NVIDIA WEBINAR
Building AI powered cloud native applications allows organizations to integrate and deploy innovative features faster, scale on-demand, and optimize operational cost. AI powered enterprise applications are one of the fastest growing workloads in the hybrid cloud as organizations develop and deploy in the cloud and scale it on-prem overtime in a consistent manner.
The NVIDIA NGC catalog offers GPU-optimized AI software including framework containers and models that allow data scientists and developers to build their AI solutions faster. Red Hat OpenShift is a leading enterprise Kubernetes platform for Hybrid Cloud with integrated DevOps capabilities, enabling organizations globally to fast track AI projects from pilot to production.
maincontent goes here
Content goes here
content goes here
Content goes here
Content goes here
Chintan Patel is a Senior Product Marketing Manager at Tesla Business Unit. He is responsible for growing awareness and driving adoption of GPU Computing products for Supercomputing and Higher Education segments. Prior to NVIDIA, he held product marketing and engineering positions at Micrel, Inc. He holds an MBA from Santa Clara University and a bachelor's degree in electrical engineering and computer science from UC Berkeley.
Deepthi Dharwar is a Principal Engineer at Red Hat working on deploying performance sensitive applications on OpenShift platform. Prior to this role, Deepthi has worked on multiple strata of system software stack including the Linux Kernel, Firmware, Virtualization and Containers. She has a degree in Computer Science and Engineering.
Diane Feddema is a principal software engineer at Red Hat Inc, in the CTO office AI Center of Excellence. Diane is currently focused on developing and applying machine learning techniques for performance analysis using hardware accelerators, automating these analyses and displaying data in novel ways. Previously Diane was a performance engineer at the National Center for Atmospheric Research, NCAR, working on optimizations and tuning in parallel global climate models, and has held various positions at Motorola (development), SGI (performance) and Cray (compiler development). She has a BS and MS in Computer Science.
Abhishek Sawarkar is responsible for the development and presentation of deep learning-focused content on the NVIDIA Jarvis framework. His background is in computer vision and machine learning but currently he is working on the entire Jarvis multi-modal pipeline featuring ASR, NLP, TTS, and CV. He is a recent graduate from Carnegie Mellon University with a master’s degree in electrical and computer engineering.
Content here
Webinar: Description here
Date & Time: Wednesday, April 22, 2018