Edge Computing.
Breaking size, weight, and power barriers also increases the ubiquity of AI and aids privacy protection. Companies are working to pack more computational power into tighter, specialized chips that use less energy to train and run the same models. Such chips allow consumer devices to run complex models locally, rather than transmit data externally and wait for models to run remotely. Retaining data entirely on the device where a model is being trained or run is an advancement that could potentially enhance individual privacy in AI-powered systems.
Source https://www.nscai.gov/wp-content/uploads/2021/01/NSCAI-Draft-Final-Report-1.19.21.pdf
Makes interesting reading on AI and US Strategy although a bit long -
2020 BRN Discussion, page-25898
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