INTERPRETING VIA AI: A DISRUPTIVE CYCLE IN OPTIMIZED AND REACHABLE DEEP LEARNING FRAMEWORKS

Machine learning has advanced considerably in recent years, with systems surpassing human abilities in diverse tasks. However, the true difficulty lies not just in developing these models, but in utilizing them optimally in practical scenarios. This is where inference in AI becomes crucial, arising as a primary concern for experts and innovators al