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Introduction

Developers need large, carefully labeled datasets to train neural networks for Vision AI applications. However, traditional data acquisition can be costly, time-consuming, prone to errors, and might not capture all the edge cases. All of these issues lead to delays and high costs for creating effective AI solutions.

Enter synthetic data, which is generated programmatically, auto-labeled, and can contain thousands of diverse scenarios that would be otherwise impossible to collect.

Join this meetup to learn how synthetic data can transform your AI development efforts:

  • Learn how to use NVIDIA’s Omniverse Replicator to quickly create synthetic data and how it can integrate with NVIDIA TAO training tools.
  • Hear from Sky Engine AI, an NVIDIA synthetic data partner, how you can leverage synthetic data services.
  • Get your questions answered in a live Q&A session with our team of experts.

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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

Nyla Worker

Product Manager for Omniverse Replicator, NVIDIA

Nyla Worker is a Product Manager for Omniverse Replicator, a framework to generate synthetic data at NVIDIA. Before, she was a Data Scientist at NVIDIA focused on simulation and deep learning within embedded devices. She has extensive experience working on deep learning edge applications for robotics and autonomous vehicles, as well as developing accelerated inference pipelines for embedded devices.

Jakub Pietrzak

Chief Technology Officer, Sky Engine AI

Jakub Pietrzak is the Chief Technology Officer at Sky Engine AI. He heads GPU-accelerated research, data science, and machine learning algorithms development. He is a computer vision magician with 15+ years of experience in machine learning, ray tracing, and digital image processing. Jakub has worked on deep learning-powered motion-capture systems for the biggest movie studios in Europe and was involved in medical imaging research projects at the Warsaw Center of Oncology. For his Ph.D. Jakub explored the idea of training neural networks on synthetic data and a topic of recreation of machine learning problems in virtual reality.

Debraj Sinha (Moderator)

Product Marketing Manager for Metropolis, NVIDIA

Debraj Sinha is a Product Marketing Manager for Metropolis at NVIDIA, focusing on building smarter spaces around the world with vision AI applications. Debraj collaborates with partners ranging from startups to Fortune 500 companies to market AI applications that drive safety and efficiency gains.

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Date & Time: Wednesday, April 22, 2018