Artificial-intelligence startup Pearl Inc. is using machine learning to analyze dental imagery, helping insurers pinpoint whether the same X-ray was used for more than one patient and whether a procedure was necessary.
The West Hollywood, Calif., company said its system has found thousands of cases in which dentists have used the same X-rays or other images to bill insurers for multiple patients.
The algorithm lets robots find the shortest route in unfamiliar environments, opening the door to robots that can work inside homes and offices.
The news: A team at Facebook AI has created a reinforcement learning algorithm that lets a robot find its way in an unfamiliar environment without using a map. Using just a depth-sensing camera, GPS, and compass data, the algorithm gets a robot to its goal 99.9% of the time along a route that is very close to the shortest possible path, which means no wrong turns, no backtracking, and no exploration. This is a big improvement over previous best efforts.
Why it matters: Mapless route-finding is essential for next-gen robots like autonomous delivery drones or robots that work inside homes and offices. Some of the best robots available today, such as Spot and Atlas made by Boston Dynamics and Digit made by Agility Robotics, are packed with sensors that make them pretty good at keeping their balance and avoiding obstacles. But if you dropped them off at an unfamiliar street corner and left them to find their way home, they’d be screwed. While Facebook’s algorithm does not yet handle outside environments, it is a promising step in that direction and could probably be adapted to urban spaces.
Self-driving cars being tested in Providence, Rhode Island, navigate city streets, with humans taking control occasionally. But the vehicles are sometimes flummoxed by what their sensors see.
British roboticist Peter Scott-Morgan doesn’t want you to see him as a man who died from a neurodegenerative disease. He wants to become Peter 2.0 – the most advanced cyborg ever.
There’s an extensive list of medical devices already helping him breathe, feed, and communicate; those technologies are set to grow in the near future. But, according to Scott-Morgan, this isn’t about staving off death; it’s about evolving.
By Rohit Talwar, Steve Wells, Alexandra Whittington, and Maria Romero
As artificial intelligence (AI) revolutionises work as we know it, how will the software testing and security industry be impacted?
The robots are coming: “Lock up your knowledge and protect your job at all costs!” The apocalyptic warnings are starting to flow of how artificial intelligence (AI) and robotics combined with other disruptive technologies could eliminate the need for humans in the workplace. Equally sceptical voices are rubbishing the idea that anything drastic will happen, citing previous industrial revolutions as proof that new jobs will emerge to fill any gaps created by the automation of existing ones. In practice, no one really knows how quickly AI might eliminate jobs or what the employment needs will be of the future businesses and industries that have not yet been born.
But the future is not black and white. Aside from the potential to take (and make) jobs, AI might also transform jobs. Below, we share a list of some critical job roles that could be transformed or eliminated completely by the use of AI and robotics over the period from 2020 to 2030. The automation of the following six jobs would bring new opportunities to the software testing world, but could also change it in other possibly in unexpected ways.
LONDON (Reuters) — British police are to start operational use of live facial recognition (LFR) cameras in London, despite warnings over privacy from rights groups and concerns expressed by the government’s own surveillance watchdog.
First used in the capital at the Notting Hill carnival in 2016, the cameras will alert police when they spot anyone on “wanted” lists.
“The use of live facial recognition technology will be intelligence-led and deployed to specific locations in London,” the city’s Metropolitan Police said in a statement on Friday.
Helsinki-based neurotech startup NextMind unveiled a compact brain-sensing wearable device that delivers real-time device control using just a person’s thoughts. It captures data from the electrical signals created by the user’s neural activity in the visual cortex, and using machine learning algorithms, transforms that output into a signal that can control a computer, AR/VR headset or any device on the Internet of Things.
The lightweight device fits into the back of a cap or headband, and rests gently on the user’s head. NextMind offers a totally new way of interacting with VR and AR environments. It is designed for ‘wear and play’ with no training required making it ideal for gaming. Users have their brain directly connected to the digital world, bypassing their physical body and creating a fully immersive experience.
RealDoll’s flagship Harmony sex robot was paraded at the AVN Adult Entertainment Expo at Las Vegas’ Hard Rock Hotel and Casino. It is capable of holding conversations with people.
Tech giant Apple has acquired Xnor.ai, an artificial intelligence startup that came from Microsoft co-founder Paul Allen’s research lab. The acquisition suggests that Apple may be planning to Xnor.ai’s machine learning tools int iPhones and iPads in the future, with processing on-device instead of in the cloud.
GeekWire first broke the news earlier Wednesday, citing sources with knowledge of the deal. According to GeekWire, the deal is reportedly worth up about $200 million. Apple paid the same $200 million for another Seattle-based AI startup, Turi, in 2016.
Unlike traditional AI that runs in massive data centers and requires network connectivity, XNOR makes AI highly efficient by allowing deep learning models to run directly on phones, IoT devices and low power microprocessors. XNOR’s technology enables AI experiences that are up to 10x faster, 200 percent more power efficient, and use 15x less memory.
