BrainChip AKD1500 is an ultra-efficient Edge AI co-processor delivering up to 800 GOPS while consuming just 300 mW of power, making it suitable for battery-powered wearables and IoT sensors. It’s based on the same event-based neuromorphic technology found on the earlier AKD1000, relying on spiking neural networks (SNN) to deliver real-time inference in a way that is much more efficient than traditional AI chips. What’s new here is that thanks to PCIe and SPI interfaces, the new ADK1500 co-processor can be paired to a wide range of hosts, ranging from Linux-capable application processors to resource-constrained microcontrollers with x86, Arm, or RISC-V architectures. BrainChip AKD1500 key features and specifications: Akida Neuron Fabric Clocked at 5 to 400 MHz Delivering up to 800 effective GOPS at <1mW/GOPS On-device learning capabilities to enable “secure application personalization, without the need for a Cloud connection or retraining” On-Chip Conversion Complex Memory/Storage 1MB on-chip local memory […]
Brainchip AKD1500 PCIe/SPI Edge AI co-processor to power battery-operated wearables and IoT devices
