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Orr Danon, CEO of Hailo, presents the “Emerging Processor Architectures for Deep Learning: Options and Trade-offs” tutorial at the May 2019 Embedded Vision Summit.

In the past year, numerous new processor architectures for machine learning have emerged. Many of these focus on edge applications, reflecting the growing demand for deploying machine learning outside of data centers. This intensive focus on processor architecture innovation comes at a perfect time in light of the slowing progress in silicon fabrication technology and the massive opportunities for deployment of AI applications using vision and other sensors.

In this presentation, Danon explores the architectural concepts underlying these diverse processors and analyzes their suitability for various applications. He derives the performance bounds of each architecture approach and provides insights on the practical deployment of machine learning using these specialized architectures. In addition, using a case study, he explores the opportunities enabled through designing neural networks to exploit specialized processor architectures.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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