Researchers tout AI that can predict 25 video frames into the future

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AI video prediction

AI and machine learning algorithms are becoming increasingly good at predicting next actions in videos. The very best can anticipate fairly accurately where a baseball might travel after it has been pitched, or the appearance of a road miles from a starting position. To this end, a novel approach proposed by researchers at Google, the University of Michigan, and Adobe advances the state of the art with large-scale models that generate high-quality videos from only a few frames. All the more impressive, it does so without relying on techniques like optical flows (the pattern of apparent motion of objects, surfaces, or edges in a scene) or landmarks, as previous methods have.

“In this work, we investigate whether we can achieve high-quality video predictions … by just maximizing the capacity of a standard neural network,” wrote the researchers in a preprint paper describing their work. “To the best of our knowledge, this work is the first to perform a thorough investigation on the effect of capacity increases for video prediction.”

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