PREDICTING THROUGH AUTOMATED REASONING: A TRANSFORMATIVE PERIOD IN STREAMLINED AND REACHABLE NEURAL NETWORK ARCHITECTURES

Artificial Intelligence has made remarkable strides in recent years, with systems achieving human-level performance in diverse tasks. However, the main hurdle lies not just in developing these models, but in deploying them optimally in everyday use cases. This is where machine learning inference becomes crucial, emerging as a primary concern for sc