This AI finds simple rules where humans see only chaos
A new AI developed at Duke University can uncover simple, readable rules behind extremely complex systems. It studies how systems evolve over time and reduces thousands of variables into compact equations that still capture real behavior. The method works across physics, engineering, climate science, and biology. Researchers say it could help scientists understand systems where traditional equations are missing or too complicated to write down.
Partial differential equations (PDEs) are a class of mathematical problems that represent the interplay of multiple variables, and therefore have predictive power when it comes to complex physical systems. Solving these equations is a perpetual challenge, however, and current computational techniques for doing so are time-consuming and expensive.
For more than 250 years, mathematicians have wondered if the Euler equations might sometimes fail to describe a fluid’s flow. Now there’s a breakthrough.