INTERPRETING VIA MACHINE LEARNING: THE APPROACHING PARADIGM IN REACHABLE AND STREAMLINED NEURAL NETWORK ADOPTION

AI has advanced considerably in recent years, with models achieving human-level performance in various tasks. However, the true difficulty lies not just in training these models, but in deploying them optimally in everyday use cases. This is where inference in AI comes into play, surfacing as a key area for researchers and innovators alike.Understa