Artificial Intelligence is rapidly becoming an indispensable tool in science and engineering, yet many formulators view it as a mysterious "black box."  In reality, one of AI's most powerful technologies, vector databases, operates on principles that coating formulators have unknowingly used for decades through Hansen Solubility Parameters (HSP).

This presentation begins with an intuitive introduction to how AI converts words, images, molecules, and other information into high-dimensional vector embeddings.  These vectors are mathematically compared using similarity measurements to identify relationships, make predictions, and retrieve the most relevant information.  Although the mathematics behind AI may involve hundreds or even thousands of dimensions, the underlying concept is remarkably similar to the three-dimensional coordinate system used in Hansen Solubility Parameters.

Building upon this foundation, the presentation will explore how HSP characterizes materials according to their Dispersion (δD), Polar (δP), and Hydrogen Bonding (δH) interactions.  By calculating distances between materials in this three-dimensional space, formulators can predict compatibility among polymers, solvents, pigments, additives, and other raw materials reducing costly laboratory trial-and-error while accelerating formulation development.

Practical examples will demonstrate how HSP can be used to identify alternative solvents, optimize resin compatibility, improve pigment dispersion, enhance active ingredient delivery, and solve common formulation challenges.  Throughout the presentation, attendees will discover that although AI vector databases and Hansen Solubility Parameters were developed for different purposes, they both rely on the same elegant scientific principle: materials or information that are mathematically close together are more likely to behave similarly . . . “Like Likes Like.”

By connecting these two seemingly unrelated technologies, formulators will gain not only a deeper appreciation for Hansen Solubility Parameters, but also a practical understanding of why vector databases have become one of the foundational technologies driving today's AI revolution.  This presentation demonstrates that the future of formulation science lies at the intersection of chemistry, mathematics, and artificial intelligence, providing a powerful framework for developing the next generation of smarter, more sustainable, and higher-performing coatings.