New deep learning technique paves path to pizza-making robots

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For humans, working with deformable objects is not significantly more difficult than handling rigid objects. We learn naturally to shape them, fold them, and manipulate them in different ways and still recognize them.

But for robots and artificial intelligence systems, manipulating deformable objects present a huge challenge. Consider the series of steps that a robot must take to shape a ball of dough into pizza crusts. It must keep track of the dough as it changes shape, and at the same time, it must choose the right tool for each step of the work. These are challenging tasks for current AI systems, which are more stable in handling rigid-body objects, which have more predictable states.

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Mike is a Staff Writer for Geeker. For over 14 years, he has written about technology and tech history for sites such as The Atlantic, Fast Company, PCMag, PCWorld, Macworld, Ars Technica, and Wired. As a collector of vintage computers and video games for over 25 years, he brings a deep sense of history to his writings and uses that to inform his works on the past, present, and the future of tech.

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