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Vivienne Sze: Crossing the Hardware-Software Divide for Efficient AI


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Vivienne Sze

MIT Associate Professor Vivienne Sze

Lillie Paquette/MIT School of Engineering

Artificial intelligence (AI) applications are moving to smartphones, tiny robots, Internet-connected appliances, and other devices with limited power and processing capabilities. The challenge is that AI has high computing requirements. Analyzing sensor and camera data from a self-driving car can consume about 2,500 watts, but the computing budget of a smartphone is just about a single watt.

In this interview with MIT Associate Professor Vivienne Sze, you will learn why closing this gap requires rethinking the entire stack, a trend that will define the next decade of AI.

From MIT News
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