Vivek Venugopalan, a staff research scientist at the United Technologies Research Center (UTRC) shares how they are using deep learning and GPUs to understand the life of an aircraft engine and predictive maintenance for elevators in high-rise buildings.
“GPUs have helped us arrive at solutions quickly for computationally intensive challenges across all UTRC platforms, especially in this era of big data and internet of things,” said Venugopalan. “This is very critical because what used to take months to come to a solution, we are now able to achieve this in a couple of hours.”
Share your GPU-accelerated work with us at http://nvda.ws/2cpa2d4.
Watch more scientists and researchers share how accelerated computing is benefiting their work at http://nvda.ws/2dbscA7
Developer Spotlight: Applying Deep Learning to Aerospace Technologies and Integrated Systems
May 03, 2017
Discuss (0)

Related resources
- GTC session: Building AI-Enabled Digital Twins Using NVIDIA Omniverse (Presented by Lockheed Martin) (Spring 2023)
- GTC session: Out of the Lab and into the Field: A Model for Modern RF Systems (Spring 2023)
- GTC session: Big Leap in VRAN: Full Stack Acceleration, Cloud First, AI and 6G Ready (Spring 2023)
- Webinar: Accelerating Research in the Earth and Space Sciences with AI
- Webinar: American Airlines Realizes New Business Efficiencies with Machine Learning and GPU Accelerated Data Science Workstations
- Webinar: Autonomous Driving at Scale: Architect and Deploy Object Detection Inference Pipelines