Webinar
November 9, 2023

Fast Track AI to the Edge

with NVIDIA TAO & Edge Impulse

Fast Track AI to the Edge with NVIDIA TAO & Edge Impulse

If you’re using artificial intelligence to build smart devices such as computer vision monitoring for predictive maintenance, you know that collecting, cleaning, and labeling data is time consuming, tedious, and expensive. Edge Impulse and pretrained models from NVIDIA TAO help get you on the fast track to enterprise-grade production with 100+ NVIDIA-optimized model architectures, like vision transformers and fully attentional networks. Fine-tune the models with your own data, enabling a much faster development process.

Watch the webinar, ‘Fast Track AI to the Edge with NVIDIA TAO & Edge Impulse’, to hear from NVIDIA’s Debraj Sinha (Product Marketing Manager), Edge Impulse’s Jan Jongboom (CTO & Cofounder) and Jenny Plunkett (Senior Engineer) about the latest in edge AI and how to leverage pretrained models from NVIDIA to deploy on edge devices.

Learn how to:

  • Build efficient vision ML pipelines faster by combining the power of transfer learning and the latest NVIDIA TAO models across the entire Edge Impulse ecosystem of devices, silicon, and sensors.
  • Profile the performance of your model on different hardware to find the optimal target given your use case and hardware constraints.
  • Efficiently collect data from any edge device and use Edge Impulse auto-labeling tools to increase data quality.
  • Collect data, train and validate your model, and optimize libraries to run on any edge device, from extremely low-power MCUs to efficient Linux CPU targets to any NVIDIA GPU or neural accelerator.
Speakers:

Debraj 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.

Debraj Sinha
Product Marketing Manager, NVIDIA

Jan Jongboom is an embedded engineer and machine learning advocate, always looking for ways to gather more intelligence from the real world. He has shipped devices, worked on the latest network tech, simulated microcontrollers and there's a monument in San Francisco with his name on it. Currently he serves as the cofounder and CTO of Edge Impulse, the leading development platform for embedded machine learning with 140,000+ projects.

Jan Jongboom
CTO and Cofounder, Edge Impulse

Jenny Plunkett is a software engineer, technical speaker and content creator, working as a Senior Developer Relations Engineer at Edge Impulse. Since graduating from The University of Texas she has been working in the IoT space, from customer engineering and developer support for Arm Mbed to consulting engineering for Pelion IoT. Jenny is co-author of the O’Reilly book "AI at the Edge: Solving Real World Problems with Embedded Machine Learning".

Jenny Plunkett
Senior Developer Relations Engineer, Edge Impulse

Fast Track AI to the Edge with NVIDIA TAO & Edge Impulse

If you’re using artificial intelligence to build smart devices such as computer vision monitoring for predictive maintenance, you know that collecting, cleaning, and labeling data is time consuming, tedious, and expensive. Edge Impulse and pretrained models from NVIDIA TAO help get you on the fast track to enterprise-grade production with 100+ NVIDIA-optimized model architectures, like vision transformers and fully attentional networks. Fine-tune the models with your own data, enabling a much faster development process.

Watch the webinar, ‘Fast Track AI to the Edge with NVIDIA TAO & Edge Impulse’, to hear from NVIDIA’s Debraj Sinha (Product Marketing Manager), Edge Impulse’s Jan Jongboom (CTO & Cofounder) and Jenny Plunkett (Senior Engineer) about the latest in edge AI and how to leverage pretrained models from NVIDIA to deploy on edge devices.

Learn how to:

  • Build efficient vision ML pipelines faster by combining the power of transfer learning and the latest NVIDIA TAO models across the entire Edge Impulse ecosystem of devices, silicon, and sensors.
  • Profile the performance of your model on different hardware to find the optimal target given your use case and hardware constraints.
  • Efficiently collect data from any edge device and use Edge Impulse auto-labeling tools to increase data quality.
  • Collect data, train and validate your model, and optimize libraries to run on any edge device, from extremely low-power MCUs to efficient Linux CPU targets to any NVIDIA GPU or neural accelerator.
Register nowWatch on DemandRegister now
Speaker:

Debraj 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.

Debraj Sinha
Product Marketing Manager, NVIDIA

Jan Jongboom is an embedded engineer and machine learning advocate, always looking for ways to gather more intelligence from the real world. He has shipped devices, worked on the latest network tech, simulated microcontrollers and there's a monument in San Francisco with his name on it. Currently he serves as the cofounder and CTO of Edge Impulse, the leading development platform for embedded machine learning with 140,000+ projects.

Jan Jongboom
CTO and Cofounder, Edge Impulse

Jenny Plunkett is a software engineer, technical speaker and content creator, working as a Senior Developer Relations Engineer at Edge Impulse. Since graduating from The University of Texas she has been working in the IoT space, from customer engineering and developer support for Arm Mbed to consulting engineering for Pelion IoT. Jenny is co-author of the O’Reilly book "AI at the Edge: Solving Real World Problems with Embedded Machine Learning".

Jenny Plunkett
Senior Developer Relations Engineer, Edge Impulse

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