Paving the way for the creation of AI cities, NVIDIA unveiled the NVIDIA Metropolis™ intelligent video analytics platform at GTC 2017 May 8-11. GTC is the largest and most important event of the year for GPU developers. The global GTC event series offer valuable training and a showcase of the most vital work in the computing industry today – including artificial intelligence and deep learning, healthcare, virtual reality, accelerated analytics, and self-driving cars. NVIDIA Metropolis makes cities safer and smarter by applying deep learning to video streams for applications such as public safety, traffic management and resource optimization.
Deep learning is enabling powerful intelligent video analytics that turn anonymized video into real-time valuable insights, enhancing safety and improving lives. The NVIDIA Metropolis platform enables customers to put AI behind every video stream to create smarter cities. – Deepu Talla, Vice President and General Manager of the Tegra business at NVIDIA
Growing AI City Partner Support
More than 50 NVIDIA AI city partner companies are already providing products and applications that use deep learning on GPUs, many of which are on display this week at the GPU Technology Conference. NVIDIA AI city partners can help customers reveal insights and take real-time action using deep learning on NVIDIA GPUs. Among them are industry leaders such as Avigilon, Dahua, Hanwha Techwin, Hikvision and Milestone.
City management customers using Milestone’s upcoming Video Processing Server with NVIDIA Metropolis are positioned to take the lead in the adoption of deep learning for video-enabled IoT devices. Unleashing the value of this metadata will provide intelligent insights to take smart action. – Bjørn Skou Eilertsen, Chief Technology Officer at Milestone Systems
Video Is World’s Largest Data Source
Video is the world’s largest generator of data, captured by hundreds of millions of cameras deployed in areas such as government property, public transit, commercial buildings and roadways. By 2020, the cumulative number of cameras is expected to rise to approximately 1 billion.
Humans currently monitor only a fraction of captured video, with most stored on disks for later review. Initial efforts at real-time video analytics techniques have proved far less reliable than human interpretation. Intelligent video analytics solves this challenge by using deep learning in cameras, on-premises video recorders and servers, and in the cloud to monitor video instantaneously with accuracy and scalability.
Metropolis spans multiple NVIDIA products that operate on a unified architecture. High-performance deep learning inferencing happens at the edge with the NVIDIA Jetson™ embedded computing platform, and through servers and data centers with NVIDIA® Tesla® GPU accelerators. Rich data visualization is powered by NVIDIA Quadro® professional graphics. And the entire edge-to-cloud platform is supported by NVIDIA’s rich software development kits, including JetPack, DeepStream and TensorRT™.
Learn more on the NVIDIA website.