AI Processing: The Bleeding of Growth accelerating Resource-Conscious and Accessible Machine Learning Architectures
Machine learning has made remarkable strides in recent years, with algorithms matching human capabilities in diverse tasks. However, the true difficulty lies not just in creating these models, but in deploying them efficiently in real-world applications. This is where inference in AI takes center stage, surfacing as a critical focus for researchers