Accelerate Intelligent Video Analytics for Disaster Response
Event Date: September 10, 2019
Hosted By: NVIDIA
Deep learning can help the public good by tapping into massive feeds of video data to gather real-time, actionable insights for areas like disaster relief. Discover how NVIDIA's DeepSteam SDK can speed up disaster response by streamlining applications such as analytics, intelligent traffic control, automated optical inspection, object tracking, and web content filtering.
View this archived recording for an in-depth, technical webinar to learn how to:
Deploy NVIDIA® TensorRT™ into hardware-accelerated IVA application in a few short steps
Build a high-throughput, low-latency streaming framework capable of scaling with the size of your data
Across the enterprise, there’s a growing need for graphics and compute
acceleration with fast, secure access from anywhere, on any device. Engineers,
designers, and architects are using powerful applications that rely on graphics-intensive datasets and need to be accessed by distributed teams fr...
Artificial intelligence (AI) promises to impact the world’s geopolitical hierarchy like no other technology in history. With the most powerful countries in a race to establish AI dominance, Rep. Will Hurd (R-Texas), chairman of the House Subcommittee on Information Technology, presided over a seri...
The presence of extraordinary amounts of data, to train on, to
learn from, and to explore, represents a golden age of computing.
But beneath this incredible opportunity lies a massive challenge.
Traditional CPU compute cannot keep pace with the growth in data,
and as a result, even the most soph...
Thousands of researchers rely on NVIDIA’s end-to-end accelerated computing platform to
solve the world’s most complex problems. When COVID-19 became a global pandemic, that
trend continued: Many researchers and developers fighting the pandemic turned to GPUaccelerated computing to advance scie...
Virtual client computing (VCC), including application and desktop virtualization, is a foundational capability for organizations adapting to the future of work. The application of computing accelerators — including GPU acceleration — improves client performance, expands the available use cases, ...
The high demands of today’s professional applications mean there are
more use cases for GPUs across the enterprise than ever before. Designers
and engineers rely on graphics-intensive applications featuring 3D
visualization, many of which include AI-enhancements. Data scientists run