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PyTorch New York Meetup (Virtual) on June 7th: Video Replay Available

SusanK_Intel1
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6/15/23 Blog edited with Link added to video replay

It’s no secret that PyTorch is one of the most popular deep learning frameworks out there. You don’t have to venture too far to see how it is being used to shape the technology of the future. However, what you may not know is the influence that Intel has in its continued development.

See a video replay of the NYC PyTorch Meetup from Wednesday, June 7, 2023 at 11 AM EDT.

In this talk, we introduced the Intel® Optimization for PyTorch* as well as the high-performance libraries that it is built on. We demonstrated how it can be used to achieve significant performance accelerations with just a few lines of code changes. We also discussed some best practices for getting the most optimal performance. By the end of the talk, you will have a better understanding of how to use the Intel® Optimization for PyTorch to get the most of out of your deep learning workloads.

This event was hosted by the Linux Foundation.

Thanks to Deborah Jacob for the opportunity to present at the NYC PyTorch meeting!

We encourage you to learn more about and incorporate Intel’s other AI/ML Framework optimizations and end-to-end portfolio of tools into your AI workflow. Also, visit AI & ML page to learn about Intel’s AI software development resources to prepare, build, deploy, and scale AI solutions.

About our expert

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Kevin Ta is an AI Software Solutions Engineer in the Software and Advanced Technology Group at Intel Corporation. He enables customers to develop and accelerate their AI workflows using performance optimizations provided by Intel’s artificial intelligence and data analytics product line. He holds a Ph.D. in Engineering & Applied Science with a focus on medical image analysis and a B.S. in Biomedical Engineering with a specialization in bioinstrumentation and electronic systems.

 

 

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About the Author
Susan is a Product Marketing Manager for AIML at Intel. She has her Ph.D. in Human Factors and Ergonomics, having used analytics to quantify and compare mental models of how humans learn complex operations. Throughout her well-rounded career, she has held roles in user-centered design, product management, customer insights, consulting, and operational risk.