International Data Corporation (IDC) recently published an IDC Innovators report profiling five companies that offer compelling and differentiated computer vision software. The five companies are Algolux, Deep Vision AI, Sighthound, ViSenze, and Umbo CV. Computer vision is an AI technology that allows computers to understand and label images. Use cases include video surveillance, driverless car testing, daily medical diagnostics, and monitoring the health of crops and livestock. AI is used for pattern recognition and learning techniques driven largely by machine learning (ML) and deep learning (DL) algorithms that bring visual understanding capabilities in a growing variety of hardware and software applications.
How would you protect the US against Chinese cyberattacks? Would you push for stricter security standards, or new encryption technology? The Trump administration's national security team has another idea: a government-controlled 5G network. Axios has obtained documents showing that the team is pushing for a centralized, secure 5G network within 3 years. This would create a secure communications avenue for self-driving cars, AI, VR and other budding technologies. Just how it would be built is another story, however.
Edge computing has become widespread, as more companies rely on IoT-based technologies that assist with enterprise physical security, monitoring, and automated equipment. Specifically, companies are investing in sensors, cameras, remote devices, servers, and networks at the edges of their enterprises. This is thanks in part to the combination of new 5G, and edge computing capabilities offering everything from real-time analytics to automation to self-driving cars and trucks. ZDNet and TechRepublic journalists have launched a special report examining the role edge computing plays in various industries and delves into the benefits and risks pertaining to edge computing implementation. Nick Heath explains what you need to know before traveling down the route of edge analytics and processing.
Palo Alto-based Cobalt Robotics Inc. today introduced a new line of robot security guards for indoor use. The roving robots use the same kind of components you'd expect in a self-driving car to sense people and problems in a building. Cofounders Travis Deyle and Erik Schluntz, who are former GoogleX and SpaceX engineers, say they designed the robots to complement, not replace, human security guards. Altogether, Cobalt's robo-guards pack 60 sensors, including lidar, ultrasound, depth sensors and cameras, as well as wide angle day and night cameras to detect people around them. They also include mics and two-way video chat screens that allow human security guards or building managers to remotely interact with a person who the robot approaches.
Uber drivers who pay a visit to the company's inspection lot near Mission Bay in San Francisco will be met with a rather strange sight: a five-foot-tall, white, egg-shaped robot wheeling around the lot, on the look-out for trouble. The robot is a K5, a 300-pound security robot made by Silicon Valley start-up Knightscope. Stacy Stephens, Knightscope's VP of marketing, says Uber is a recent customer of the company. The robot has multiple high-definition cameras for 360-degree vision, a thermal camera, a laser rangefinder, a weather sensor, a license-plate recognition camera, four microphones, and person recognition capabilities. Once set up in a geofenced area, "it roams around looking for anomalies," said Stephens.