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Continuing the evolution of AI at the edge, the 2nd Generation Akida provides enhanced capabilities for modern applications. This upgrade implements 8-bit quantization for increased precision and introduces support for Vision Transformers and temporal event-based neural networks. The platform handles advanced cognitive tasks seamlessly with heightened accuracy and significantly reduced energy consumption. Designed for high-performance AI tasks, it supports complex network models and utilizes skip connections to enhance speed and efficiency.
BrainChip's Akida is an advanced neuromorphic processor that excels in efficiency and performance, processing data similar to the human brain by focusing on essential sensory inputs. This approach drastically reduces power consumption and latency compared to conventional methods by keeping AI local to the chip. Akida’s architecture, which scales to support up to 256 nodes, allows for high efficiency with a small footprint. Nodes in the Akida system integrate Neural Network Layer Engines configurable as either convolutional or fully connected, maximizing processing power by handling data sparsity through event-based operations.
The Akida1000 Reference SoC exemplifies how advanced AI processing units can be integrated into real-world systems. Empowering developers through a fully operational prototype, it enables the creation of sophisticated, intelligent systems like autonomous vehicles and smart homes. With architectures supporting 1.2 million neurons and 10 billion synapses, it can function as both a stand-alone AI accelerator and a supporting co-processor, accommodating varied applications that demand real-time responsiveness and high computational throughput.
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