Akida is an implementation of a spiking neural network with pre-processing for both real-world signals and digital data. The spiking neural network is a type of artificial neural network that emulates the functionality of the human brain's synapses and neurons. It can be trained using one-shot learning in supervised and unsupervised learning modes, making it applicable to a number of end-market applications including vision systems for civil surveillance, autonomous vehicles, robots and drones, financial technology and cybersecurity.
The Akida chip is relatively small in that is supports 1.2 million neurons and 10 billion synapses between neurons. But the small size makes it low cost and suitable for edge of network applications such as advanced driver assistance systems (ADAS), autonomous vehicles, drones, vision-guided robotics, surveillance and machine vision systems.
It includes sensor interfaces for traditional pixel-based imaging, dynamic vision sensors (DVS), Lidar, audio, and analog signals. It also has high-speed data interfaces such as PCI-Express, USB, and Ethernet. Embedded in the NSoC are data-to-spike converters designed to optimally convert popular data formats into spikes to train and be processed by the Akida Neuron Fabric.
The Akida chip can be networked together to allow scale up so that Akida can be used for complex neural network training and inferencing for many markets including agricultural technology (AgTech), cybersecurity and financial technology (FinTech).
The device is implemented in CMOS logic process but the company did not indicate what choices have been made about digital or temporal resolution for spike amplitude or timing? Nor did the company, which is fabless, indicate where the chips are being manufactured or in what manufacturing process.
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