Generative AI

In recent decades, AI has made incredible strides. The origins of the field stem from classical statistical models meticulously designed to help us analyze and make sense of data. As we developed more robust computational methods to process and store data, the field shifted—intersecting computer science and statistics and giving us ML. ML systems could learn complex relationships and surface latent insights from vast amounts of data, transforming our approach to statistical modeling.

This shift laid the groundwork for the rise of deep learning, a substantial step forward that introduced multi-layered neural networks (i.e., a system of interconnected functions) to model complex patterns. Deep learning enabled powerful discriminative models that became pivotal for advancements in diverse fields of research, including image recognition, voice recognition, and natural language processing.

However, the journey continues with the emergence of generative AI. Generative...