BUILT FOR EXTREME PARALLEL PROCESSING POWER
GPU computers leverage their thousands of GPU cores and the CUDA platform from NVIDIA to boost the parallel processing of the device further than a normal CPU ever could. This enables the device to perform millions of simultaneous operations necessary for applications such as video analytics, deep learning, machine vision and more.
PURPOSE BUILT. INDUSTRIAL. POWER EFFICIENT
Computers which leverage Vision Processing Units (abbreviated to VPUs), a type of expansion card that is application specific. Intel VPUs are purpose-built to boost deep learning performance in fields such as computer vision, automatic speech recognition and natural language processing. In comparison with General Purpose GPUs, VPUs are more efficiently designed for AI and as such are lower cost and draw significantly less power. This allows for a smaller footprint and fanless design. Ideal for IOT edge deployments.
A COMPLETE SYSTEM, DESIGNED BOTTOM UP FOR AI
Nvidia Jetson Computers are a complete package designed for AI. They do not take an expansion card to add AI functionality. Rather, the entire platform was designed from the beginning for AI embedded and edge devices. Jetson systems come pre-designed and configured with a CPU, a GPU with specially designed AI cores, memory, power management and more with a low power, fanless industrial design.
BOOST THE AI PROCESSING PERFORMANCE OF YOUR DEVICE
Intel® Movidius™ Myriad™ X VPUs designed to boost the AI capabilities of compatible computers. Intel VPUs are supported by OpenVino, the open source toolkit developed by Intel specifically for optimizing and deploying AI Inference. Supported by frameworks such as TensorFlow, Caffe, MXNET and more. Available in Mini PCIe, M.2 and full-sized PCIe for all levels of performance.
AI Computers can be used in a wide array of different industries and applications.
Automatic number plate recognition is widely used in public transportation, toll roads, road safety and even autonomous vehicles. With more than 2 billion vehicles in use worldwide, it is becoming more and more of a necessity. AI image processing powered by VPU and GPU computers are essential for training models which ensure accuracy in spite of such things as lighting, motion blur, weather and viewing angle.
Machine vision has long been a staple in automation and manufacturing. As technology advances applications for machine vision have expanded to autonomous vehicles, kiosks and security. The parallel processing afforded by GPU and VPU computers allow for more compute intensive vision computation to fulfill these needs.
The field of defect detection has evolved from simple rules-based computation to highly complex detection and prediction based on deep learning algorithms. To make full use of this evolving technology New Era provides high-powered industrial AI computers which can accept GPU and VPUs.
Video analysis covers a wide range of applications such as facial recognition, security, demographics, object recognition, etc. New Era provides a wide variety of VPU and GPU computers suitable for deployment in a wide range of environments and sizes.
Customer count, customer flow, advertisement metrics, smart forecasting, and virtual attendants, are just a few of the features of a fully implemented smart retail system. There are a great many ways that brick and mortar stores are leveraging AI computers to improve customer experience and profitability.
Whether it’s a self-guided vehicle for passenger transport, an autonomous drone, or an autonomous mobile robot for use in a warehouse, autonomous vehicles are a rapidly evolving field that leverages AI to its fullest. New Era carries a line of AI computers which are also rugged and in-vehicle certified!
Deep Learning, much like many other AI applications is one whose performance is greatly improved by greater graphics and computing power. New Era carries several lines of industrial GPU and VPU computers compatible with a long list of machine learning libraries and frameworks.
The essence of IOT Edge computing is taking load off of centralized servers by performing computing tasks in the field, closer to the point of data input. The benefits of this are faster analysis of data, less load on cloud servers, and real-time prediction. Depending on the nature of the data and analysis, AI and GPU computers can be a perfect fit for this application.