Auto-capture of interesting moments by assistant systems

One or more computer-readable non-transitory non-volatile storage media embodying software that is operable when executed to:

• access, from a client system associated with a first user, one or more sensor signals captured by one or more sensors of the client system, wherein the client system comprises a plurality of sensors, and wherein the one or more sensors signals are accessed from the one or more sensors based on one or more cascading model policies, wherein each cascading model policy utilizes one or more of a respective cost or relevance associated with each sensor;
• detect, based on one or more machine-learning models and the one or more sensor signals, a change in a context of the first user associated with an activity of the first user, wherein the change in the context of the first user satisfies a trigger condition associated with the activity;
• and
• automatically capture, responsive to the detected change in the context of the first user, visual data by one or more cameras of the client system,
• wherein each cascading model policy utilizes a respective cost associated with each sensor, and wherein each cascading model policy specifies accessing a first sensor signal from a first sensor associated with a first cost before accessing a second sensor signal from a second sensor associated with a second cost if the first cost is lower than the second cost.

A system comprising:

• one or more processors;
• and a non-transitory non-volatile memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to:
• access, from a client system associated with a first user, one or more sensor signals captured by one or more sensors of the client system, wherein the client system comprises a plurality of sensors, and wherein the one or more sensors signals are accessed from the one or more sensors based on one or more cascading model policies, wherein each cascading model policy utilizes one or more of a respective cost or relevance associated with each sensor;
• detect, based on one or more machine-learning models and the one or more sensor signals, a change in a context of the first user associated with an activity of the first user, wherein the change in the context of the first user satisfies a trigger condition associated with the activity;
• and
• automatically capture, responsive to the detected change in the context of the first user, visual data by one or more cameras of the client system,
• wherein each cascading model policy utilizes a respective cost associated with each sensor, and wherein each cascading model policy specifies accessing a first sensor signal from a first sensor associated with a first cost before accessing a second sensor signal from a second sensor associated with a second cost if the first cost is lower than the second cost.