Abstract: Improved intelligent personal assistant (IPA) software agents are disclosed that are configured to interact with various people, service providers, files, and/or smart devices. More particularly, this disclosure relates to an improved Natural Language Processing (NLP) Intent Determination Service (IDS) that is able to determine the likely best action to take in response to generic user commands and queries. The disclosed NLP IDS automatically selects valid (or potentially valid) API paths (e.g., sequence of API calls) to produce desired actions. Associated system actions and known API sequencing rules may then be used to process the incoming user command or query. A feedback loop is also disclosed to identify newly available APIs and success criteria for selected API paths. Discovery of API paths may be performed using predefined information, monitored information, programmatically determined interfaces, and programmatically tested interfaces.

Abstract: Improved intelligent personal assistant (IPA) software agents are disclosed that are configured to interact with various people, service providers, files, and/or smart devices. More particularly, this disclosure relates to an improved Natural Language Processing (NLP) Intent Determination Service (IDS) that is able to determine the likely best action to take in response to generic user commands and queries. The improved NLP IDS disclosed is said to be ‘search-based’ because, rather than attempt to parse incoming user commands and queries up front, the incoming user commands and queries are searched against a pre-generated database of exemplary user commands (e.g., having associated action or parsing identifiers) to determine the most relevant search result(s). The associated system actions and known grammar/parsing rules of the most relevant search result(s) may then be used to process the incoming user command or query—without having to actually parse the incoming user command or query from scratch.

Abstract: Disclosed are apparatuses, methods, and computer readable media for improved multi-datatype searching comprising receiving a search query of a first datatype, generating a vector of the first datatype describing the search query, expanding the vector of the first datatype to include a second datatype vector, wherein the second datatype vector is different from the first datatype but may be conceptually equivalent, and wherein the second datatype is associated with the vector of the first datatype, and performing a search based on the first datatype and a search on the second datatype.

Abstract: This disclosure relates generally to apparatus, methods, and computer readable media for composing communications for computing devices across multiple formats and multiple protocols. More particularly, but not by way of limitation, this disclosure relates to apparatus, methods, and computer readable media to permit computing devices, e.g., smartphones, tablets, laptops, and the like, to send communications in a number of pre-determined and/or ‘determined-on-the-fly’ optimal communications formats and/or protocols. Determinations of optimal delivery methods may be intelligently based on the sender individually or the relationship with the sender in the context of a group of recipients—including the format of the incoming communication, the preferred format of the recipient and/or sender, and an optimal format for a given communication message.

Abstract: This disclosure relates to systems, methods, and computer readable media for performing filtering of computer vision generated tags in a media file for the individual user in a multi-format, multi-protocol communication system. One or more media files may be received at a user client. The one or more media files may be automatically analyzed using computer vision models, and computer vision generated tags may be generated in response to analyzing the media file. The tags may then be filtered using Natural Language Processing (NLP) models, and information obtained during NLP tag filtering may be used to train and/or fine-tune one or more of the computer vision models and the NLP models.

Abstract: This disclosure relates to systems, methods, and computer readable media for performing multi-format, multi-protocol message threading in a way that is most beneficial for the individual user. Users desire a system that will provide for ease of message threading by “stitching” together related communications in a manner that is seamless from the user's perspective. Such stitching together of communications across multiple formats and protocols may occur, e.g., by: 1) direct user action in a centralized communications application (e.g., by a user clicking ‘Reply’ on a particular message); 2) using semantic matching (or other search-style message association techniques); 3) element-matching (e.g., matching on subject lines or senders/recipients/similar quoted text, etc.); and 4) “state-matching” (e.g., associating messages if they are specifically tagged as being related to another message, sender, etc. by a third-party service, e.g., a webmail provider or Instant Messaging (IM) service).

Abstract: An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or web sites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.

Abstract: This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information.

Abstract: Disclosed are systems, methods, and computer readable media for automatically assessing and allocating virtualized resources (such as CPU and GPU resources). In some embodiments, this method involves a computing infrastructure receiving a request to perform a workload, determining one or more workflows for performing the workload, selecting a virtualized resource, from a plurality of virtualized resources, wherein the virtualized resource is associated with a hardware configuration, and wherein selecting the virtualized resources is based on a suitability score determined based on benchmark scores of the one or more workflows on the hardware configuration, scheduling performance of at least part of the workload on the selected virtualized resource, and outputting results of the at least part of the workload.

Abstract: Improved intelligent personal assistant (IPA) software agents are disclosed that are configured to interact with various people, service providers, files, and/or smart devices. More particularly, this disclosure relates to an improved Natural Language Processing (NLP) Intent Determination Service (IDS) that is able to determine the likely best action to take in response to generic user commands and queries. The improved NLP IDS disclosed is said to be ‘search-based’ because, rather than attempt to parse incoming user commands and queries up front, the incoming user commands and queries are searched against a pre-generated database of exemplary user commands (e.g., having associated action or parsing identifiers) to determine the most relevant search result(s). The associated system actions and known grammar/parsing rules of the most relevant search result(s) may then be used to process the incoming user command or query—without having to actually parse the incoming user command or query from scratch.

Abstract: A system and method for transforming location-based data queries into temporal domain by leveraging a location-to-time knowledge conversion graph. In some systems which contain diverse sets of data objects, only certain objects may contain explicit location data, while others may not. Therefore, queriability of this diverse data by location properties would likely yield incomplete results. In some embodiments, this method allows for the transformation and augmentation of a given data query containing location-based filtering properties into a time-region-based lookup, wherein a given location has been assigned to a time region in the given data graph and all data events within that time region may be augmented with location metadata automatically in the knowledge graph. Over time, a system utilizing these embodiments can offer comprehensive location-based data services and insights to a given system or user wherein a diverse set of data objects exists and not all objects contain explicit location information.

Abstract: Techniques for resolving multiple user requests from multiple user accounts by an interactive interface are described. An interactive interface can obtain a first multi-dimensional context graph for a first user account and a second context graph for a second user account. Each graph comprises correlated contexts related to the user account. The interface can also receive a first user request associated with the first user account and a second user request associated with the second user account; determine, based on the first graph, a first current context and one or more first previous contexts for the first user request; determine, based on the second graph, a second current context and one or more second previous contexts for the second user request; determine one or more interrelationships between the first and the second graphs; and resolve the user requests based on the contexts and the interrelationships.

Abstract: This disclosure relates generally to apparatus, methods, and computer readable media for composing communications for computing devices across multiple formats and multiple protocols. More particularly, but not by way of limitation, this disclosure relates to apparatus, methods, and computer readable media to permit computing devices, e.g., smartphones, tablets, laptops, and the like, to send communications in a number of pre-determined and/or ‘determined-on-the-fly’ optimal communications formats and/or protocols. Determinations of optimal delivery methods may be intelligently based on the sender individually or the relationship with the sender in the context of a group of recipients—including the format of the incoming communication, the preferred format of the recipient and/or sender, and an optimal format for a given communication message.

Abstract: This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information.

Abstract: Disclosed are systems, methods, and computer readable media for automatically assessing and allocating virtualized resources (such as central processing unit (CPU) and graphics processing unit (GPU) resources). In some embodiments, this method involves a computing infrastructure receiving a request to perform a workload, determining one or more workflows for performing the workload, selecting a virtualized resource, from a plurality of virtualized resources, wherein the virtualized resource is associated with a hardware configuration, and wherein selecting the virtualized resources is based on a suitability score determined based on benchmark scores of the one or more workflows on the hardware configuration, scheduling performance of at least part of the workload on the selected virtualized resource, and outputting results of the at least part of the workload.

Abstract: This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called ‘zero-knowledge’ privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information.

Abstract: Disclosed are apparatuses, methods, and computer readable media for improved multi-datatype searching comprising receiving a search query of a first datatype, generating a vector of the first datatype describing the search query, expanding the vector of the first datatype to include a second datatype vector, wherein the second datatype vector is different from the first datatype but may be conceptually equivalent, and wherein the second datatype is associated with the vector of the first datatype, and performing a search based on the first datatype and a search on the second datatype.

Abstract: An improved decentralized, blockchain-driven network for artificial intelligence (AI)-enabled skills exchange between Intelligent Personal Assistants (IPAs) in a network is disclosed that is configured to perform computational tasks or services (also referred to herein as “skills”) in an optimally-efficient fashion. In some embodiments, this may comprise a first IPA paying an agreed cost to a second IPA to perform a particular skill in a more optimally-efficient fashion. In some embodiments, a skills registry is published, comprising benchmark analyses and costs for the skills offered by the various nodes on the skills exchange network. In other embodiments, a transaction ledger is maintained that provides a record of all transactions performed across the network in a tamper-proof and auditable fashion, e.g., via the use of blockchain technology. Over time, the AI-enabled nodes in the system may learn to scale, replicate, and transact with each other in an optimized—and fully autonomous—fashion.

Abstract: This disclosure relates to systems, methods, and computer readable media for performing multi-format, multi-protocol message threading in a way that is most beneficial for the individual user. Users desire a system that will provide for ease of message threading by “stitching” together related communications in a manner that is seamless from the user's perspective. Such stitching together of communications across multiple formats and protocols may occur, e.g., by: 1) direct user action in a centralized communications application (e.g., by a user clicking ‘Reply’ on a particular message); 2) using semantic matching (or other search-style message association techniques); 3) element-matching (e.g., matching on subject lines or senders/recipients/similar quoted text, etc.); and 4) “state-matching” (e.g., associating messages if they are specifically tagged as being related to another message, sender, etc. by a third-party service, e.g., a webmail provider or Instant Messaging (IM) service).

Abstract: An application program interface (API) analyzer that determines protocols and formats to interact with a service provider or smart device. The API analyzer identifies an API endpoint or websites for the service provider or smart device, determines a service category or device category, selects a category-specific corpus, forms a service-specific or device-specific corpus by appending information regarding the service provider or smart device to the category-specific corpus, and parses API documentation or the websites.