With a feel for physics, AI models simulate a wider range of real-world scenarios

Artificial intelligence models are jacks of many trades, including writing, generating images, and creating 3D models. But they aren’t as helpful when it comes to testing robots or designs for vehicles in diverse environments, since they don’t understand physics as well as they do.

To build an AI system that can reliably simulate a variety of physical scenarios, engineers need a range of physics data at a scale that isn’t yet feasible. That’s because it’s very time-consuming to get neural networks just a few data points they can.

What Happened

They rely on algorithms called “numerical solvers” to calculate physical properties at different points of a 3D shape. It virtually reenacts everyday mechanical interactions in 3D, showing how particles stop when reaching some part of an object.

• These simulations give the models a sense of how physics works, helping them model the real world more accurately, reach peak performance twice as fast, and train on up to 60 percent less data.

• GeoPT studied 1.3 million samples of synthetic dynamics, in which tiny spheres moved at various speeds and angles until stopping at a certain point on the object.

• The team presented the paper at the International Conference on Machine Learning in July.The researchers’ work was supported, in part, by Neural Modular Physics Twin for Robotics.

Key Details

Soon, the project could help engineers predict how vehicles (like cars and planes), everyday items (including chairs and containers), and robots respond to various physical elements, such as wind, water, and collisions. The researchers believe their work could also be a step.

• Tsinghua University Associate Professor Mingsheng Long was also a co-author.

• For example, a more in-depth approach could help model weather patterns, test out different materials, and generate realistic videos.

• The team hopes to scale up their system, training on even more shapes and simulating more complex physical phenomena.

Why It Matters

To use GeoPT, users simply upload 3D models of objects like battleships, passenger airplanes, and trucks, and specify the direction and speed of the force they want to simulate. The result is a kind of heat map showing how the object will.

• The researchers add that their system is only a preview of the kind of physics world model they’ve been working toward.

• Picture learning about physical interactions using marbles and action figures — similarly, simulation models can use synthetic dynamics to gain a feel for physics before they train on labeled data.

What Reports Say

Coverage of the story so far points to:

• Continued reporting by MIT News as more details emerge