Spiked Neural Networks are implemented by Neuromorphic, a brain-inspired ASIC (SNNs). Its aim is to obtain massively parallel brain computing power in the 10 watts range. Memory and processing units are combined into a single abstraction (in-memory computing). In complex environments, this leads in the benefit of dynamic, self-programmable behaviour. Neuromorphic chips provide a range of advantages, involving high speed, low power consumption, cognitive computing, and optimum memory use. Aerial surveillance, satellite imaging, and audio and signal processing are among a few of the applications for these devices. A wide range of industry verticals, including consumer electronics, automotive, robotics, and military and defence, have shown strong demand.

Neuromorphic chips can be built digitally, analogically, or hybridically. Analog chips more closely reflect the biological features of brain networks than digital processors. In the analog architecture, few transistors are used for imitating the differential equations of neurons. As a result, they use less energy than digital neuromorphic chips in general. Furthermore, they have the ability to extend the processing period beyond the time allotted. This feature allows the pace to be increased to process data faster than in real-time.

Research and Investment on Neuromorphic Chips

Apple launched the M1 Chip, which was specifically created for Mac devices. Apple Neural Engine is introduced to the Mac by the M1 Chip, which accelerates deep learning tasks. The 16-core design is capable of doing 11 trillion operations per second, allowing for up to 15x quicker machine learning performance – In November 2020.

Janux GS31 is a First Edge Optimized AI Inference Server designed by SolidRun and Gyrfalcon that supports primary neural network frameworks. For improved inference performance for most complicated video AI models, it may be configured with up to 128 Gyrfalcon Lightspeeur SPR2803 AI acceleration chips – In March 2020. 

GrAI Matter Labs introduced the GrAI VIP, or Vision Inference Processor, a full-stack AI system-on-chip platform that will accelerate visual inference capabilities in robotics, industrial automation, AR/VR, and surveillance products and markets. GrAI VIP uses GrAI Matter Labs' proven NeuronFlow event-based dataflow computing engine, which allows up to 100x faster inference latency than competitor alternatives – January 2021. 

Future of Neuromorphic Chips

Neuromorphic chips are also expected to be used in a variety of  IT technologies, including face recognition, voice recognition, robots, drones, autonomous vehicles, and wearable devices, all of which are significant next-generation technologies that will play a significant role in the 4th Industrial Revolution. More advanced IT technologies, such as an AI doctor who can detect sickness with high accuracy or a fully autonomous automobile that requires no human interaction, will be facilitated by neuromorphic technology. Neuromorphic chips have a lot of potential for growth because of its high usage rate.