Is neuromorphic computing the future of visual perception in machines?

Technology companies specializing in compact, energy-efficient edge computing devices are actively working to enhance their devices' capabilities to enable visual perception in machines for applications like facial recognition. Typically, visual perception demands significant computational resources when deployed remotely on edge devices, leading to reduced latency and the ability to make real-time decisions.

Historically, the conventional use of deep learning and machine learning neural hardware, along with GPUs, has shown inefficiency in terms of energy consumption, especially when deployed near the …

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