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Bringing development of BrainChip Akida Neuromorphic models to all using Edge Impulse
Edge Impulse and BrainChip have partnered to bring the power of neuromorphic computing to all developers. Join us for an early look at the capabilities available for the Edge Impulse + BrainChip integration, and learn how to build and deploy efficient BrainChip Akida Neuromorphic models using Edge Impulse platform.


Key Topics:

- The no-code data ingestion, algorithm development, and embedded Akida deployment tools allow for rapid prototyping and validation of Edge ML algorithms with custom data.

- The Akida platform enables energy efficient, low memory, and high performance deployments, compared with traditional CPU and accelerated AI hardware.

- The MetaTF library (via deployment option) will allow for existing projects to be quickly converted to Akida SNN’s (with the above benefits, and low-to-no-code path)
Quantization aware training ensures that model remain accurate after conversion.

- The Edge Impulse Linux CLI and its integration with the Akida runtime allows for rapid performance testing with real world data


Speakers:

Todd Vierra - Director Customer Engagement - Brainchip
Nikunj Kotecha - Solutions Architect - Brainchip
David Schwartz - User Success Engineer - Edge Impulse


Featured Hardware (not required for attendance):
1x Akida SoC Development PCIe development kit
1x Linux ARM/x86 host system
1x USB camera


GDPR & PRIVACY

Edge Impulse is committed to protecting and respecting your privacy, and we’ll only use your personal information to provide the products and services you requested from us. From time to time, we would like to contact you about our products and services, as well as other content that may be of interest to you. By joining this webinar you agree to receive other communications from Edge Impulse and you can opt-out at anytime.

We would also like to share your details with BrainChip for the purposes of the webinar. If you would prefer for your details not to be shared, please email hello@edgeimpulse.com.

00:57:00

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Speakers

Todd Vierra
Director Customer Engagement @Brainchip
Todd brings more than 25 years of engineering and technical sales expertise in chip design, electronic design automation, and intellectual property. He joined BrainChip from ARM, where he was director of field sales engineers for more than 15 years, providing support for ARM processors in the Machine Learning, Internet of Things (IoT), embedded and automotive, client/mobile, and enterprise business divisions. He spent nearly seven years in high-speed ASIC design at Applied Micro Systems, and 4 years at Cadence Design Systems. At Nurlogic Design Inc., and Artisan Components Todd led the technical sales teams for digital and high-speed Analog IP. He has a BS Electrical, Electronics, and Communications Engineering and an MBA from Coleman University.
Nikunj Kotecha
Solutions Architect @Brainchip
Nikunj Kotecha is a Machine Learning Solutions Architect at BrainChip Inc. Currently, he works on developing and optimizing Machine Learning algorithms for the Akida neuromorphic hardware. He also demonstrates capabilities of Akida to clients and supports with their neuromorphic solutions for Akida. He has a Master of Science in Computer Science, where he specialized in concepts of Artificial intelligence with Deep Learning algorithms. At the time, he was a part of the Machine Learning lab and has published technical papers, supported research into different avenues of AI. He published research on Cross-Modal Fusion with Transformer architecture for Sign Language translation during the completion of his Masters. He has also worked at Oracle, where he build and integrated Machine Learning solutions to provide operational benefits of using Oracle Clinical Trial software.
David Schwarz
User Success Engineer @Edge Impulse
David Schwarz is a User Success Engineer at Edge Impulse, helping customers build and deploy products powered by machine learning. He is a University of Texas graduate with previous experience in embedded systems design and applications engineering.