What changes with machine learning, large language models, generative AI, and ChatGPT in search and discovery? EVERYTHING!

This paper provides a primer on the necessary basics of an Artificial Intelligence (AI) system and how some of the systems approach certain methodologies. It also stresses data quality as input to AI systems and shows examples of some criteria of which to be aware when training an AI algorithm, such as the system keying in on anomalous parameters, loopholes in the logic when designing the system, and the origin of data sources.