INTERPRETING WITH NEURAL NETWORKS: A CUTTING-EDGE CHAPTER IN STREAMLINED AND ATTAINABLE NEURAL NETWORK SOLUTIONS

AI has made remarkable strides in recent years, with models achieving human-level performance in diverse tasks. However, the real challenge lies not just in creating these models, but in deploying them optimally in practical scenarios. This is where inference in AI comes into play, arising as a primary concern for researchers and tech leaders alike