Abstract: Systems and methods for intelligent memory sharing and contextual retrieval across multiple devices and multiple applications are provided. The systems and methods do not just show a user what he or she has stored across his or her different devices but intelligently suggests relevant topics and/or information based on what is contained in a shared working memory compiled from the temporary memories on all of the user devices.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for providing contextualized SMS data from one or more SMS messages to a client are presented. SMS data from SMS messages may be filtered and relevant information from the filtered SMS data may be extracted. The extracted information from the SMS data may be categorized into one or more contextual categories in a tiered contextual content hierarchy. The categorization of the SMS data may include analyzing world knowledge related to the extracted information and associating searchable context metadata with the categorized information. An indication to provide feedback related to the SMS data may be received and feedback related to the received SMS data may then be provided to the client.

Abstract: Methods and systems are provided for automatically generating a dynamic taskline. Initially, sources are accessed to retrieve contextual information associated with a user. From this contextual information, a user task is detected that comprises subtasks. Subtasks are identified, where the subtasks are associated with the user task. The subtasks are ranked based, in part, on the contextual information associated with the user. A taskline is automatically generated based on the ranking of the subtasks. The taskline is dynamically modified based on a particular point in time or updated contextual information associated with the user, to constantly provide the user with relevant and useful information.

Abstract: Systems and methods for intelligent memory sharing and contextual retrieval across multiple devices and multiple applications are provided. The systems and methods do not just show a user what he or she has stored across his or her different devices but intelligently suggests relevant topics and/or information based on what is contained in a shared working memory compiled from the temporary memories on all of the user devices.

Abstract: Systems and methods for intelligent memory sharing and contextual retrieval across multiple devices and multiple applications are provided. The systems and methods do not just show a user what he or she has stored across his or her different devices but intelligently suggests relevant topics and/or information based on what is contained in a shared working memory compiled from the temporary memories on all of the user devices.

Abstract: Systems and methods for intelligent memory sharing and contextual retrieval across multiple devices and multiple applications are provided. The systems and methods do not just show a user what he or she has stored across his or her different devices but intelligently suggests relevant topics and/or information based on what is contained in a shared working memory compiled from the temporary memories on all of the user devices.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for providing contextualized SMS data from one or more SMS messages to a client are presented. SMS data from SMS messages may be filtered and relevant information from the filtered SMS data may be extracted. The extracted information from the SMS data may be categorized into one or more contextual categories in a tiered contextual content hierarchy. The categorization of the SMS data may include analyzing world knowledge related to the extracted information and associating searchable context metadata with the categorized information. An indication to provide feedback related to the SMS data may be received and feedback related to the received SMS data may then be provided to the client.

Abstract: Methods and systems are provided for automatically generating a dynamic taskline. Initially, sources are accessed to retrieve contextual information associated with a user. From this contextual information, a user task is detected that comprises subtasks. Subtasks are identified, where the subtasks are associated with the user task. The subtasks are ranked based, in part, on the contextual information associated with the user. A taskline is automatically generated based on the ranking of the subtasks. The taskline is dynamically modified based on a particular point in time or updated contextual information associated with the user, to constantly provide the user with relevant and useful information.

Abstract: The subject disclosure is directed towards making cube data highly available and efficient to access by separating the read cube server from the processing cube server, on different physical machines. The read cube server may be mirrored, and the write cube server may be mirrored. When the primary read cube server is not operational (e.g., has failed) or is having its read cube synchronized, the read queries are handled by the mirror read cube server. When a processing cube server (or its write cube) is not operational, its mirror processing cube server takes over and performs cube processing operations via its mirror write cube.

Abstract: The subject disclosure is directed towards making cube data highly available and efficient to access by separating the read cube server from the processing cube server, on different physical machines. The read cube server may be mirrored, and the write cube server may be mirrored. When the primary read cube server is not operational (e.g., has failed) or is having its read cube synchronized, the read queries are handled by the mirror read cube server. When a processing cube server (or its write cube) is not operational, its mirror processing cube server takes over and performs cube processing operations via its mirror write cube.

Abstract: The subject disclosure is directed towards making cube data highly available and efficient to access by separating the read cube server from the processing cube server, on different physical machines. The read cube server may be mirrored, and the write cube server may be mirrored. When the primary read cube server is not operational (e.g., has failed) or is having its read cube synchronized, the read queries are handled by the mirror read cube server. When a processing cube server (or its write cube) is not operational, its mirror processing cube server takes over and performs cube processing operations via its mirror write cube.