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[D] Any references on building models that infer real world physics?

Hi! I have been wondering about how to build a model that learns to infer the physics of environments from its input.

More specifically: how to build a model that takes input videos of, let’s say, objects falling down ( a glass being pushed from a table, an apple falling from a tree, etc.) and then makes the inference that things tend to fall to the ground? The model does not have to figure out any mathematical formula for calculating the gravitational force. Learning the common sense physics as humans do is what I am primarily interested in.

Has anyone come across research that addresses this problem or a similar problem? I would greatly appreciate any help. Thanks in advance! 🙂

submitted by /u/darthmeshkat
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.