It’s all but certain that human workers in factories and fulfillment centers are a dying breed. The last nail in their coffin might be a new robotic arm from a company called RightHand Robotics that’s not only able to teach itself how to pick up objects it’s never handled before, but it can also share what it learns with other robot arms around the world.
To ensure its new RightPick system can continuously adapt to new products all the time, RightHand Robotics developed a multi-fingered gripper with both an extending suction tool in the middle, and a camera that’s able to analyze objects and determine the best strategy for grasping and holding any object. Images from the camera are instantly processed by an algorithm developed by RightHand that tells the gripper what combination of fingers it should use, and if activating the suction tool is necessary. The system can also take advantage of machine learning techniques to automatically refine and tweak that algorithm as it encounters and learns to handle unfamiliar products.
The new skills that one RightPick system learns on the job can also help improve RightPick setups at other factories and fulfillment centers, as the robot arms remain connected to a cloud server at all time, sharing their collective knowledge to help improve each one’s capabilities. This connectivity also allows the company’s engineers and developers to remotely connect to one of the arms if it’s having an especially hard time adapting to a new object, and needs to be taught how to properly handle it.
Amazon’s Robot War Is Spreading
Video - A slew of new automation specialists appear on the warehouse battlefield.
What that means for warehouse humans is an open question. There were 939,000 people working in the industry in February, up 44 percent over the past 10 years, according to data from the U.S. Bureau of Labor Statistics. The rise of e-commerce has created a need for more hands to pick items and pack boxes. Seattle-based Amazon.com Inc.’s rapid shipping times have taught customers to expect goods on their doorstep in two days or less, fueling a warehouse boom as retailers scramble to amass distribution hubs closer to their shoppers.
Logistics firms can have a hard time hiring enough people, particularly during peak shopping seasons. Adding robots should ease some of the seasonal shortages, and may make the work less physically demanding. Working conditions at U.S. warehouses are often scrutinized for their grueling nature: Pickers complain of exhausting shifts, sometimes in oppressive heat or biting cold. Many of the jobs are temporary, fluctuating with the shopping calendar.
In the logistics business, smarter warehouse bots will likely reduce the number of people it takes to run a fulfillment center.
“I don’t think people are investing in automation because of a near-term labor shortage,” said Karl Siebrecht, CEO at Flexe, a Seattle-based company that bills itself as the Airbnb of warehouse space. “It’s about improving productivity. Fundamentally, that means people will be replaced.”
NASA’s scientists formed a club to dream up uses for AI like self-replicating robots and harpooning comets
“We have a little skunkworks project here at JPL that we call ‘AI moonshots,’ which has nothing to with the moon,” JPL AI head Steve Chien tells Quartz. “It has to do with a bunch of AI people thinking about ‘What are ways we can have tremendous impact on NASA’s mission?'”
Chien says they’ve discussed concepts like robots that can convert near-Earth objects like asteroids into antennas; robots that self-replicate by using found materials to 3D-print new robots; autonomous exploration of still-undiscovered Planet 9; and even hitchhiking on passing comets.
DARPA X-Plane completes initial demos, eyes full-scale flight in 2018
Video The US Defense Advanced Research Projects Agency's (DARPA's) LightningStrike vertical take-off and landing (VTOL) X-Plane programme has completed an initial flight demonstration phase with a scale model. DARPA said Wednesday the subscale X-Plane model demonstrated auto takeoff, sustained hover, directional and translational control, waypoint navigation and auto landing functions during flight tests that began in March 2016. That test run is now over and officials will next focus on a full-scale system demonstration.
Carl Schaefer, Aurora's programme manager for XV-24A, said the SVD is a 325 lb (147.4 kg), lithium battery powered scale model with a 10.7 ft (3.2 m) wingspan, capable of flying at 100 kt. "It did validate our aerodynamic approach to this," he said of the scale model testing.
Bagai said the full-scale model is expected to be tested at speeds of 300-400 kt, or twice as fast as contemporary helicopters.
Notably, the effort hopes to advance electrical engines for aircraft, although it will take a hybrid approach for the upcoming full-scale model. It will use Rolls-Royce's AE 1107C turboshaft engine to power three Honeywell one-megawatt electric distributed propulsion (EDP) generators that drive 24 ducted fans on the wings and the canards, according to Mark Wilson, chief operating officer for Rolls-Royce North American Technologies (Liberty Works).
Carnegie Mellon AI Takes On Chinese Poker Players
PITTSBURGH, April 5, 2017 — A version of Carnegie Mellon University’s Libratus, which in January became the first artificial intelligence to defeat top poker pros at Heads-up, No-Limit Texas Hold’em, will play six top Chinese players for a $290,000 winner-take-all purse.
The 36,000-hand exhibition featuring the different AI, named Lengpudashi or “cold poker master,” will be April 6-10 on the island province of Hainan, China.
Google says its AI chips smoke CPUs, GPUs in performance tests
Tensor Processing Unit (TPU), a chip that is designed to accelerate the inference stage of deep neural networks.
Google tested the chips on six different neural network inference applications, representing 95 percent of all such applications in Google’s data centers. The applications tested include DeepMind AlphaGo, the system that defeated Lee Sedol at Go in a five-game match last year.