Most AI accelerators currently rely on CNN (convolutional neural network) to perform AI inference in a much faster and efficient way than on CPU cores, or even GPUs. But there’s another type of neural network, namely spiking neural networks (SNN) that uses the timing of spikes in an electrical signal to perform pattern recognition tasks in a way similar to neurons in the brain. The claims in terms of efficiency are quite unbelievable, with up to 10,000 times more performance per watts than in microprocessor and digital accelerometer, 500 times lower energy, and 100 times shorter latency. Several companies are working on neuromorphic AI accelerators for spiking neural networks, with notably Prophesee focusing on image processing, and Innatera that is working on an ultra-low-power AI accelerator handling audio, health, and radar for sound and speech recognition, vital signs monitoring, elderly person fall sensors, etc… Innatera recently provided additional information about […]
Innatera neuromorphic AI accelerator for spiking neural networks (SNN) enables sub-mW AI inference
