Brainchip Extends AI, Machine Learning In Space And Time With Bio-Inspired Neural Networks

With artificial intelligence and machine learning (AI/ML) processors and coprocessors roaring across the embedded edge product landscape, the quest continues for high-performance technology that can run a wide range of AI/ML models with very low power consumption. Brainchip has been marketing a line of unique, bio-inspired Akida line of licensable, configurable neural processing IP for a while now. The company's synthesizable IP is designed to efficiently implement AI/ML workloads as an on-chip CPU coprocessor that demands little CPU intervention. Now, the company has introduced its second-generation Akida AI/ML neural-processing coprocessor architecture, which improves upon the first-generation IP architecture in several ways. The company's Akida IP runs standard neural-network models built with standard AI/ML tool flows, but this IP uniquely leverages the energy-efficient organic brain architectures produced over more than 100 million years of evolution, implementing cognitive AI/ML processing using a bio-inspired but fully digital approach to neural processing.