COMPUTING WITH NEURAL NETWORKS: THE VANGUARD OF IMPROVEMENT TRANSFORMING EFFICIENT AND AVAILABLE NEURAL NETWORK ARCHITECTURES

Artificial Intelligence has made remarkable strides in recent years, with models matching human capabilities in diverse tasks. However, the main hurdle lies not just in developing these models, but in deploying them effectively in practical scenarios. This is where inference in AI takes center stage, arising as a primary concern for researchers and

AI has achieved significant progress in recent years, with systems surpassing human abilities in numerous tasks. However, the real challenge lies not just in creating these models, but in implementing them efficiently in everyday use cases. This is where machine learning inference becomes crucial, surfacing as a key area for experts and tech leader