An ambient computing system comprising: one or more sensors configured to generate sensor signals; and a plurality of processing components including a machine learning engine, and one or more other processing components, wherein the ambient computing system is configured to perform operations comprising: remaining in a monitoring power state until a controller receives an interrupt indicating presence of one or more sensor signals, providing the one or more sensor signals as input to the machine learning engine, wherein the machine learning engine implements a predictive model trained on user-specific data that is specific to a particular user, performing, by the machine learning engine, an inference pass over the predictive model to generate an output representing a particular context that is specific to the particular user, determining, based on the particular context for the particular user, that one or more components of the ambient computing system should be disabled, and in response to said determining that one or more components of the ambient computing system should be disabled, disabling the one or more components of the ambient computing system, characterised in that disabling the one or more components of the ambient computing system comprises disabling one or more of the sensors, disabling a transcription module that automatically transcribes human speech, and/or disabling an I/O channel between the sensors and other components of the ambient computing system. one or more sensors configured to generate sensor signals; and a plurality of processing components including a machine learning engine, and one or more other processing components, wherein the ambient computing system is configured to perform operations comprising: remaining in a monitoring power state until a controller receives an interrupt indicating presence of one or more sensor signals, providing the one or more sensor signals as input to the machine learning engine, wherein the machine learning engine implements a predictive model trained on user-specific data that is specific to a particular user, performing, by the machine learning engine, an inference pass over the predictive model to generate an output representing a particular context that is specific to the particular user, determining, based on the particular context for the particular user, that one or more components of the ambient computing system should be disabled, and in response to said determining that one or more components of the ambient computing system should be disabled, disabling the one or more components of the ambient computing system, characterised in that disabling the one or more components of the ambient computing system comprises disabling one or more of the sensors, disabling a transcription module that automatically transcribes human speech, and/or disabling an I/O channel between the sensors and other components of the ambient computing system. remaining in a monitoring power state until a controller receives an interrupt indicating presence of one or more sensor signals, providing the one or more sensor signals as input to the machine learning engine, wherein the machine learning engine implements a predictive model trained on user-specific data that is specific to a particular user, performing, by the machine learning engine, an inference pass over the predictive model to generate an output representing a particular context that is specific to the particular user, determining, based on the particular context for the particular user, that one or more components of the ambient computing system should be disabled, and in response to said determining that one or more components of the ambient computing system should be disabled, disabling the one or more components of the ambient computing system, characterised in that disabling the one or more components of the ambient computing system comprises disabling one or more of the sensors, disabling a transcription module that automatically transcribes human speech, and/or disabling an I/O channel between the sensors and other components of the ambient computing system.