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Introduction

Date: Tuesday, November 10, 2020
Time: 11:00am – 12:00pm PT
Duration: 1 hour


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.


In this session you will learn to:
  • Leverage the NVIDIA NGC catalog of GPU-optimized containers and models to build AI applications
  • Take advantage of Red Hat OpenShift to automate and streamline the development, deployment, and management of intelligent apps that include AI models, also known as DevOps for MLOps
  • Build a conversational AI solution, using BERT model with NGC and OpenShift on a public cloud
Join us after the presentation for a live Q&A session.



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DGX Station Datasheet

Get a quick low-down and technical specs for the DGX Station.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.

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Speakers

Chintan Patel

Senior Product Marketing Manager, NVIDIA

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

Principal Engineer, Red Hat

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

Principal Software Engineer, Red Hat

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

Technical Marketing Engineer, NVIDIA

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.

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Date & Time: Wednesday, April 22, 2018