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Introduction

Date: September 28, 2021
Time: 11:00am – 12:00pm PT
Duration: 1 hour

Simplifying and accelerating AI Development workflows is hugely valuable, whether you have an army of data scientists or just a few application developers. From adapting a model to fit your use-case to optimizing your model throughput and latency for deployment - there are a number of ways to shorten your time to market. The NVIDIA TAO Toolkit should be part of any AI development process and abstracts away the AI/DL framework complexity, allowing you to fast-track your model adaptation and optimization process.

In this session, we’ll cover the top five reasons to leverage NVIDIA TAO Toolkit, including:
  • How it can help you overcome your data prep challenges
  • How to fine-tune your models without deep expertise in AI
  • How to get them ready for deployment in production

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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

Akhil Docca

Senior Product Marketing Manager, NVIDIA

Akhil Docca is a senior product marketing manager for NVIDIA TAO, an AI-Model-Adaptation platform. Akhil has a Master’s in Business Administration from UCLA Anderson School of Business and a Bachelor’s degree in Mechanical Engineering from San Jose State University.

Chintan Shah

Senior Product Manager, NVIDIA

Chintan Shah is a senior product manager at NVIDIA, focusing on AI products for intelligent video analytics. Chintan manages an end-to-end toolkit for efficient deep learning training and real-time inference. Previously, he developed hardware IPs for NVIDIA GPUs. Chintan holds a master’s degree in electrical engineering from North Carolina State University.

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Date & Time: Wednesday, April 22, 2018