Stochastic Computing

Stochastic computing (SC) represents a paradigm shift in computation, trading precision for significantly reduced hardware complexity and energy consumption by representing numbers as probability streams. Current research focuses on applying SC to machine learning, particularly in resource-constrained environments like the Internet of Things, using novel architectures like stochastic finite-state machines and integrating SC into spiking neural networks and attention mechanisms. This approach shows promise for accelerating inference in applications such as image processing and deep learning, leading to more energy-efficient and potentially faster devices for various fields, including autonomous systems and medical imaging.