INTERPRETING BY MEANS OF NEURAL NETWORKS: THE ZENITH OF BREAKTHROUGHS IN STREAMLINED AND REACHABLE DEEP LEARNING FRAMEWORKS

Artificial Intelligence has advanced considerably in recent years, with algorithms matching human capabilities in various tasks. However, the main hurdle lies not just in training these models, but in utilizing them efficiently in everyday use cases. This is where machine learning inference comes into play, arising as a primary concern for scientis