In one of the first lawsuits to address the use of live facial recognition technology by governments, a British court ruled on Wednesday that police use of the systems is acceptable and does not violate privacy and human rights. The case has been closely watched by law enforcement agencies, privacy groups and government officials because there is little legal precedent concerning the use of cameras in public spaces that scan people's faces in real time and attempt to identify them from photo databases of criminal suspects. While the technology has advanced quickly, with many companies building systems that can be used by police departments, laws and regulations have been slower to develop. The High Court dismissed the case brought by Ed Bridges, a resident of Cardiff, Wales, who said his rights were violated by the use of facial recognition by the South Wales Police. Mr. Bridges claimed that he had been recorded without permission on at least two occasions -- once while shopping and again while attending a political rally.

Police robots, thrown through a broken window, could be used to distract suspects before police enter a room. The idea is to add a distracting device that produces a loud bang and a brilliant flash to small robots already used by many US police departments. Weighing about half a kilo, Throwbots can be tossed through windows or over walls and driven around to explore building interiors with video, audio and infra-red sensors.

Facial recognition: controversial as it stands right now, facial recognition is still being introduced in a multitude of services and applications. Probably the most renowned one is Facebook's use of deep-learning-based recognition to tag (News - Alert) images uploaded to the platform. Some of the tests that are being conducted right now have facial recognition applications as part of security systems in public spaces. The purpose is to use neural networks to aid in the search of missing persons, while also quickly identify criminals and terrorists. In this case, deep learning is more than just the comparison of a face against a database, because the algorithms are capable of factoring in changes in hairstyles, minor surgeries, and even modifications due to the conditions of the place where the image is taken.

A man from Cardiff, UK, says the police breached his human rights when they used facial recognition technology, but today a court ruled that the police's actions were lawful. That is, however, hardly the end of the matter. South Wales Police has been trialling automated facial recognition (AFR) technology since April 2017. Other forces around the country are trialling similar systems, including London's Metropolitan Police. Bridges may have been snapped during a pilot called AFR Locate.

This Jan. 22, 2018, file still frame from video provided by KCBS-TV shows a Tesla Model S electric car that has crashed into a fire engine on Interstate 405 in Culver City, Calif. DETROIT – A government report says the driver of a Tesla that slammed into a firetruck near Los Angeles last year was using the car's Autopilot system when a vehicle in front of him suddenly changed lanes and he didn't have time to react. The National Transportation Safety Board said Tuesday the driver never saw the parked firetruck and didn't brake. The report raises further questions about the effectiveness of Tesla's system, which was in operation before several other crashes including two fatalities in Florida and one in Silicon Valley. Tesla warns drivers that the system is not fully autonomous and drivers must be ready to intervene.

A team of researchers at Yonsei University and École Polytechnique Fédérale de Lausanne (EPFL) has recently developed a new technique that can recognize emotions by analyzing people's faces in images along with contextual features. They presented and outlined their deep learning-based architecture, called CAER-Net, in a paper pre-published on arXiv. For several years, researchers worldwide have been trying to develop tools for automatically detecting human emotions by analyzing images, videos or audio clips. These tools could have numerous applications, for instance, improving robot-human interactions or helping doctors to identify signs of mental or neural disorders (e.g.,, based on atypical speech patterns, facial features, etc.). So far, the majority of techniques for recognizing emotions in images have been based on the analysis of people's facial expressions, essentially assuming that these expressions best convey humans' emotional responses. As a result, most datasets for training and evaluating emotion recognition tools (e.g., the AFEW and FER2013 datasets) only contain cropped images of human faces.

A robot pilot is learning to fly. It has passed its pilot's test and flown its first plane, but it has also had its first mishap too. Unlike a traditional autopilot, the ROBOpilot Unmanned Aircraft Conversion System literally takes the controls, pressing on foot pedals and handling the yoke using robotic arms. It reads the dials and meters with a computer vision system. The robot can take off, follow a flight plan and land without human intervention. ROBOpilot is a drop-in system meaning that the pilot's seat is removed and replaced with the robot.

Human "exceptionalism" is for many people an unquestioned assumption. For the religious, it is a God-given fact; for humanists, it is a celebration of our unique mental capacities.

It could eventually be used to make brain surgeries less invasive. Yoonho Kim and his colleague Xuanhe Zhao at Massachusetts Institute of Technology created the robot out of a polymer with small magnetic particles embedded throughout, meaning it can be directed using a magnet. It is coated in a self-lubricating material and is less 0.6 millimetres in diameter. The pair tested the robot on a silicone model of a human brain, which contained a substance that mimics blood. When controlled with a magnet held outside the brain, the robot could worm its way through hard-to-reach blood vessels.

A former Google engineer was charged Tuesday with stealing closely guarded secrets that he later sold to Uber as the ride-hailing service scrambled to catch up in the high-stakes race to build robotic vehicles. The indictment filed by the U.S. Attorney's office in San Jose, California, is an offshoot of a lawsuit filed in 2017 by Waymo, a self-driving car pioneer spun off from Google. Uber agreed to pay Waymo $245 million to settle the case, but the federal judge overseeing the lawsuit made an unusual recommendation to open a criminal probe. Uber considered having self-driving technology crucial to survive. Anthony Levandowski, a pioneer in robotic vehicles, was charged with 33 counts of trade secrets theft.