Abstract: A graph data structure for an artificial intelligence knowledge base includes a plurality of user-centric facts associated with a user. Each user-centric fact has an application-agnostic data format and includes a subject graph node, an object graph node, and an edge connecting the subject graph node to the object graph node. The graph data structure is designed to accommodate facts from different application-specific data providers using the same application-agnostic data format even when the different application-specific data providers use different native data formats.

Abstract: This disclosure provides a system and method for providing intelligently-selected collections of user-centric content in a web browser. When implemented as a method, the method includes maintaining a user-centric graph with a plurality of user-centric facts derived from user interaction with different computer services. The method further includes recognizing different contexts of interest to the user. For each context, a collection of user-centric facts pertaining to the context are recognized in the user-centric graph, such recognition being based on a relationship between user-centric facts in the user-centric graph. The method further includes, for each context, displaying intelligently-selected content based on the collection of user-centric facts.

Abstract: A method for providing contextual information to a user during a browsing session includes maintaining a user-centric graph including a plurality of user-centric facts associated with the user and derived from interaction by the user with a plurality of different computer services. The method further includes recognizing a context of interaction with a browser application by a user. The method further includes identifying assistive information pertaining to the context, and displaying the assistive information to the user. The assistive information may be based at least on one or more user-centric facts in the user-centric graph.

Abstract: Techniques of remote computing resource access using sharable links are disclosed herein. One example technique includes receiving, at a security portal of a private network, an access request from a client device of a user for accessing a virtual machine (“VM”) on the private network via a public network. The technique can then include retrieving a copy of a configuration file corresponding to the virtual machine according to the VM identifier in the access request and accessing the virtual machine according to operating parameters in the retrieved copy of the configuration file to generate an execution result. The technique can further include transmitting, from the security portal, the execution result to the client device of the user via the public network, thereby shielding, with the security portal, the virtual machine on the private network from actions initiated via the public network.

Abstract: A method for providing contextual information to a user during a browsing session includes maintaining a user-centric graph including a plurality of user-centric facts associated with the user and derived from interaction by the user with a plurality of different computer services. The method further includes recognizing a context of interaction with a browser application by a user. The method further includes identifying assistive information pertaining to the context, and displaying the assistive information to the user. The assistive information may be based at least on one or more user-centric facts in the user-centric graph.

Abstract: This disclosure provides a system and method for providing intelligently-selected collections of user-centric content in a web browser. When implemented as a method, the method includes maintaining a user-centric graph with a plurality of user-centric facts derived from user interaction with different computer services. The method further includes recognizing different contexts of interest to the user. For each context, a collection of user-centric facts pertaining to the context are recognized in the user-centric graph, such recognition being based on a relationship between user-centric facts in the user-centric graph. The method further includes, for each context, displaying intelligently-selected content based on the collection of user-centric facts.

Abstract: This disclosure provides a system and method for providing intelligently-selected collections of user-centric content in a web browser. When implemented as a method, the method includes maintaining a user-centric graph with a plurality of user-centric facts derived from user interaction with different computer services. The method further includes recognizing different contexts of interest to the user. For each context, a collection of user-centric facts pertaining to the context are recognized in the user-centric graph, such recognition being based on a relationship between user-centric facts in the user-centric graph. The method further includes, for each context, displaying intelligently-selected content based on the collection of user-centric facts.

Abstract: A method for providing contextual information to a user during a browsing session includes maintaining a user-centric graph including a plurality of user-centric facts associated with the user and derived from interaction by the user with a plurality of different computer services. The method further includes recognizing a context of interaction with a browser application by a user. The method further includes identifying assistive information pertaining to the context, and displaying the assistive information to the user. The assistive information may be based at least on one or more user-centric facts in the user-centric graph.

Abstract: This disclosure provides a system and method for providing intelligently-selected collections of user-centric content in a web browser. When implemented as a method, the method includes maintaining a user-centric graph with a plurality of user-centric facts derived from user interaction with different computer services. The method further includes recognizing different contexts of interest to the user. For each context, a collection of user-centric facts pertaining to the context are recognized in the user-centric graph, such recognition being based on a relationship between user-centric facts in the user-centric graph. The method further includes, for each context, displaying intelligently-selected content based on the collection of user-centric facts.

Abstract: A method for providing contextual information to a user during a browsing session includes maintaining a user-centric graph including a plurality of user-centric facts associated with the user and derived from interaction by the user with a plurality of different computer services. The method further includes recognizing a context of interaction with a browser application by a user. The method further includes identifying assistive information pertaining to the context, and displaying the assistive information to the user. The assistive information may be based at least on one or more user-centric facts in the user-centric graph.

Abstract: A graph data structure for an artificial intelligence knowledge base includes a plurality of user-centric facts associated with a user. Each user-centric fact has an application-agnostic data format and includes a subject graph node, an object graph node, and an edge connecting the subject graph node to the object graph node. The graph data structure is designed to accommodate facts from different application-specific data providers using the same application-agnostic data format even when the different application-specific data providers use different native data formats.

Abstract: Personalized experiences based on leisure interest identification are provided to a user. An enriched entity and attribute graph is created based on leisure entities or attributes extracted from digital data signals. The user data signals may include browser history, queries in searches, social media signals, or click data. Global data is utilized to crawl the enriched entity and attribute graph to infer entities or attributes. Based on the inferred entities or attributes, leisure suggestions can be ranked and provided to the user via a user device. Completion suggestions may additionally be provided to the user via the user device that enable the user to complete an activity associated with one or more of the leisure suggestions.