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

Artificial Intelligence has made remarkable strides in recent years, with systems surpassing human abilities in diverse tasks. However, the true difficulty lies not just in developing these models, but in deploying them optimally in everyday use cases. This is where machine learning inference becomes crucial, emerging as a primary concern for scien