NEURAL NETWORKS REASONING: THE APPROACHING LANDSCAPE TOWARDS REACHABLE AND EFFICIENT MACHINE LEARNING ARCHITECTURES

Artificial Intelligence has made remarkable strides in recent years, with algorithms matching human capabilities in diverse tasks. However, the main hurdle lies not just in training these models, but in implementing them optimally in real-world applications. This is where machine learning inference comes into play, arising as a primary concern for