Microsoft Technology Licensing, LLC

Other

Amazon Technologies, Inc.

Christopher Lee Mullins

Robert Standefer, Iii

John Anthony Taylor

Jonathan Edgar Fay

Steven Wayne Ickman

Thomas Matthew Laird-McConnell

Henrik Frystyk Nielsen

Joshua Allen Cowhig

Scott Jeff Gellock

James Henry Lewallen, Jr

Lili Cheng

Gabriel Gilabert

John Peter Shewchuk

Christopher Clayton McConnell

Miguel Castro

Miguel Oom Temudo De Castro

David Shigeru Taniguchi

Anuj Prateek

Christopher Michael Whitten

Congyong Su

Carlos Castro

Weston Connor Panther

Thomas Matthew Laird-Mcconnell

Robert Iii Standefer

Robert Standefer

Examples of the present disclosure describe systems and methods of delegating authorization to access isolated collections of data. In aspects, a request to access an isolated collection of resource identifiers and relationships may be received by an application. The resource identifiers may correspond to resources in one or more remote data repositories. Upon receiving the request, the application may interrogate a remote data repository to determine whether the requestor is currently authorized to access the one or more resources corresponding to the resource identifiers in the isolated collection. If the requestor is determined to be authorized, the application may use an authorization indication provided by the remote data repository to provide the requestor with access to the isolated collection. If the requestor is determined to be unauthorized, the application may prohibit access to the isolated collection.

Delegated authorization for isolated collections

Described herein are systems and methods for providing interactive notification panels to a user. A bot apparatus receives a notification from an application program and transforms the notification into one or more interactive notification panels configured to receive user inputs and/or to provide an output to at least one user input. Based on at least one user input, the bot apparatus transmits data to the application program, which causes the application program to perform one or more actions.

Interactive notification panes in a computing system

In non-limiting examples of the present disclosure, systems, methods and devices for enabling conversational bot communications are presented. A marketplace comprising an identity of a plurality of skills may be maintained, each of the plurality of skills associated with a manifest and a conversational bot. A request for execution of a specific skill may be received. A plurality of conversational bots may be identified, each of the plurality of conversational bots being associated with a manifest for executing the specific skill. The plurality of conversational bots may be ranked. The specific skill may be caused to be executed by the highest ranked conversational bot. In some examples, a plurality of highest ranked conversational bots may be surfaced and a bot that is selected may execute the specific skill.

Marketplace for conversational bot skills

A computing system for real-time analyzing meeting conversations using artificial intelligence (AI) is configured to establish a meeting communication channel that facilitates a meeting among multiple client systems. Each of the multiple client systems corresponds to a meeting participant. In response to receiving communication from the multiple client systems, the computing system analyzes currently received communication via an AI engine while the meeting remains active. The currently received communication is communication received within a rolling time window ending at a current time. Based on the analysis, the computing system identifies an agenda item that has a highest correlation with the currently received communication and a sentiment of at least one participant. The computing system then determines a level of interest of the agenda item based on the sentiment of the participant and causes at least one client system to display a notification or an alert or make suggestions.

Conversational AI for intelligent meeting service

The present disclosure relates to processing operations configured to generate and present a chat bot diagnostic visualization that provides real-time visual insights into operation of a chat bot for debugging assistance. A chat bot diagnostic tool is programmed to launch a graphical user interface that displays a visual representation of diagnostic data for debugging a chat bot in real-time. To enable conversational specific data to be reviewed, the present disclosure is configured to implement a middleware adapter within in a run-time stack of a chat bot that is configured to trace data traffic between a chat bot and a channel of an application/service. This enables the chat bot diagnostic tool to observe data traffic and filter the data traffic to identify relevant data for debugging a chat bot. A debugging data visualization of a chat bot interaction is emulated through a graphical user interface of the chat bot diagnostic tool.

Chat bot diagnostic visualization

Aspects of the present disclosure relate to systems and methods for providing strong resource identification. When a resource is created, saved, or re-based, a cryptographic key pair may be generated and associated with the resource. A public key of the cryptographic key pair may be used as a unique identifier. Information about the resource, such as the name of the resource and its actual location may be stored in an index based upon the resource's public key. Sharing the resource with other devices may comprise sending the resource's key, as opposed to information about the resource's actual location, to one or more recipient device.

Strong resource identity in a cloud hosted system

Examples of the present disclosure describe systems and methods relating to context rules in a graph or isolated collection. In an example, information in an isolated collection may be associated with one or more contexts. The information may be represented within the isolated collection based on one or more rules, and one or more of the rules may be associated with one or more contexts to which the information relates, thereby indicating a context association. A context association may indicate a positive, negative, or other relationship between one or more rules and one or more contexts. Based on the context association, information within the isolated collection may be adapted to generate different views of the isolated collection for different contexts. As such, relevant, useful, or actionable information may be included or emphasized, while information that is not as relevant, useful, or actionable may be omitted or deemphasized.

Context rules for a graph

The present disclosure relates to systems and methods of overlaying a plurality of isolated collections to generate an overlaid isolated collection. In an example, a first and second isolated collection having at least one common resource may be overlaid. A first and second inference ruleset may be extracted from the first and second isolated collection, respectively. Based on the first and second inference ruleset, one or more suggestions may be generated relating to conflicting inference rules. A suggestion may comprise selecting a subset of the conflicting inference rules (e.g., none, some, or all of the rules) for inclusion in the overlay isolated collection. Another suggestion may comprise generating a new inference rule based on the conflicting inference rules. An indication relating to the suggestions may be received. The indication may be used to generate a third isolated collection and a third inference ruleset.

Contextual analysis of isolated collections based on differential ontologies

A method for utilizing shared memory spaces for data lifecycle management in a conversational AI system includes receiving one or more storage requests directing conversational data to multiple nodes of a conversational data object and storing the conversational data that is directed to each different one of the multiple nodes within a different one of multiple discrete memory spaces. Each of the multiple discrete memory spaces is governed by a scope policy defining a lifetime for data stored within the memory space. The method further provides for erasing data of each node of the multiple different nodes of the conversational data object according to the lifetime defined by the scope policy governing the memory space storing the node.

Shared memory space management for conversational artificial intelligence system

A computing system for real-time analyzing meeting conversations using artificial intelligence (AI) is configured to establish a meeting communication channel that facilitates a meeting among multiple client systems. Each of the multiple client systems corresponds to a meeting participant. In response to receiving communication from the multiple client systems, the computing system analyzes currently received communication via an AI engine while the meeting remains active. The currently received communication is communication received within a rolling time window ending at a current time. Based on the analysis, the computing system identifies an agenda item that has a highest correlation with the currently received communication or a task that is assigned to at least one of the participants, and causes, in substantially real time, at least one of the plurality of the client systems to display the agenda item or add the task to a task list.

In non-limiting examples of the present disclosure, systems, methods and devices for enabling conversational bot communications are presented. A natural language input may be received by a first conversational bot. A skill needed to fulfill a request in the natural language input may be identified. A determination may be made that the skill is not executable by the first conversational bot. A determination may be made that the skill is executable by a second conversational bot. A request for execution of the skill may be sent from the first conversational bot to the second conversational bot. A request for information needed for the second conversational bot to execute the skill may be received by the first conversational bot from the second conversational bot. The information may be sent from the first conversational bot to the second conversational bot. The skill may be executed.

Conversational manifests for enabling complex bot communications

Representative embodiments disclose mechanisms to create analytic metrics for bots. In one set of embodiments, the system creates a custom URI that encodes bot specific information in a URI format. An analytic record is created based on the URI and the analytic record can be logged and/or sent directly to an analytic platform designed to provide analytic metrics for websites. In this fashion, website analytic platforms can be used to provide analytic metrics for bots. In another set of embodiments, analytic records are created that are logged and/or sent directly to a bot specific analytic platform. Such a platform may help derive bot specific analytic metrics.

Network mapping and analytics for bots

Examples of the present disclosure describe systems and methods of managing user tasks using isolated collections of data. In aspects, input may be received by a task management application/service. The task management application/service may analyze the input to determine isolated collection of resources identifying tasks associated with one or more user accounts. The task management application/service may aggregate and analyze the tasks to determine associations between the tasks, to classify tasks and/or to prioritize tasks. The task management application/service may use the analyzed data to provide notifications, prompt user action and/or provide query results. In aspects, the task management application/service may also provide an interface comprising a single master view of tasks aggregated from disparate data stores and/or user accounts associated with a user.

Master view of tasks

A system and method of automating data profile updating and querying includes building bots using standard schema having predefined data types for collecting data relating to a user or object. A bot stores the collected data in a data profile for the user or object in a graph data store that is queried by that bot or another bot to extract data relating to the user or object. The data relating to the user or object may be collected from two or more data channels including, for example, a channel of spoken data and a channel of typed data. The collected data is selectively processed by a bot to establish context for the collected data and is inserted into a knowledge graph that may be joined to another knowledge graph for querying. The bots automate the collection and sharing of collected profile data with other bots in an application ecosystem.

Growing community of inventors

Sammamish, WA, United States of America

Christopher Lee Mullins