Machine learning provides powerful tools to researchers to identify and predict patterns and behaviors, as well as learn, optimize, and perform tasks. This ranges from applications like vision systems on autonomous vehicles or social robots to smart thermostats to wearable and mobile devices like smartwatches and apps that can monitor health changes. While these algorithms and their architectures are becoming more powerful and efficient, they typically require tremendous amounts of memory, computation, and data to train and make inferences.
Read more : Tiny machine learning design alleviates a bottleneck in memory usage on internet-of-things devices.
