MACHINE LEARNING REASONING: THE APPROACHING PARADIGM ACCELERATING AVAILABLE AND OPTIMIZED NEURAL NETWORK ADOPTION

Machine learning has made remarkable strides in recent years, with algorithms achieving human-level performance in numerous tasks. However, the main hurdle lies not just in training these models, but in implementing them effectively in real-world applications. This is where machine learning inference takes center stage, emerging as a critical focus