Abstract: The method receives a first request to establish a trusted relationship with a second client account of the SaaS platform. The trusted relationship enables sharing, with the second client account, of a client asset associated with the first client account. The method determines whether the first request satisfies one or more conditions related to the trusted relationship. The method stores an indication of the trusted relationship between the first client account and the second client account in a data store. The method receives a second request to perform a communication operation based on the client asset associated with the first client account. The method performs the communication operation on behalf of the second client account using the client asset associated with the first client account and based on the indication of the trusted relationship between the first client account and the second client account.

Abstract: An Artificial Intelligence (AI)-based data processing system processes current data to determine if the quality of the current data is adequate to be provided to data consumers and if the quality is adequate, the current data is further analyzed to determine if an impacted load including changes to dimension data of the current data or an incremental load including changes to fact data of the current data is to be provided to the data consumers. Depending on the amount of data to be provided to the data consumers, processing units (PUs) may be determined and assigned to carry out the data upload. Various machine learning (ML) models that are used to provide predictions from the current data are analyzed to determine the quality of predictions and if needed, can be automatically retrained by the data processing system.

Abstract: In an embodiment, a method includes matching terms of a received query to a database of provider capabilities. The method further includes determining, for each portion of the received query, a respective provider to execute the portion of the received query. The method further includes sending each portion of the received query to its respective provider. The method further includes combining results from each respective provider to a returned query result.

Abstract: Algorithm for tolerance analysis, allocation, and synthesis, also known as tolerance budgeting, is discussed. Also discussed is a metric to rank compensators for a system. It is based on the system Jacobian and the inner product of the output vector error as the tolerancing criterion. These tolerances are calculated by fitting an appropriate, axis aligned multidimensional Orthotope within an ellipsoid like region that is not necessarily axis aligned.

Abstract: In an embodiment, a method includes matching terms of a received query to a database of provider capabilities. The method further includes determining, for each portion of the received query, a respective provider to execute the portion of the received query. The method further includes sending each portion of the received query to its respective provider. The method further includes combining results from each respective provider to a returned query result.

Abstract: An artificial intelligence based system and method for predicting and preventing illicit behavior is disclosed. The system and method may include obtaining search strings used by multiple users, as well as the clickstream data of such users. The search terms included in the search strings may be preprocessed and analyzed for inclusion of suspicious words, e.g., words related to illicit behavior, provided in a corpus of suspicious words. Information associated with the search strings containing suspicious words may be analyzed to identify users associated with the same search strings. The clickstream of the identified users may be analyzed to determine whether the users are likely to engage in illicit behavior. Preventive measures may be taken to prevent such users from engaging in such illicit behavior.

Abstract: A system for providing real-time optimized product designs may obtain historical data and real-time data related to a product to identify real-time customer preferences and sentiments associated with the product. The system may provide a plurality of real-time potential attribute recommendations comprising attributes likely to be preferred by customers. The system may provide a set of preferred attribute recommendations based on the plurality of real-time potential attribute recommendations ranked highest in an attribute ranking order. The system may provide a cannibalization factor and a similarity index for each of the set of preferred attribute recommendations. The system may provide a real-time demand forecast of the product and may also provide a predicted cannibalization volume and a predicted incremental volume for the product in real-time. The system may determine a set of final attribute recommendations for the product to provide an optimized design for the product in real-time.

Abstract: An instrument (10) to prepare and safely place an intra-uterine device (30) in uterus (50) of a woman, comprising a dynamic stopper (20), a string management arrangement (110) whereby a string (31) of an IUD (30) is in one of a locked condition or an unlocked condition, an operating device (100), further comprising a base (70), a cover (90) a carriage (140), wherein the dynamic stopper (20) slidably resides in the base (70) and can slide by the sliding length (23), wherein the string (31) exits from an outpoint (87) and re-enters from an inpoint (88), the outpoint (87) is at a trim length (46) and the inpoint (88) is at a conservative length (47). The string (31) can be trimmed as per sounding measurement of uterus (50) of woman, before inserting the instrument (10) in uterus (50) and string (31) entanglement possibilities are eliminated, irrespective of type of IUD (30, 30A, 30B).

Abstract: Systems and methods for automated message delivery feedback that includes receiving a set of messaging requests to transmit a message to at least one recipient device; making a set of messaging attempts, each of the set of messaging attempts including an attempt to deliver the message to the at least one recipient device; receiving delivery feedback and automatically associating the delivery feedback to one messaging attempt of the set of messaging attempts; and updating a delivery status of the at least one messaging attempt.

Abstract: In a computer-implemented method for generating a privacy compliant audit log for a conversational interface, a request for information from a user is received at a conversational interface. A response to the request for information is generated, the response including data responsive to the request for information. It is determined whether the response comprises private user data. An audit log including the request and information related to the response is generated, where the information related to the response does not include the private user data.

Abstract: In a computer-implemented method for name type identification, a list of names is received. A probability that each name of the list of names is one of a given name and a surname is determined. Each name of the list of names is determined as one of a given name and a surname based on the probability. Entities of the list of names are determined based on the identifying each name of the list of names as one of a given name and a surname, wherein an entity includes one of a given name, a surname, and a given name/surname combination.

Abstract: A computing device includes a storage machine holding instructions executable by a logic machine to generate multi-string clusters, each containing alphanumeric strings of a dataset. Further multi-string clusters are generated via iterative performance of a combination operation in which a hierarchically-superior cluster is generated from a set of multi-string clusters. The combination operation includes, for candidate pairs of multi-string clusters, generating syntactic profiles describing an alphanumeric string from each multi-string cluster of the candidate pair. For each of the candidate pairs, a cost factor is determined for at least one of its syntactic profiles. Based on the cost factors determined for the syntactic profiles, one of the candidate pairs is selected. The multi-string clusters from the selected candidate pair are combined to generate the hierarchically-superior cluster including all of the alphanumeric strings from the selected candidate pair of multi-string clusters.

Abstract: Systems and methods for entity recommendation can make use of rich data by allowing the items to be recommended and the recipients of the recommendation (e.g., users) to be modeled as “complex entities” composed of one or more static sub-entities and/or a dynamic component, and by utilizing information about multiple relationships between the sub-entities as reflected in bipartite graphs. Generating recommendations from such information may involve creating vector representations of the sub-entities based on the bipartite graphs (e.g., using graph-based convolutional networks), and combining these vector representations into representations of the items and users (or other recipients) to be fed into a classifier model.

Abstract: Systems, methods, and computer-executable instructions for guiding program synthesis includes receiving a specification that includes an input and output example. Programs are synthesized that meet the specification. During synthesizing each of the programs includes branching decisions. Each branching decision includes a plurality of paths. Synthesizing the programs comprises includes selecting a first score model, for a first branching decision. Each of the programs is scored using the first score model. The paths of the first branching decision are pared based on the score. One the paths is selected. A synthesized program that meets the specification is returned. The synthesized program includes the one of the paths.

Abstract: Methods and systems for aligning amplification gains in a plurality of interconnected devices are disclosed. The method includes receiving by each device limiter gain attenuations and brownout gain attenuations broadcasted by the plurality of devices and selecting the maximum brownout gain attenuation and the maximum limiter gain attenuation. The method includes determining a total attenuation as a sum of the maximum brownout attenuation gain and the maximum limiter attenuation gain. The method includes receiving a frame synchronization signal and adjusting the amplification gain by applying the total attenuation responsive to the frame synchronization signal.

Abstract: Systems and methods for entity recommendation can make use of rich data by allowing the items to be recommended and the recipients of the recommendation (e.g., users) to be modeled as “complex entities” composed of one or more static sub-entities and/or a dynamic component, and by utilizing information about multiple relationships between the sub-entities as reflected in bipartite graphs. Generating recommendations from such information may involve creating vector representations of the sub-entities based on the bipartite graphs (e.g., using graph-based convolutional networks), and combining these vector representations into representations of the items and users (or other recipients) to be fed into a classifier model.

Abstract: Systems and methods for entity recommendation can make use of rich data by allowing the items to be recommended and the recipients of the recommendation (e.g., users) to be modeled as “complex entities” composed of one or more static sub-entities and/or a dynamic component, and by utilizing information about multiple relationships between the sub-entities as reflected in bipartite graphs. Generating recommendations from such information may involve creating vector representations of the sub-entities based on the bipartite graphs (e.g., using graph-based convolutional networks), and combining these vector representations into representations of the items and users (or other recipients) to be fed into a classifier model.

Abstract: An artificial intelligence based system and method for predicting and preventing illicit behavior is disclosed. The system and method may include obtaining search strings used by multiple users, as well as the clickstream data of such users. The search terms included in the search strings may be preprocessed and analyzed for inclusion of suspicious words, e.g., words related to illicit behavior, provided in a corpus of suspicious words. Information associated with the search strings containing suspicious words may be analyzed to identify users associated with the same search strings. The clickstream of the identified users may be analyzed to determine whether the users are likely to engage in illicit behavior. Preventive measures may be taken to prevent such users from engaging in such illicit behavior.

Abstract: In an embodiment, a method includes determining, based on a received query and contextual information, candidate reasoners to respond to a received query to select a candidate reasoner. A reasoner or candidate reasoner is a module that translates information from a sensor, user settings, or other source, into additional or revised fields for a query. The method further includes generating, at each candidate reasoner determined, additional or revised query fields based on the contextual information and a rule of a rule database. The method further includes merging the additional query fields for each candidate reasoner based on a confidence score or other metric of each corresponding candidate reasoner. The confidence score can be based on applicability of the contextual information to the received query. The method further includes providing an enhanced query having the additional or revised query fields.

Abstract: Systems, methods, and computer-executable instructions for secure data analysis using encrypted data. An encryption key and a decryption key are created. The security of encryption using the encryption key and the decryption key are based upon factoring. A computation key is created based upon the encryption key. Data is encrypted using the encryption key. The encrypted data and the computation key are provided to a remote system. The remote system is requested to perform data analysis on the encrypted data. An encrypted result of the data analysis is received from the remote system. The encrypted result of the data analysis is decrypted with the decryption key.