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Revolutionizing Embedded Computer Vision with Cutting-Edge AI Processors

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Manage episode 422964913 series 3574631
Indhold leveret af EDGE AI FOUNDATION. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af EDGE AI FOUNDATION eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

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Unlock the secrets to high-efficiency embedded computer vision with industry experts Sandeep Mistry from Arm and Alex Chang from Himax Technology. We promise insights into the TinyML community and the collaborative efforts that are setting new benchmarks in the field. Alex Chang shares an in-depth look at Himax Technology’s cutting-edge AI processors and always-on sensors designed for low-power, battery-operated devices. Learn how Himax’s dual-mode CMOS sensors are revolutionizing applications like doorbells and smart devices, and why efficient AI processing at the edge is increasingly crucial.
Curious about the architecture of state-of-the-art AI processors? Discover the intricate details of a sophisticated Wi-Fi processor designed specifically for AI applications. We explore groundbreaking features such as DC-DC converters, dynamic voltage and frequency scaling (DVFS), and advanced security measures like Physical Unclonable Functions (PUF) and qubit-toe accelerators. You'll also understand how specialized hardware accelerators for motion detection, JPEG decoding, and voice detection enhance comprehensive audio and video AI processing. The development ecosystem, complete with essential software tools and downloadable resources on GitHub, is laid out to ease your implementation process.
Ready to see AI in action? Follow our guided process of porting a pose estimation model to the iMac's YSI2 processor, aimed at tasks like fall detection and human-machine interfaces. We detail how to use a modified version of the UltraLytics GLLv8 postmodel for better accuracy and how to optimize the model for the ARM Ethos U55 MPU using the Ethos U Vella compiler. Witness a live demo showcasing the model’s real-time performance, achieving over 10 frames per second. We wrap up with a discussion on revolutionary partnerships driving Edge AI forward, spotlighting contributions from companies like Syntient, Atreus, ARM, and many others. Don't miss this chance to stay at the forefront of embedded computer vision and Edge AI technology!

Support the show

Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org

  continue reading

Kapitler

1. High Efficiency Embedded Computer Vision (00:00:00)

2. High-Performance AI Processor Ecosystem (00:17:28)

3. Model Porting to iMac Processor (00:25:55)

4. Revolutionizing Edge AI Partnerships (00:41:55)

20 episoder

Artwork
iconDel
 
Manage episode 422964913 series 3574631
Indhold leveret af EDGE AI FOUNDATION. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af EDGE AI FOUNDATION eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Send us a text

Unlock the secrets to high-efficiency embedded computer vision with industry experts Sandeep Mistry from Arm and Alex Chang from Himax Technology. We promise insights into the TinyML community and the collaborative efforts that are setting new benchmarks in the field. Alex Chang shares an in-depth look at Himax Technology’s cutting-edge AI processors and always-on sensors designed for low-power, battery-operated devices. Learn how Himax’s dual-mode CMOS sensors are revolutionizing applications like doorbells and smart devices, and why efficient AI processing at the edge is increasingly crucial.
Curious about the architecture of state-of-the-art AI processors? Discover the intricate details of a sophisticated Wi-Fi processor designed specifically for AI applications. We explore groundbreaking features such as DC-DC converters, dynamic voltage and frequency scaling (DVFS), and advanced security measures like Physical Unclonable Functions (PUF) and qubit-toe accelerators. You'll also understand how specialized hardware accelerators for motion detection, JPEG decoding, and voice detection enhance comprehensive audio and video AI processing. The development ecosystem, complete with essential software tools and downloadable resources on GitHub, is laid out to ease your implementation process.
Ready to see AI in action? Follow our guided process of porting a pose estimation model to the iMac's YSI2 processor, aimed at tasks like fall detection and human-machine interfaces. We detail how to use a modified version of the UltraLytics GLLv8 postmodel for better accuracy and how to optimize the model for the ARM Ethos U55 MPU using the Ethos U Vella compiler. Witness a live demo showcasing the model’s real-time performance, achieving over 10 frames per second. We wrap up with a discussion on revolutionary partnerships driving Edge AI forward, spotlighting contributions from companies like Syntient, Atreus, ARM, and many others. Don't miss this chance to stay at the forefront of embedded computer vision and Edge AI technology!

Support the show

Learn more about the EDGE AI FOUNDATION - edgeaifoundation.org

  continue reading

Kapitler

1. High Efficiency Embedded Computer Vision (00:00:00)

2. High-Performance AI Processor Ecosystem (00:17:28)

3. Model Porting to iMac Processor (00:25:55)

4. Revolutionizing Edge AI Partnerships (00:41:55)

20 episoder

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