food orders that would be loaded onto delivery drones for delivery within minutes.

A third scene anticipates swarms of delivery drones dropping off orders of food or t-shirts to people attending concerts or sports games. Amazon’s patent filing even considers how the airships could fly at much lower altitudes to act as giant billboards or megaphones that advertise and sell items directly to the crowds below.

There is a method to the madness. Amazon currently aims to attract customers with the promise of getting almost anything—clothing, electronics and groceries—delivered within days or even hours. It is currently racing against Google and delivery drone startups such as Flirtey to become the go-to service for customers who expect speedy deliveries of their purchases. The Amazon patent idea for an “airborne fulfillment center” may never become reality, but it speaks to the company’s ambition to enable an “instant gratification” world for customers.

At its heart, Amazon’s idea for flying warehouses aims to solve two problems. First, a mobile warehouse flying high above cities would theoretically enable Amazon to move its packages and products even closer to customers’ homes and businesses and shorten the time needed for last-mile deliveries. The company could even strategically move certain flying warehouses to different locations depending on temporary demand (such as crowds gathering at stadiums for sporting events or concerts).

Second, the flying warehouse scheme tries to tackle the range problem for delivery drones. The small delivery drones being tested by Amazon have fairly limited range of approximately 10 miles (or 20 miles roundtrip). That poses a challenge for Amazon’s Prime Air service, which recently began its first deliveries near Cambridge, UK with the promise of delivering packages within 30 minutes.

IBM’s Watson Replaces 34 ‘White-Collar’ Employees at Japanese Insurance Company

The impact AI and robotics is having on repetitive manual labor is evident — automobile assembly lines and Amazon’s fulfillment centers are just two examples. But many white-collar jobs are similarly repetitive; they can be broken down into steps and decisions that a machine can easily learn.

The bad news is that jobs have been, and will be, eliminated. By 2021, AI systems could gobble up some 6 percent of U.S. jobs, according to a report from Forrester Research. The World Economic Forum predicts advances in AI could eliminate more than 7 million jobs in 15 of the world’s leading economies over several years.

But here’s the upside: Handing repetitive tasks to machines might free us up for higher-level tasks. The same WEF report notes that AI will create 2 million new jobs in computer science, engineering and mathematics. And leaders from tech giants like Google, IBM and Microsoft have said AI will amplify human abilities rather than fully replace us. Instead of sweating time-consuming repetitive tasks, computers will, perhaps, free us up to tackle challenges that require a human touch.

For example, an AI company called Conversica built a system that sends messages to sales leads to get initial conversations started and gauge interest. The most promising leads are then sent to a salesperson to close the deal. IBM’s Watson can dig through medical data and images to find signs of cancer, but the final diagnosis is still in the warm, fleshy hands of a human.

Ovum, a firm that keeps its thumb on the pulse of tech trends, expects AI to be the biggest disruptor for data analytics in 2017. Forrester predicts 2017 will be the year “big data floodgates open,” with investments in AI tripling.

Time will tell if AI lives up to these expectations; in the meantime you can use this helpful tool to determine the likelihood of a computer taking your job.

21st Century Camouflage Confuses Face Detectors

When it comes to disguises, silly mustaches and fake noses won’t cut it anymore.

As facial recognition capabilities grow more sophisticated, cameras and algorithms can to do more with less. Even grainy images, like those you might find on a gas station surveillance camera, can hold enough information to match a face to a database. But there are ways to hide. 

Gathering Knowledge

Your face is garnering a lot of interest these days. Police departments use facial recognition systems to identify criminals. Facebook knows your friends’ faces. Facial recognition is being incorporated into billboards to display ads based on the sex of the person looking at them.

In the not-so-distant future, your face might replace your wallet—a smile will serve as your identification card and credit card. Amazon plans to eliminate the checkout line at its new brick-and-mortar grocery store concept, Amazon Go, in Seattle. How? According to the company’s website:Our checkout-free shopping experience is made possible by the same types of technologies used in self-driving cars: computer vision, sensor fusion, and deep learning. Our Just Walk Out Technology automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart.

How computer vision will work at Amazon Go isn’t exactly clear, but your face may play an important role in the shopping experience. Right now, the store is only open to Amazon employees, but it is expected to open to the public sometime in 2017.

Given all this attention, there may come a day when we want to avoid this kind of computer recognition.

Adam Harvey, a Berlin-based artist, is developing a line of clothing and accessories aimed at disrupting facial recognition software by fighting fire with fire. His forthcoming HyperFace project is a set of wearable patterns that overloads facial recognition software with images of faces to distract from the real person hiding behind it, exploiting weaknesses in the technology.

Faces In A Crowd

A facial recognition system keys in on dominant features and parses them into numeric sequences that are calculated according to the parameters of the algorithm. By crunching the numbers, it can to determine whether it’s “seeing” a human being or not, and who that face belongs to. Some algorithms need no more than 100 pixels—2.5 percent of an Instagram photo—to identify 78 relevant facial characteristics, said Harvey in a 2016 talk at the Chaos Communication Congress.

Harvey’s designs are collages that mimic basic facial features, sending a barrage of information that obscures a real face. Theoretically, worn as a shirt, scarf or shawl, patterns (pictured above) should protect your identity from nosy algorithms.

HyperFace is an extension of Harvey’s NYU thesis project to thwart face detectors with makeup and hair gel. In addition to hairstyles that covered the face, concealing the “T-zone”—the area around the bridge of the nose and eyes—seems to be most important.