Robots in the work place can perform hazardous or even 'impossible' tasks; e.g., toxic waste clean-up, desert and space exploration, and more. AI researchers are also interested in the intelligent processing involved in moving about and manipulating objects in the real world.
Facebook is certainly a high-tech company, but it's not one you would necessarily associate with robots. However, as the firm revealed today, that's exactly where its researchers are looking next -- trying to see how experiments in robotics can further its work in AI. A lot of firms, including Google, Nvidia, and Amazon, use robots as a platform to explore avenues of AI research. Controlling robots is, in many ways, trickier than challenges like playing board games and video games. With these latter tasks, researchers have access to simulated game environments, which allows AI agents to play and learn at accelerated speeds.
The process, known as deep learning, is already being used in many applications, like enabling computers to understand speech and identify objects so that a self-driving car will recognize a stop sign and distinguish a pedestrian from a telephone pole. In medicine, Google has already created systems to help pathologists read microscope slides to diagnose cancer, and to help ophthalmologists detect eye disease in people with diabetes. "We have some of the biggest computers in the world," said Dr. Daniel Tse, a project manager at Google and an author of the journal article. "We started wanting to push the boundaries of basic science to find interesting and cool applications to work on." In the new study, the researchers applied artificial intelligence to CT scans used to screen people for lung cancer, which caused 160,000 deaths in the United States last year, and 1.7 million worldwide.
DETROIT - Ford revealed details of its long-awaited restructuring plan Monday as it prepared for a future of electric and autonomous vehicles by parting ways with 7,000 white-collar workers worldwide, about 10 percent of its global salaried workforce. The major revamp, which had been underway since last year, will save about $600 million per year by eliminating bureaucracy and increasing the number of workers reporting to each manager. In the U.S. about 2,300 jobs will be cut through buyouts and layoffs. About 1,500 have left voluntarily or with buyouts, while another 300 have already been laid off. About 500 workers will be let go starting this week, largely in and around the company's headquarters in Dearborn, Michigan, just outside Detroit.
TEHRAN - Iran has quadrupled its production of low-enriched uranium amid tensions with the U.S. over Tehran's unraveling nuclear accord, two semi-official news agencies reported Monday, an announcement just after President Donald Trump warned Iran it would face its "official end" if it threatened America again. While the reports said the production is of uranium enriched only to the 3.67 percent limit set by the 2015 nuclear deal that Tehran reached with world powers, it means that Iran soon will go beyond the stockpile limitations established by the accord. This follows days of heightened tensions sparked by the Trump administration's deployment of bombers and an aircraft carrier to the Persian Gulf over still-unspecified threats from Iran. While Trump's dueling approach of flattery and threats has become a hallmark of his foreign policy, the risks have only grown in dealing with Iran, where mistrust between Tehran and Washington stretch back four decades. So far this month, officials in the United Arab Emirates alleged that four oil tankers sustained damage in a sabotage attack; Yemeni rebels allied with Iran launched a drone attack on an oil pipeline in Saudi Arabia; and U.S. diplomats relayed a warning that commercial airlines could be misidentified by Iran and attacked, something dismissed by Tehran.
A recent hardware test of NASA's robotic assistant, 'Astrobees,' takes a new wave of space-bound autonomous helpers one step closer to reality. According to NASA, this month astronaut Anne McClain ran a hardware test of the robot, named'Bumble,' one of three robotic assistants launched to the International Space Station (ISS) on April 15. Scientists hope Bumble will carry out an array of housekeeping tasks like monitoring equipment and keeping inventory of supplies that NASA hopes will free up its astronauts to perform other more critical tasks relating to with their missions and experiments. Astrobees are just one of many robotic applications from NASA who is also studying the use of'soft' robotics that replace traditional hardware with malleable plastics'Astrobee will prove out robotic capabilities that will enable and enhance human exploration,' said Maria Bualat, Astrobee project manager at NASA's Ames Research Center in a statement. 'Performing such experiments in zero gravity will ultimately help develop new hardware and software for future space missions.'
Facebook isn't often thought of as a robotics company, but new work being done in the social media giant's skunkworks AI lab is trying to prove otherwise. The company on Monday gave a detailed look into some of the projects being undertaken by its AI researchers at its Menlo Park, California-based headquarters, many of which are aimed at making robots smarter. Among the machines being developed are walking hexapods that resemble a spider, a robotic arm and a human-like hand complete with sensors to help it touch. Facebook has a dedicated team of AI researchers at its headquarters in Menlo Park, California that are tasked with testing out robots. The hope is that their learnings can be applied to other AI software in the company and make those systems smarter.
Facebook is trying to develop artificial intelligence models that will allow robots–including walking hexapods, articulated arms, and robotic hands fitted with tactile sensors–to learn by themselves, and to keep getting smarter as they encounter more and more tasks and situations. In the case of the spider-like hexapod ("Daisy") I saw walking around a patio at Facebook last week, the researchers give a goal to the robot and task the model with figuring out by trial and error how to get there. The goal can be as simple as just moving forward. In order to walk, the spider has to know a lot about its balance, location, and orientation in space. It gathers this information through the sensors on its legs.
Hailo, an AI startup based in Israel, has released its initial chip that the company claims is "the world's top performing deep learning processor," with the Hailo-8 chip claimed to deliver 26 tera-operations pers second (TOPS), while consuming only a few watts of power. If true, that would certainly put it near or at the top of its class in performance for edge applications in areas like self-driving cars, drones, smart appliances, and virtual/augmented reality devices. The challenge in these edgey environments has always been to get AI processors with the requisite performance for these applications but consuming only the small amounts of power available in these settings. In fact, Hailo is positioning its new offering as chip that "enables edge devices to run sophisticated deep learning applications that could previously run only on the cloud." However, doesn't mean Hailo-8 is as powerful as a top-of-the-line inference GPU for the datacenter.
One example is Steward Health Choice Network's (SHCN) Health Plan Division, a division of Steward Health Care Systems. During the past two years, using RPA has led to drastic improvements in productivity for SHCN. Within 30 days of implementing its first RPA script, SHCN began realizing an ROI. Since that time, the labor automation -- Foxtrot RPA has processed 4.5 million transactions, with a cost avoidance of $2.75 million for the $1.4 billion organization. SHCN's Health Plan Division's efficiency gains illustrate what RPA can deliver to the healthcare industry.
A fleet of miniature autonomous cars has shown how driverless cars improve traffic flow by at least 35% when programmed to work together. Researchers at the University of Cambridge, UK, tested how 16 miniature robotic cars driving around a two-lane track reacted when one of the cars on the inner lane stopped. When the cars were in cooperative mode, they alerted the rest of the cars to slow down as it neared the immobile car, allowing the inner lane cars to quickly pass it. However, when they were not driving cooperatively, traffic built up as cars had to stop and wait for a safe moment to overtake the stopped car. "Autonomous cars could fix a lot of different problems associated with driving in cities, but there needs to be a way for them to work together," said co-author of the study Michael He, an undergraduate student at St John's College who designed the lane-changing algorithms for the experiment.