Allegro DVT Partners with SiMa.ai to Optimize Power Efficiency for Embedded Edge Applications

Allegro DVT, the leading provider of video compression and decompression semiconductor IP solutions, announced that SiMa.ai, the machine learning company enabling effortless deployment at the embedded edge, has integrated Allegro’s high performance video Encoding and Decoding IPs into its Machine Learning System on a Chip (MLSoC) Platform.

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SiMa.ai’s purpose-built software and hardware MLSoC Platform, which is available to customers now, is designed to address any computer vision application while delivering 10x better performance per watt with a push-button experience. Seamless power optimization is critical for computer vision applications at the edge. With Allegro DVT’s Encoder and Decoder IPs, SiMa.ai’s customers can achieve high performance with low power without compromising efficiency or ease of use across markets such as smart vision, robotics, industry 4.0, healthcare, government among others.

“When developing our MLSoC Platform, we wanted a partner with the right technology that could meet the machine learning needs of our customers,” said Srivi Dhruvanarayan, VP Hardware Engineering, SiMa.ai. “We required high performance digital video technology and selected Allegro DVT because it offers the best quality digital video compression solution for ultimate performance at the lowest power. Together, we are delivering a comprehensive documentation and software package for easier integration at the edge.”

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Nathalie Brault, COO of Allegro DVT added, “This is an important collaboration for the industry because it combines two cutting edge platforms in our video IPs and SiMa.ai’s MLSoC Platform to deliver best-in-class ML processing at the edge. We are looking forward to being a part of transforming the embedded edge market with SiMa.ai and giving customers the highest power efficiency at their fingertips.”

iMa.ai is a machine learning company delivering the industry’s first software-centric, purpose-built MLSoC platform. With push-button performance, we enable Effortless ML deployment and scaling at the embedded edge by allowing customers to address any computer vision problem while achieving 10x better performance at the lowest power

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