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.

In the age of global warming, forest fires are becoming more frequent and faster-growing. Clearly, the world needs sustainable solutions to preserve our natural resources, protect human lives, and avoid economic devastation. As an environmental advocate and sustainability enthusiast, I got to thinking about whether a technological solution can help with this daunting task. Fortunately, I am also a computer scientist, one who is all too aware of how tedious and time-consuming research can be. In such times, I often choose to play my ace in the hole by going straight to Intel's rich ecosystem--the Intel Partner Alliance. Not surprisingly, it led me to an ingenious solution: the AAEON Intelligent Forest Fire Monitoring System (Figure 1).

TAIPEI, Taiwan – AAEON Technology in Taipei, Taiwan, and Aotu.ai in Santa Clara, Calif., are introducing the BrainFrame Edge AI Developers Kit (DevKit) for an Intel artificial intelligence (AI) computer to enable system integrators rapidly to create and deploy smart machine vision applications. The BrainFrame Edge AI DevKit helps create solutions such as machine vision-based access control, uniform compliance, manufacturing automation, and video analytics. BrainFrame scales and configures easily and enables a connected camera to become a continuously monitoring Smart Vision system. BrainFrame's automatic algorithm fusion and optimization engine has VisionCapsules, Aotu.ai's open source algorithm packaging format. These self-contained capsules have a negligible memory footprint and include all necessary code, files, and metadata to describe and implement a machine learning algorithm.

Machine vision has come a long way from the simpler days of cameras attached to frame grabber boards--all arranged along an industrial production line. While the basic concepts are the same, emerging embedded systems technologies such as Artificial Intelligence (AI), deep learning, the Internet-of-Things (IoT) and cloud computing have all opened up new possibilities for machine vision system developers. To keep pace, companies that used to only focus on box-level machine vision systems are now moving toward AI-based edge computing systems that provide all the needed interfacing for machine vision, but also add new levels of compute performance to process imaging in real-time and over remote network configurations. AI IN MACHINE VISION ADLINK Technology appears to be moving in this direction of applying deep learning and AI to machine vision. The company has a number of products, listed "preliminary" at present, that provide AI machine vision solutions. These systems are designed to be "plug and play" (PnP) so that machine vision system developers can evolve their existing applications to AI-enablement right away with no need to replace existing hardware.

AAEON, a specialist in artificial intelligence (AI) edge solutions, has released the BOXER-8251AI AI edge box PC, powered by NVIDIA Jetson Xavier NX. The BOXER-8251AI is said to offer greater performance and is more compact. The device is powered by the Jetson Xavier NX from NVIDIA. Featuring a six-core 64-bit ARM processor, it boasts 384 CUDA cores, 48 Tensor Cores, and two NVDLA engines capable of running multiple neural networks in parallel, delivering accelerated computing performance up to 21 TOPS. Built to bring dedicated AI processing to the edge, the system also features 8GB of LPDDR4 memory and 16GB of onboard eMMC memory that's expandable through the Micro-SD card slot.

The FWS-8600 2U Rackmount Network Appliance is built to handle powerful network applications, including UTM, SDN and NFV. Additionally, it features support for the Second Generation Intel Xeon Scalable Processor (formerly Cascade Lake) with Intel Deep Learning Boost, allowing the FWS-8600 to meet the high-data needs of AI edge and cloud networks, including AIOT. The FWS-8600 can support LAN throughput up to 300 400 Gbps, according to AAEON testing. It also features four lockable hard drive bays, support for up to 512GB of RDIMM ECC RAM, and four NIM slots. With manufacturer support from AAEON, the FWS-8600 can be configured and built to your network needs.

Autonomous robots are complicated machines. There are many different systems needed for a robot to understand its environment, learn from it, and then take actions within that environment. Just one of those components can take time to understand, develop and integrate together. The earliest self-driving cars required racks of servers running Intel Xeon processors to be able to understand and navigate within their environments. While autonomous robots don't usually have the same level of constraints as a self-driving car, they do operate in a similar problem space.

The slim PC can also be fitted with AAEON's AI Core – a mini-PCIe module powered by Intel Movidius Myriad 2 technology. The deep learning module enables the Boxer-6405 to serve as a powerful edge AI device, and the AI Core's advanced VPU enhances the system's already formidable machine vision capabilities. Because the AI Core operates on the edge without a connection to a network or the cloud, issues relating to latency, reliability, and security are eliminated. The low-power-consumption system features a 6W TDP, and it can also serve as an effective IoT gateway device, as WiFi and 4G modules can be installed via the machine's two mini card slots. The fanless system has an IP40 rating, an operational temperature range of -20 to 60ºC, and a DC power input range of 9V to 24V.

Aaeon has launched an "UP AI Edge" family of products that builds on a new Apollo Lake based "UP Core Plus" SBC with stacking AI companion boards based on the Movidius Myriad 2 or Intel Cyclone 10GX plus add-ons including a quad-GbE board and a camera. Aaeon Europe quickly met its modest $11K Kickstarter goal for the new UP AI Edge ecosystem, which builds on its UP board products and community. The centerpiece is a new UP Core Plus SBC, although the official, Ubuntu-equipped UP AI Edge development package uses the larger, more feature-rich UP Squared SBC. The Ubuntu stack also includes Intel's OpenVINO computer vision toolkit, which is optimized for the Myriad 2. Also available is the Arduino Create development environent, an Open CL/ Movidius Driver, Intel System Studio, and cloud connectors for Microsoft Azure, Amazon AWS, Google Cloud, and IBM Bluemix. You can also use the Neural Compute Stick SDK available for the Myriad 2 equipped Intel Movidius Neural Compute Stick for "rapid prototyping, validation and deployment of Deep Neural Network (DNN) inference applications at the edge," says Aaeon.

Last year, Intel embedded its line of Myriad 2 chips into a USB stick that developers could plug into development boards or personal computers to experiment with artificial intelligence. The custom chips can accelerate neural networks used in image recognition and other tricky tasks that computers can be trained to tackle. On Tuesday, the company introduced a program to make it easier for developers to turn prototypes built with the Neural Compute Stick into security cameras, industrial sensors, and other production devices. Intel is partnering with Aaeon to offer a board called the A.I. Core, which serves as a sort of production version of the dongle. The A.I. Core board contains the same Myriad vision processing unit as the stick, allowing small companies and entrepreneurs to move to the production board without changing code.