BrainChip Holdings Ltd , the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI IP, and Edge Impulse, the edge AI platform for enterprise teams building innovative products, join to present a technical livestream discussing their collaborative efforts in building an ecosystem for accelerated Edge AI products August 24 at 9 a.m. PDT.
“The world of neuromorphic computing is a truly fascinating one and to some may be perceived as complex”
“A Neuromorphic Deep Dive into Next-Gen AI Solutions” features technical leads from BrainChip and Edge Impulse offering a detailed exploration of BrainChip’s Akida hardware metrics and providing a framework for designing AI models using Edge Impulse. As part of the webinar, attendees will see live demonstrations of models running on BrainChip AKD1000 reference SoC.
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“The world of neuromorphic computing is a truly fascinating one and to some may be perceived as complex,” said Nikunj Kotecha, Senior Solutions Architect at BrainChip. “Through this joint webinar, BrainChip and Edge Impulse will shed more light on how we simplify the development, implementation and deployment of cutting-edge neuromorphic AI models and solutions, to drive innovation in Edge devices. It really is a can’t-miss event.”
BrainChip is the worldwide leader in edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, Akida™, uses neuromorphic principles to mimic the human brain, analyzing only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Akida uniquely enables edge learning local to the chip, independent of the cloud, dramatically reducing latency while improving privacy and data security. Akida Neural processor IP, which can be integrated into SoCs on any process technology, has shown substantial benefits on today’s workloads and networks, and offers a platform for developers to create, tune and run their models using standard AI workflows like Tensorflow/Keras.
SOURCE: Businesswire