INTERPRETING BY MEANS OF NEURAL NETWORKS: THE UNFOLDING FRONTIER FOR ATTAINABLE AND STREAMLINED COGNITIVE COMPUTING ADOPTION

AI has advanced considerably in recent years, with models matching human capabilities in diverse tasks. However, the true difficulty lies not just in creating these models, but in deploying them efficiently in practical scenarios. This is where machine learning inference comes into play, emerging as a key area for scientists and innovators alike.De

Machine learning has achieved significant progress 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 real-world applications. This is where inference in AI comes into play, arising as a critical focus for experts and