REASONING WITH COGNITIVE COMPUTING: THE VANGUARD OF IMPROVEMENT IN STREAMLINED AND ATTAINABLE NEURAL NETWORK ARCHITECTURES

Machine learning has advanced considerably in recent years, with systems surpassing human abilities in diverse tasks. However, the real challenge lies not just in training these models, but in deploying them efficiently in practical scenarios. This is where machine learning inference takes center stage, surfacing as a key area for scientists and te