BrainChip' Akida and Lorser' SDR for neuromorphic computing in SDR devices
Date: 06/06/2023
BrainChip and Lorser Industries together develop neuromorphic computing solutions by combining BrainChip’s Akida technology and Lorser’s expertise in SDR design and manufacturing for software- defined radio (SDR) devices.
SDR serves vast range of applications including astronomy, aerospace, geography, oceanography, navigation, and logistics. Akida said its neural network processing allows SDR devices to perform advanced tasks such as signal detection, classification, modulation/demodulation, encryption/decryption, and detect anomalies in signal or acoustic data with AI and machine learning (ML).
“We believe that neuromorphic computing is the future of AI/ML, and an SDR with neuromorphic AI/ML capability will offer users significantly more functionality, flexibility, and efficiency,” said Diane Serban, CEO of Lorser Industries. “The Akida processor and IP is the ideal solution for SDR devices because of its low power consumption, high performance, and, importantly, its ability to learn on-chip, after deployment in the field..”
“BrainChip and Lorser share a common interest in creating intelligent devices that can manage communication in a variety of different and evolving environments,” said Rob Telson, Vice President of Ecosystems & Partnerships at BrainChip. “Lorser, with their leadership in advanced SDR technology is the ideal partner for us to work with on a breakthrough device with the ability to utilize AI/ML to identify patterns, detect anomalies and intelligently adapt to a range of scenarios.”
BrainChip' Akida event-based AI neural processor and IP is suggested for advanced AI/ML such as intelligent sensors, medical devices with extended battery life, high-end video-object detection, and ADAS/autonomous systems. BrainChip said it' s Akida neuromorphic architecture can learn real-time on-chip, and limits energy consumption to micro watt to milli-watt ranges, making it ideal for low-power, high-efficiency applications.
