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New AI helps solve engineering mathematics much faster

Dec. 09, 2024.
2 mins. read. 1 Interactions

A new AI system can speed up calculations across science and engineering, reducing computing time from hours or days to seconds.

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Giulio Prisco

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Giulio Prisco is Senior Editor at Mindplex. He is a science and technology writer mainly interested in fundamental science and space, cybernetics and AI, IT, VR, bio/nano, crypto technologies.

Modeling how cars crash, spacecraft endure harsh conditions, or bridges handle stress could soon be much faster. Researchers at Johns Hopkins University have developed a new artificial intelligence (AI) system called DIMON. This AI framework helps personal computers quickly solve large math problems usually needing supercomputers.

DIMON tackles partial differential equations, which are math formulas used to predict how things like fluids or electricity move through different shapes. These equations are crucial in engineering for understanding how systems will behave over time and space.

The researchers have described DIMON in a paper published in Nature Computational Science.

DIMON can speed up a wide range of engineering computations

DIMON can work on any problem across science and engineering. It’s particularly useful for tasks where shapes, forces, or materials change, like in crash tests or medical research.

For example, the team used DIMON to study heart health by creating “digital twins” of patients’ hearts. These models predict how electrical signals move through unique heart shapes, helping diagnose and treat cardiac arrhythmia.

Solving these equations traditionally takes a lot of time because you need to break down complex shapes into small parts and re-solve for each change in shape. DIMON, however, learns patterns from one shape and applies them to others, making the process thousands of times faster.

It reduces computing time from hours or days to just seconds, right on a desktop computer.

“With this new AI approach, the speed at which we can have a solution is unbelievable,” says research co-leader Natalia Trayanova in a Johns Hopkins University press release. “The time to calculate the prediction of a heart digital twin is going to decrease from many hours to 30 seconds.

She adds that this will be done on a desktop computer rather than on a supercomputer, allowing doctors to make it part of the daily clinical workflow.

DIMON could help in any field where shapes and their behaviors are key to solving problems, from designing better car parts to improving spacecraft materials.

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