In recent years, deep learning has proven to be an effective solution to many of the hard problems of artificial intelligence. But deep learning is also becoming increasingly expensive. Running deep neural networks requires a lot of compute resources, training them even more. The costs of deep learning are causing several challenges for the artificial intelligence community, including a large carbon footprint and the commercialization of AI research. And with more demand for AI capabilities away from cloud servers and on “edge devices,” there’s a growing need for neural networks that are cost-effective. While AI researchers have made progress in reducing the costs of…
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