Dynamic electric vehicle charging would make EV infrastructure more reliable and convenient.
The easy accessibility of cloud-native artificial intelligence and machine learning allows agencies to quickly design, test and deploy complex service solutions.
By modeling different levels of driver cooperation, researchers hope to help autonomous vehicles safely and efficiently navigate situations where a driver’s temperament figures into decision-making.
The Bureau of Engraving and Printing is looking for new ways to integrate machine-readable features into future versions of U.S. currency that could be used to detect and deter counterfeiting.
The Defense Department has begun deploying 5G-powered augmented reality/virtual reality systems for mission planning and training at some of its 5G testbed sites.
Researchers at Oak Ridge National Laboratory have developed a modeling tool that helps transportation planners decide where to place electric vehicle charging stations to encourage intercity driving.
To prevent damage to power equipment from cyberattacks, researchers at Idaho National Laboratory have developed a device that autonomously reviews and filters commands being sent to a power grid’s relay devices.
An algorithm detects smoke plumes by comparing images from 25 tower-mounted cameras against the more than 10 million it’s been trained on.
MLOps operationalizes the production of machine-learning software so agencies can expedite the continuous production of ML models at scale, significantly reducing the time it takes to deploy intelligent AI applications.
Researchers at Japan’s National Institute of Information and Communications Technology have demonstrated long-haul data transmission at 319 terabits/sec over 1,800 miles.