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Tiny machine learning design alleviates a bottleneck in memory usage on internet-of-things devices
An MIT team evaluated memory bottleneck to deploying machine learning on small "internet of things" devices and created a new method and device that outperforms other tinyML methods on image detection and classification tasks.
Shan cai
Wei ming chen
Ji lin
Watson ai lab
National science foundation
Department of electrical engineering
Woodside energy
Watson ai lab research scientist chuang gan
Song han
Electrical engineering
Computer science
Neural information processing systems
National science
Mit ibm watson ai lab
Nternet of things
Edge devices
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