Recogni Announces 1000 TOPS Class Solution for Autonomous Driving

Microprocessor Report Acknowledges Recogni’s Superior High-Performance Perception Processing at Very Low Power Consumption Over Competitors

SAN JOSE, CA – Recogni, Inc., the leader in AI-based perception for autonomous vehicles, today announced Recogni Scorpio, the world’s first 1000 TOPS (Peta-Op) class inference solution for autonomous mobility. The company’s vision-inference chip enables superhuman object detection accuracy up to – 300m in real-time under various road and environment conditions and the ability to process multiple streams of ultra-high resolution and very high frame rate cameras. Microprocessor Report noted that Recogni’s solution “performs far better” than other inference engines in leading SoCs on the market.

“Vision is fundamental to accurate perception processing and essential to autonomous driving platforms,” said RK Anand, Founder and Chief Product Officer at Recogni. “From the beginning, we took a unique approach of processing high-resolution images at the edge to achieve near-perfect object detection and classification and enable autonomous driving stacks to make better driving decisions. Scorpio can process multiple 8-megapixel streams at 30 frames per second in less than 10 milliseconds using only 25 watts. That’s a performance order of magnitude greater than anything else on the market and, we believe, will help to accelerate autonomous driving to become a reality.”

Currently being evaluated by several top-tier automotive manufacturers and suppliers, Recogni’s solution can achieve 1000 TOPS with less than 10ms of processing delay and below 25 watts of power consumption. This is not only 10-20 times more power efficient than competing solutions, but it enables the flexible design of autonomous driving vehicle stacks and minimizes the impact on driving range. In addition, with such a short processing time of less than 10ms, the Electronic Control Unit (ECU) has more-than-ample time for taking the necessary driving decisions. High compute capacity, efficient processing, low latency, and low power consumption are the pillars of Recogni’s platform.

“Recogni’s purpose built architecture is a unique approach to AI perception, allowing customers to perceive the environment in high resolution with very low latency and low power – this is a game changer for OEMs and suppliers looking to add new, powerful ADAS and self-driving features to new vehicles,” said Marc Bolitho, Chief Executive Officer at Recogni. “Recogni’s unique approach in perception processing is truly first of its kind and enables customers to deploy safe autonomous driving functions and extend the range for electric vehicles.”

Industry Validation

Microprocessor Report’s Bryon Moyer thoroughly evaluated Recogni’s solution and concluded, “As the industry moves to greater resolution, Recogni is well positioned, whereas other SoCs will need an upgrade.” The report also notes that competing SoCs will likely be that upgrade, but it’s “two to three years behind Recogni’s first chip.”

The report details Recogni’s product superiority in terms of supporting high-resolution cameras at high frame rates, support for red/clear/clear/blue (RCCB) image sensors, the approach of minimizing preprocessing before inference, compression algorithms to reduce the required on-chip memory and the product’s self-managing capabilities.

Moyer recognized that “no other stand-alone automotive AI accelerator uses high-resolution cameras and processes each full frame (rather than targeting regions of interest. More common are SoCs that handle inference as one of those many functions.” This is one of the biggest differentiators and advantages of the Recogni solution.


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