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TinyML is a sub-branch of machine learning that focuses on lightweight algorithms capable of running on a device, rather than on a server, with low power consumption and memory overheads. This technology offers enhanced integration of existing ML models on memory-restricted devices and offers confidentiality baked in as the models are run locally and do not require data to be transmitted to third party providers. TinyML can be used to mitigate the confidentiality issues and infrastructural burden of services such as ChatGPT, as well as to comply with certain laws, treaties, or agreements.