Throughout my career, and now more than ever at Intel, I have dreamed about where technology will take us next, and it's even more exciting to be creating the future. Today, that future is here with the unveiling of the Myriad X, the world's first vision processing unit (VPU) to ship with a dedicated Neural Compute Engine to deliver artificial intelligence (AI) capabilities to the edge in an incredibly low-power, high-performance package. In the coming years, we'll see a huge range of new products emerge that are made more autonomous by embedding real-time intelligence capabilities in devices – from drones and smart cameras to augmented reality and more – to give them the ability to see, understand, interact with and learn from rapidly changing environments. Myriad X combines dedicated imaging, computer vision processing and – thanks to the industry-first Neural Compute Engine – high-performance deep learning inference within the same chip, and the results are opening up new realms of possibility. With this faster, more pervasive intelligence embedded directly into devices, the potential to make our world safer, more productive and more personal is limitless.
Today, Intel launched the Movidius Neural Compute Stick, the world's first USB-based deep learning inference kit and self-contained artificial intelligence (AI) accelerator that delivers dedicated deep neural network processing capabilities to a wide range of host devices at the edge. Designed for product developers, researchers and makers, the Movidius Neural Compute Stick aims to reduce barriers to developing, tuning and deploying AI applications by delivering dedicated high-performance deep-neural network processing in a small form factor. As more developers adopt advanced machine learning approaches to build innovative applications and solutions, Intel is committed to providing the most comprehensive set of development tools and resources to ensure developers are retooling for an AI-centric digital economy. Whether it is training artificial neural networks on the Intel Nervana cloud, optimizing for emerging workloads such as artificial intelligence, virtual and augmented reality, and automated driving with Intel Xeon Scalable processors, or taking AI to the edge with Movidius vision processing unit (VPU) technology, Intel offers a comprehensive AI portfolio of tools, training and deployment options for the next generation of AI-powered products and services. "The Myriad 2 VPU housed inside the Movidius Neural Compute Stick provides powerful, yet efficient performance – more than 100 gigaflops of performance within a 1W power envelope – to run real-time deep neural networks directly from the device," said Remi El-Ouazzane, vice president and general manager of Movidius, an Intel company.
Intel's first few "Compute Stick" products were basically fully functional PCs packed into a tiny case with an HDMI connector that you could plug directly into a display. The latest Compute Sticknot th from Intel is a little different. Intel subsidiary Movidius has launched a Neural Compute Stick that you can plug into the USB port of any computer to add hardware-accelerated machine learning/vision processing/artificial intelligence to an existing computer. The Neural Compute Stick sells for $79 and it's actually something Movidius was working on before Intel acquired the company… but now that Movidius is part of the Intel team, it gets to wear the Compute Stick name, I guess. The stick features a Movidius Vision Processing Unit (VPU), which allows it to perform neural network processing without relying on cloud computing, so no internet connection is required.
The Movidius Neural Compute Stick enables rapid prototyping, validation and deployment of Deep Neural Network (DNN) inference applications at the edge. Its low-power VPU architecture enables an entirely new segment of AI applications that aren't reliant on a connection to the cloud. The NCS combined with Movidius Neural Compute SDK allows deep learning developers to profile, tune, and deploy Convolutional Neural Network (CNN) on low-power applications that require real-time inferencing.
"Clean water and health care and school and food and tin roofs and cement floors, all of these things should constitute a set of basics that people must have as birthrights."1 Obtaining clean water is a critical problem for much of the world's population. Testing and confirming a clean water source typically requires expensive test equipment and manual analysis of the results. For regions in the world in which access to clean water is a continuing problem, simpler test methods could dramatically help prevent disease and save lives. To apply artificial intelligence (AI) techniques to evaluating the purity of water sources, Peter Ma, an Intel Software Innovator, developed an effective system for identifying bacteria using pattern recognition and machine learning.