Multi-modal device capable of automated actions

A method that facilitates automation of an action based upon a plurality of factors, comprising:

• storing, in a memory communicatively coupled to a processor, computer-executable instructions for performing the method of facilitating automation of the action based upon the plurality of factors;
• executing the instructions on the processor;
• according to the instructions being executed:
• obtaining the plurality of factors pertaining to user communication with another user through employment of a communication device, the plurality of factors include an environmental factor, a location factor, and a user state;
• analyzing each of the obtained plurality of factors to infer an action that a user desires to be performed based at least in part upon historical analysis;
• translating detected language into a language comprehendible to a user of output, wherein either the detected language or the comprehendible language is determined by operation of a GPS system to obtain a present location and language associated with the present location;
• automatically scheduling an appointment, wherein scheduling the appointment is based on the analysis of each of the plurality of factors to infer a user intent and to automatically implement the action based at least in part upon a rules-based logic component, wherein the rules based logic component automatically allows execution of the action based upon satisfaction of a defined rule, and based at least in part upon operation of an implementation component configured to identify an individual, the implementation component using an algorithm together with a desired degree of certainty, and based at least in part upon operation of an artificial intelligence component that comprises a classifier function that maps an input attribute vector to a confidence that input associated with the vector belongs to a class, and wherein the class to which an input belongs infers the action that the user desires to be automatically performed;
• prompting a user with suggestions prior to commencement of the automatically scheduled appointment, wherein the suggestions are based on prediction of weather at a time of the automatically scheduled appointment;
• and
• adjusting a time of the automatically scheduled appointment in response to the prediction of the local weather.

A system for altering personal data for a user based upon a user interaction with a mobile communication device, comprising:

• a detection component that employs a plurality of integrated sensors to passively monitor a user to obtain contextual information that relates to the user, at least a portion of the obtained contextual information is derived from user interaction with another user, wherein the detection component is configured for adjusting a time of a scheduled appointment in response to the prediction of the local weather;
• an inquiry component for prompting a user with suggestions prior to commencement of the scheduled appointment, wherein the suggestions are based on prediction of local weather at a time of the scheduled appointment;
• a multi-language component for translating detected voice data into a language comprehendible to a user, wherein the comprehendible language is identified at least in part by operation of a GPS system to obtain a present location and language and a dialect associated with the present location;
• an artificial intelligence component that utilizes a classifier to infer an intention of the user based upon the obtained information, the inference of the intention is made through use of artificial intelligence techniques, wherein the artificial intelligence component uses rules-based logic to automatically prompt execution of the action based at least in part upon satisfaction of a defined rule, and based at least in part upon an implementation component configured to identify an individual, the implementation component using an algorithm together with a desired degree of certainty, and based at least in part upon an artificial intelligence component that comprises a classifier function that maps an input attribute vector to a confidence that input associated with the vector belongs to a class, and wherein the class to which an input belongs infers the action that the user desires to be automatically performed;
• and
• an implementation component that performs an action as a function of the inferred intention.