Patents Examined by William D Titcomb
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Patent number: 11551150Abstract: Implementations relate to training a model that can be used to process values for defined features, where the values are specific to a user account, to generate a predicted user measure that reflects both popularity and quality of the user account. The model is trained based on losses that are each generated as a function of both a corresponding generated popularity measure and a corresponding generated quality measure of a corresponding training instance. Accordingly, the model can be trained to generate, based on values for a given user account, a single measure that reflects both quality and popularity of the given user account. Implementations are additionally or alternatively directed to utilizing such predicted user measures to restrict provisioning of content items that are from user accounts having respective predicted user measures that fail to satisfy a threshold.Type: GrantFiled: July 6, 2020Date of Patent: January 10, 2023Assignee: GOOGLE LLCInventors: Spurthi Amba Hombaiah, Vladimir Ofitserov, Mike Bendersky, Marc Alexander Najork
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Patent number: 11550602Abstract: Integration code usable to cause a computing device to determine which category from a plurality of categories corresponds to an interface of an interface provider is generated based at least in part on output from a machine learning algorithm trained to categorize interfaces. The computing device is caused, by providing the integration code to the computing device, to execute the integration code to cause the computing device to evaluate characteristics of an interface of an interface provider, determine a category of an interface of the interface provider, and interact with the interface in a manner that accords with the category.Type: GrantFiled: November 23, 2020Date of Patent: January 10, 2023Assignee: Klarna Bank ABInventors: Vladimir Curie, James W. Barrett, Andrey Melentyev, Melody Ju
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Patent number: 11550453Abstract: A method for rendering context based information on a user interface includes receiving a user request to extract the context based information from a database. The database includes a 5 plurality of documents and the request includes at least one search criteria required to determine a context of the user request. The method includes generating a list of documents corresponding to the context of the user request and rendering on a viewing portion of the user interface the list of documents corresponding to the context of the user request.Type: GrantFiled: August 12, 2022Date of Patent: January 10, 2023Assignee: AlphaSense OyInventors: Rajmohan Neervannan, Jaakko Kokko, Mathias Creutz
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Patent number: 11531822Abstract: A model training service of a provider network may receive content items as training data. For example, the content items may be documents with certain portions labeled as stale. The model training service may train one or more different types of models using those content items (e.g., natural language inference model, paraphrasing detection model, named entity recognition model). The model training service may then provide the model(s) to a content staleness check (CSC) service. The CSC service may receive, from a client, a request that indicates one or more content items to be checked for staleness. The CSC service may process the content items by the model(s) to generate one or more indications of staleness of the content item. The CSC service may generate a response based on the indications of staleness. For example, the CSC service may generate a document with certain portions highlighted as stale content.Type: GrantFiled: June 30, 2020Date of Patent: December 20, 2022Assignee: Amazon Technologies, Inc.Inventors: Mingwen Dong, Sheng-Min Shih, Tapodipta Ghosh, Mihir Anil Joshi, Stuart Myles, Kun Cao
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Patent number: 11531909Abstract: The purpose of the present invention is to train a learning model and thereby create a utility model, and assist with an operation for making practical use thereof. Provided is a computer system 50 for preparing learning models in one or more learning units 102; receiving an input of learning data from a data source 111, and training said one or more learning models using the learning data. One or more utility models are finalized on the basis of said one or more trained learning models, and said one or more utility models are deployed to one or more inference units 114. Each of said one or more inference units 114: receives an input of utility data from the data source 111; provides the utility data to the utility models and executes an inference; and transmits, to a data target 113, inference result data outputted from the utility models.Type: GrantFiled: February 5, 2018Date of Patent: December 20, 2022Assignee: Abeja, Inc.Inventors: Yousuke Okada, Takanori Ogata, Toshiya Kawasaki, Takuma Teramoto
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Patent number: 11526678Abstract: A training system includes: a first training dataset including first entries, wherein each of the first entries includes: a first sentence; a second sentence; and an indicator of a relationship between the first and second sentences; a training module configured to: generate a second dataset including second entries based on the first entries, respectively, wherein each of the second entries includes: the first sentence of one of the first entries; the second sentence of the one of the first entries; a first surface realization corresponding to first facts regarding the first sentence; the indicator of the one of the first entries; and train a model using the second dataset and store the model in memory.Type: GrantFiled: May 14, 2020Date of Patent: December 13, 2022Assignee: NAVER CORPORATIONInventor: Julien Perez
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Patent number: 11526780Abstract: A method of extending a conversational computing interface. The method comprises executing a nonnative skill implemented in a nonnative programming language of the conversational computing interface. The method further comprises automatically computer-tracing computer operations performed by the nonnative skill during such execution. The method further comprises automatically computer-generating a native computer-executable plan representing the traced computer operations in a native programming language of the conversational computing interface.Type: GrantFiled: October 4, 2019Date of Patent: December 13, 2022Assignee: Microsoft Technology Licensing, LLCInventor: David Leo Wright Hall
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Patent number: 11521282Abstract: Systems and methods of the present invention provide for generating and displaying a progress monitoring assistant to show the growth scale value score comparing two or more assessments and providing a preliminary interpretation of the comparison.Type: GrantFiled: August 5, 2021Date of Patent: December 6, 2022Assignee: PEARSON EDUCATION, INC.Inventors: Kristina Breaux, Thomas Witholt
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Patent number: 11521124Abstract: For each generative model of a set of K generative models that classifies sensor data into K classes, in-distribution samples are sampled from training data as being classified as belonging to the class of the generative model and out-of-distribution samples are sampled from the training data as being classified as not belonging to the class of the generative model. Out-of-distribution samples are also generated from each remaining reciprocal generative model in the set of reciprocating generative models excluding the generative model to provide additional samples classified as not belonging to the class of the generative model. Parameters of the generative model are updated to minimize a loss function to maximize likelihood of the samples belonging to the class, and to maximize the loss function on both the sampled out-of-distribution samples and the generated out-of-distribution samples to minimize likelihood of the samples not belonging to the class.Type: GrantFiled: December 13, 2019Date of Patent: December 6, 2022Assignee: Robert Bosch GmbHInventors: Filipe J. Cabrita Condessa, Jeremy Z. Kolter
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Patent number: 11514265Abstract: The disclosed embodiments provide a system for performing inference. During operation, the system obtains a graph containing nodes representing members of an online system, edges between pairs of nodes, and edge scores representing confidences in a type of relationship between the pairs of nodes. Next, the system performs a set of iterations that propagate a label for the type of relationship from a first subset of edges to remaining edges in the graph, with each iteration updating a probability of the label for an edge between a pair of nodes based on a subset of edge scores for a second subset of edges connected to one or both nodes in the pair and probabilities of the label for the second subset of edges. The system then performs one or more tasks in the online system based on the probability of the label for the edge.Type: GrantFiled: September 26, 2019Date of Patent: November 29, 2022Assignee: Microsoft Technology Licensing, LLCInventors: Parag Agrawal, Yan Wang, Aastha Jain, Hema Raghavan
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Patent number: 11507802Abstract: The present disclosure relates to a system, and method for computer-based recursive learning of artificial intelligence (AI) apprentice agents. The system includes a system circuitry in communication with a database and a memory. The system circuitry is configured to receive a new data-structure comprising one or more inputs and a goal, and convert, using a perception agent, the one or more inputs of the new data-structure into one or more input feature parameters of the new data-structure. The system circuitry is configured to obtain, using a reasoning agent, an action for the new data-structure, and determine, using an evaluation agent, whether the action for the new data-structure generates the goal of the new data-structure. When it is determined that the action generates the goal of the new data-structure, the system circuitry is further configured to store the new data-structure in the database.Type: GrantFiled: August 30, 2019Date of Patent: November 22, 2022Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Kumar Abhinav, Alpana Dubey, Sakshi Jain, Veenu Arora, Hindnavis Vijaya Sharvani
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Patent number: 11508191Abstract: A vehicle interface device for diagnosing, scanning and programming an electrical system of a vehicle having a housing and being connectable to an electrical system of a vehicle, a local diagnostic computer, and a remote diagnostic computer. The vehicle interface device is selectively switchable for operation in either a local mode or a remote mode. In the local mode, the vehicle interface device is connected with the local diagnostic computer and operates as a pass-thru device. In the remote mode, the vehicle interface device is connected with the remote diagnostic computer.Type: GrantFiled: December 3, 2019Date of Patent: November 22, 2022Assignee: Opus IVS, Inc.Inventors: Brian J. Herron, Andrew D. Betteley, Mark W. Wine
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Patent number: 11501264Abstract: Meeting and conferencing systems and methods are implemented in a variety of manners. Consistent with an embodiment of the present disclosure, a meeting system is implemented via a computer server which is configured to provide a web-based meeting-group subscription option to potential meeting participants. A meeting scheduling data is received over a web-accessible virtual meeting interface. The meeting scheduling data includes group identification information and meeting time information. In response to the group identification information, participant identification information is retrieved for participants that become associated with a meeting group identified by the group identification information. Chat sessions may be used by the meeting participants.Type: GrantFiled: February 26, 2021Date of Patent: November 15, 2022Assignee: 8x8, Inc.Inventor: Ramprakash Narayanaswamy
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Patent number: 11501216Abstract: A computer system has a first machine learning module configured to predict a probability of a respective option being selected by a particular user if presented to that user via a computer app. A second machine learning module is configured to determine a respective confidence value associated with the probability. A third module uses the predicted probabilities and confidence values to determine at least one option to be presented to the particular user.Type: GrantFiled: February 21, 2020Date of Patent: November 15, 2022Assignee: KING.COM LTD.Inventors: Lele Cao, Sahar Asadi
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Patent number: 11494703Abstract: Systems and methods to utilize a machine learning model registry are described. The system deploys a first version of a machine learning model and a first version of an access module to server machines. Each of the server machines utilizes the model and the access module to provide a prediction service. The system retrains the machine learning model to generate a second version. The system performs an acceptance test of the second version of the machine learning model to identify it as deployable. The system promotes the second version of the machine learning model by identifying the first version of the access module as being interoperable with the second version of the machine learning model and by automatically deploying the first version of the access module and the second version of the machine learning model to the plurality of server machines to provide the prediction service.Type: GrantFiled: March 31, 2020Date of Patent: November 8, 2022Assignee: Opendoor Labs Inc.Inventor: Chongyuan Xiang
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Patent number: 11487409Abstract: [Problem] To propose an application corresponding to a situation of each user and improve user convenience in starting use of the application. [Solution] Provided is an information processing apparatus including: a display control unit configured to display, on a display screen, execution information related to execution of at least one application specified on the basis of a predetermined determination result; and a processing control unit configured to execute first processing in a case where the at least one application is specified, and execute second processing on the basis of a response of a user to the displayed execution information.Type: GrantFiled: July 18, 2018Date of Patent: November 1, 2022Assignee: SONY CORPORATIONInventor: Hiroki Mine
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Patent number: 11481942Abstract: A unified platform obtains, stores, and shares search results based on user profiles or groups with a common interest. User profiles or group profiles may be used to identify categories containing objects related to a common interest, and the objects may be selected for placement in a graphical user interface from which they may be purchased by or for the user. The objects may preferably be virtual objects stored in a virtual locker or other virtual display unit. Users are able to conduct web-based searches for products or services from different websites and store dimensional representations of virtual products or services in a unified platform.Type: GrantFiled: December 22, 2020Date of Patent: October 25, 2022Assignee: IMAPLAYER, LLCInventors: William Geivett, Christopher Hayes
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Patent number: 11475322Abstract: A computer-implemented method that includes obtaining a plurality of values each corresponding to one of a plurality of variables. The plurality of variables include variables of interest. The method includes obtaining a prediction for the values from a model, determining metric(s) for each of the variables of interest, and determining one or more of the variables of interest to be one or more influential variables based on the metric(s) determined for each of the variables of interest. The variables include one or more non-influential variables that is/are different from the influential variable(s). The influential variable(s) has/have a greater influence on the prediction than the non-influential variable(s).Type: GrantFiled: March 5, 2019Date of Patent: October 18, 2022Assignee: SYNCHRONY BANKInventors: Gregory Dean Jorstad, Thomas Patrick Prendergast, Jr.
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Patent number: 11475324Abstract: A method, apparatus, system, and computer program product for generating a human readable recommendation. The method determines, by a computer system, a key performance value for a key performance indicator from a collection of data; A metric value for a metric is determined by the computer system from the collection of data. A correlation coefficient indicating a correlation between the key performance indicator and the metric is identified by the computer system. A human readable recommendation is generated by the computer system using a recommendation pattern when the correlation coefficient indicates that the correlation between the key performance indicator and the metric is sufficiently significant.Type: GrantFiled: November 21, 2019Date of Patent: October 18, 2022Assignee: International Business Machines CorporationInventors: Lukasz G. Cmielowski, Maksymilian Erazmus, Rafal Bigaj, Wojciech Sobala
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Patent number: 11475357Abstract: Systems and methods for computing a causal uplift in performance of an output action for one or more treatment actions in parallel are described herein. In an embodiment, a server computer receives interaction data for a particular period of time which identifies a plurality of users and a plurality of actions that were performed by each user of the plurality of users through a particular graphical user interface during the particular period of time. The server computer uses the interaction data to generate a feature matrix of actions for each user, and a set of confounding variables included to minimize spurious correlations. The feature matrix is then used to train a machine learning system, using data identifying a user's performance or non-performance of each action as inputs and data identifying performance or non-performance of a target output action as the output.Type: GrantFiled: July 29, 2019Date of Patent: October 18, 2022Assignee: APMPLITUDE, INC.Inventors: Scott Kramer, Cynthia Rogers, Eric Pollmann, Muhammad Bilal Mahmood