Updating neural network parameters via encoded messages

Abstract

This disclosure provides methods, devices, and systems for machine learning. The present implementations more specifically relate to systems and techniques for updating neural network (NN) parameters via encoded messages. An input device may implement a NN model trained to perform inferencing on input tokens received via one or more sensors of the input device. In some aspects, the input device receives a first input token via the one or more sensors, determines that the first input token includes an encoded message, extracts NN information from the encoded message, and updates one or more parameters of the NN model based on the extracted NN information. In some other aspects, the input device receives a second input token via the one or more sensors, determines that the second input token does not include an encoded message, and performs an inferencing operation on the second input token based on the updated NN model.

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