Remark Holdings, Inc. (Nasdaq: MARK), a diversified global technology company with leading artificial intelligence ("AI") computer vision solutions, today announced its recent partnership with AAEON, a leader in AI edge computing the importance of delivering market-ready solutions for the creation of smart cities that require vision solutions for increased public safety, situational awareness, and behavioral analysis. "We are very pleased about this partnership. Combining our AI-driven video analytics with AAEON's computing platforms creates a simplified solution for system integrators and end users. Together we can easily build and deploy a complete vision system that detects, identifies, tracks, and characterizes objects, people, vehicles, and behaviors at scale and speed with actionable insights and minimal false alarms," said Dr. Xiaoyun Yang, Director of Research and Development at Remark Holdings. Remark AI's AI-powered SSP capabilities generate real-time alerts for proactive security, including: And for medium to large businesses, it's unrealistic and inefficient to rely on manually monitoring cameras' video streams, given the number of false alarms and the need to act quickly.

VVDN Technologies, a premier electronic product engineering and manufacturing company, announced that it has joined the NVIDIA Partner Network (NPN) as a provider of AI-enabled computer vision solutions powered by the NVIDIA Jetson edge AI platform. The NPN program is designed to help partners expand the usage of NVIDIA-based solutions, platforms, and technologies, and provide end customers with a world-class solution and support experience. As part of the NVIDIA Jetson partner ecosystem, VVDN can leverage the powerful GPU-accelerated edge computing capabilities of the NVIDIA Jetson lineup including Jetson AGX Series, Jetson TX2 series, Jetson Xavier NX and Jetson Nano to develop and manufacture next-gen innovative AI/ML based camera and vision solutions for its customers. NVIDIA Jetson is the leading AI-at-the-edge computing platform with over half a million developers and a strong partner ecosystem. With pre-trained AI models, developer SDKs and support for cloud-native technologies across the full Jetson lineup, manufacturers of intelligent machines and AI developers can build and deploy high-quality, software-defined features on embedded and edge devices targeting robotics, AIoT, smart cities, healthcare, industrial applications, and more.

BrainChip Holdings Ltd, a leading provider of ultra-low power high performance AI technology, announced that it has partnered with Magik Eye Inc., developers of revolutionary 3D sensors that change how machines see the world, to market a breakthrough solution for object detection, object classification and gesture recognition based on MagikEye's Invertible Light 3D depth sensing technology and the Akida neuromorphic processor. This relationship opens a new and exciting gateway for BrainChip in Japan. MagikEye's Invertible Light provides the smallest, fastest and most power-efficient 3D depth sensing. This is done using a standard CMOS image sensor and a regular dot projector along with a proprietary and patented technique to produce 3D point cloud data. Coupled with the Akida neuromorphic processor, the companies intend to jointly provide a total 3D vision solution to customers for fast 3D object detection and recognition in applications, including robotics, automotive and emerging consumer products, such as AR/VR and others.

Machine vision quality assurance systems have excelled at automating the location, identification, and inspection of manufactured components through computational image analysis. But when the component is part of a larger assembly, a complex package, or a kit--such as an automotive assembly or surgical intubation kit--defects, random product placement, variations in lighting, and other factors can quickly overwhelm a traditional machine vision system. For this reason, final inspection of assemblies, packages, and kits is usually conducted manually, to the detriment of overall quality and productivity. While manual operators typically excel at inspecting complex assemblies, by comparing multiple attached or connected components to automated quality inspection solutions, it's hard for operators to stay sharp. Studies show most operators can only focus on a single task for 15 to 20 minutes at a time.

It's been an amazing year leading the Internet of Things (IoT) Group at Intel. During this time we have been working hard to define and develop a data-driven technology foundation for industry innovation. Our strategy is to drive end-to-end distributed computing in every vertical by focusing on silicon platforms and workload consolidation at the edge. Critical to our success is aligning our ecosystem of partners and developers to deliver the benefits. This focused effort is paying off, as Intel's IoT business grew by 20 percent in 2017 and continued with strong growth in this year's first quarter.