Models are the foundation for predicting outcomes and forming business decisions from data. Models range from simple trend analysis to deep complex predictors and precise descriptions of how variables behave. Eureqa specializes in being able to learn “analytical models” from data—that is, models that can be analyzed, interpreted, and understood. In the past, analytical models have remained the most challenging type of model to obtain, requiring incredible skill and knowledge to create. However, modern AI today can infer these models directly from data.
A mathematical model (or analytical model) is a “description of a system using mathematical concepts and language. Mathematical models are used not only in the natural sciences (such as physics, biology, earth science, meteorology) and engineering disciplines (e.g., computer science, artificial intelligence), but also in the social sciences (such as economics, psychology, sociology, and political science). A model may help to explain a system and to study the effects of different components, and to make predictions about behavior.”
An example analytical model inferred by AI from data (Eureqa)
There’s a reason why every field of science uses math to describe and communicate the intrinsic patterns and concepts in nature, and why business analysts design mathematical models to analyze business outcomes. Essentially, these models give the most accurate predictions and the most concise explanation behind them. They allow us to forecast into the future and understand how things will react under entirely new circumstances.
Analytical models tend to use the least amount of complexity possible in order to achieve the same accuracy. Instead of assuming a particular type of model, the structure of the model is specific to the system being modeled. The drawback to analytical models is that they require significant amounts of computational effort.
Eureqa’s algorithm solves this problem efficiently at scale, and we’ve already seen major impacts in both science/research and business/enterprise. For me personally, I’m most excited by the prospect of using analytical modeling to allow AI and the machines to make discoveries in the data we collect and then interpret them back to us automatically. Automation has never been so beneficial.