We introduce RobotPerf, a vendor-agnostic benchmarking suite designed to evaluate robotics computing performance across a diverse range of hardware platforms using ROS 2 as its common baseline. The suite encompasses ROS 2 packages covering the full robotics pipeline and integrates two distinct benchmarking approaches: black-box testing, which measures performance by eliminating upper layers and replacing them with a test application, and grey-box testing, an application-specific measure that observes internal system states with minimal interference. Our benchmarking framework provides ready-to-use tools and is easily adaptable for the assessment of custom ROS 2 computational graphs. Drawing from the knowledge of leading robot architects and system architecture experts, RobotPerf establishes a standardized approach to robotics benchmarking. As an open-source initiative, RobotPerf remains committed to evolving with community input to advance the future of hardware-accelerated robotics.

The recent ransomware attack on Colonial Pipeline is another painful reminder of how vulnerable we are to such attacks and difficult it is to defend our infrastructures against them. RaaS (Ransomware as a service) is a thriving industry in many dark corners of the world, and protecting against it at the intelligent edge is particularly difficult. Challenges include day zero detection with no previous example or known signature, low latency response time, and high detection throughput rate needed to handle the ever-increasing online transactions at the intelligent edge. Additional challenges included limited compute and power resources and hardware architecture flexible enough to change when threat conditions change. Center for Advanced Electronics through Machine Learning (CAEML) researchers have been investigating machine learning hardware solutions that can accelerate ransomware detection at the intelligent edge.

Six of the eight largest public cloud providers worldwide–Alibaba, Baidu, Google, IBM, Microsoft and Tencent–have been investing heavily in quantum computing research and development (R&D). AWS, by far the largest cloud provider, had been completely absent from the quantum computing discussion until this week. The holy grail for cloud providers is to find a hardware solution that accelerates machine learning and artificial intelligence by orders of magnitude. There are two ways to improve machine learning at scale: build specialized architectures using today's design tools or find a completely different path. Quantum computing is everyone's big bet for the completely different path.

Investment figures into artificial intelligence are growing exponentially each year. According to the market researchers at Markets and Markets, the current estimate is that the AI market will reach $191 billion by the year 2025. The investment number for 2018 was $21.5 billion. Taking a look at the phenomenon, British specialist publication TechWorld took a look at how 12 of the world's technological giants are investing in the development of artificial intelligence. Here we present the current six leaders in that field. Nvidia – One of the largest chipmakers is at the same time one of the most serious investors into AI technology, as chips are key to pushing the technology forward.