INTERPRETING BY MEANS OF NEURAL NETWORKS: A CUTTING-EDGE AGE IN STREAMLINED AND ATTAINABLE AUTOMATED REASONING ARCHITECTURES

Machine learning has advanced considerably in recent years, with systems matching human capabilities in numerous tasks. However, the true difficulty lies not just in developing these models, but in implementing them effectively in everyday use cases. This is where AI inference comes into play, emerging as a critical focus for experts and innovators