BrainChip, the first commercial provider of neuromorphic AI chips, has announced the second generation of its Akida platform.
The new platform, built for embedded edge AI applications, adds 8-bit processing for higher performance along with new advanced capabilities.
These include using vision transformers and spatial-temporal convolutions for accelerated performance and improved power efficiency at the edge.
BrainChip says the new capabilities of the Akida platform provide critical benefits across a range of industrial, automotive, and smart home and city applications.
The platform is also intended for use in small form factor devices in the healthcare and consumer electronics sectors.
Sean Hehir, CEO of BrainChip, said: “Our customers wanted us to enable expanded predictive intelligence, target tracking, object detection, scene segmentation, and advanced vision capabilities. This new generation of Akida allows designers and developers to do things that were not possible before in a low-power edge device.”
BrainChip uses vision transformers to complete vision processing tasks like image recognition. The company says they are highly effective at object detection and image classification.
The Akida platform’s update also includes Temporal Event Based Neural Nets (TENN) spatial-temporal convolutions. The technology simplifies the processing of streaming data for video analytics, target tracking, and audio classification.
“By inferring and learning from raw sensor data, removing the need for digital signal pre-processing, we take a substantial step toward providing a cloudless Edge AI experience,” Hehir added.
Roger Wendelken, senior vice president of Renesas’ IoT and infrastructure business unit. “We licensed Akida neural processors because of their unique neuromorphic approach to bring hyper-efficient acceleration for today’s mainstream AI models at the edge.”
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