Sparse Neural Networks (SNNs) are a key innovation for deploying machine learning models on resource-constrained devices, especially in the context of TinyML. Traditional neural networks are dense, meaning most weights between neurons are non-zero. While this helps achieve high accuracy, it makes models memory and compute-intensive, which isn’t ideal for edge devices like microcontrollers or … Continue reading Sparse Neural Networks in Edge-AI-Tiny and Machine Learning