PREDICTING THROUGH AUTOMATED REASONING: A TRANSFORMATIVE PERIOD FOR STREAMLINED AND ATTAINABLE NEURAL NETWORK FRAMEWORKS

Artificial Intelligence has advanced considerably in recent years, with models achieving human-level performance in various tasks. However, the real challenge lies not just in training these models, but in deploying them optimally in practical scenarios. This is where inference in AI becomes crucial, emerging as a critical focus for experts and inn

Machine learning has achieved significant progress in recent years, with models surpassing human abilities in numerous tasks. However, the real challenge lies not just in creating these models, but in implementing them efficiently in real-world applications. This is where AI inference takes center stage, arising as a critical focus for scientists a