EXECUTING WITH NEURAL NETWORKS: THE BLEEDING OF EVOLUTION REVOLUTIONIZING RESOURCE-CONSCIOUS AND ACCESSIBLE MACHINE LEARNING ARCHITECTURES

Machine learning has achieved significant progress in recent years, with systems surpassing human abilities in various tasks. However, the main hurdle lies not just in developing these models, but in utilizing them effectively in real-world applications. This is where AI inference becomes crucial, emerging as a key area for experts and tech leaders