Artificial Intelligence Discovers Alternative Physics

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A new Columbia University AI program observed physical phenomena and uncovered relevant variables—a necessary precursor to any physics theory. But the variables it discovered were unexpected. Energy, Mass, Velocity. These three variables make up Einstein’s iconic equation E=MC2. But how did Alber

Latent embeddings from our framework colored by physical state variables. Credit: Boyuan Chen/Columbia EngineeringAI program observed physical phenomena and uncovered relevant variables—a necessary precursor to any physics theory. But the variables it discovered were unexpected.. But how did Albert Einstein know about these concepts in the first place? Before understanding physics you need to identify relevant variables.

“We thought this answer was close enough,” said Hod Lipson, director of the Creative Machines Lab in the Department of Mechanical Engineering, where the work was primarily done. “Especially since all the AI had access to was raw video footage, without any knowledge of physics or geometry. But we wanted to know what the variables actually were, not just their number.”

Boyuan Chen explains how a new AI program observed physical phenomena and uncovered relevant variables—a necessary precursor to any physics theory. Credit: Boyuan Chen/Columbia Engineering In the experiments, the number of variables was the same each time the AI restarted, but the specific variables were different each time. So yes, there are indeed alternative ways to describe the universe and it is quite possible that our choices aren’t perfect.

 

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