Tech Alert: BrainChip Showcases Compelling Benchmarks and...

Tech Alert: BrainChip Showcases Compelling Benchmarks and Recommends Better Metrics for AI Devices at the Edge

JAN 15, 2023 5:30PM
LAGUNA HILLS, CA / ACCESSWIRE / January 15, 2023 / A new white paper by BrainChip Holdings Ltd (ASX:BRN)(OTCQX:BRCHF)(ADR:BCHPY), the world's first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI IP, evaluates the current state of edge AI benchmarks and the need to continually improve metrics that measure performance and efficiency of real-world, power-conscious edge AI deployments.

Current industry benchmarks measuring edge AI inference performance have started to capture the challenges of edge devices operation over the traditional TOPS rating. The paper, "Benchmarking AI Inference at the Edge: Measuring Performance and Efficiency for Real-World Deployments," recommends the additional factors required to holistically gauge the performance and efficiency needed to enable compelling, optimized AI applications for complex, multi-modal edge environments.

BrainChip's paper examines the limits of conventional AI performance benchmarks; discusses balancing performance and power at the edge; compares performance and energy efficiency with the tinyML benchmarks from MLCommons, which have made a good start towards identifying use cases; and shows how edge AI inference performance and efficiency is maximized with Akida™. It illustrates how various factors like model size, load times and system bandwidth can play a significant part in the overall result but aren't currently accounted for. This is an area where the consortia should, and are, actively collaborating to improve. But there is room for more.

"While there's been a good start, current methods of benchmarking for edge AI don't accurately account for the factors that affect devices in industries such as automotive, smart homes and Industry 4.0," said Anil Mankar, Chief Development Officer at BrainChip. "We believe that as a community, we should evolve benchmarks to continuously incorporate factors such as on-chip, in-memory computation and model sizes to complement the latency and power metrics that are measured today."

To learn more about the importance of balancing these important criteria and better understand how BrainChip's unique approach of event-based, neuromorphic design delivers compelling results, interested parties can download the white paper at https://www.brainchipinc.com/.