Prediction Patents (Class 706/21)
  • Patent number: 12289216
    Abstract: Methods and systems are described herein for modifying scheduled events based on bandwidth availability. To modify the scheduled event, the system determines a plurality of user devices corresponding to an event. The system receives first network conditions for a first user device and generates a feature input based on the first network conditions. The system inputs the feature input into an artificial intelligence model to determine a first available bandwidth metric and aggregates the first available bandwidth metric with respective available bandwidth metrics for other user devices of the plurality of user devices to determine a composite available bandwidth metric. The system can compare the composite available bandwidth metric to a threshold available bandwidth metric and in response to determining that the composite available bandwidth metric equals or exceeds the threshold available bandwidth metric, the system generates for display, on a user device interface, a recommendation for modifying the event.
    Type: Grant
    Filed: October 31, 2023
    Date of Patent: April 29, 2025
    Assignee: Capital One Services, LLC
    Inventors: Galen Rafferty, Samuel Sharpe, Jeremy Goodsitt, Grant Eden, Austin Walters
  • Patent number: 12281932
    Abstract: An abnormal sound identification device includes an arithmetic device and an output device. The arithmetic device is configured to identify frequency-time data recorded in a vehicle, specify a first time range and a second time range in the frequency-time data, input the frequency-time data to the trained model to cause the trained model to identify an abnormal sound generated in the first time range as a first abnormal sound based on the input frequency-time data and cause the trained model to identify an abnormal sound generated in the second time range as a second abnormal sound, and cause the output device to output a kind of the first abnormal sound with the kind not matching a kind of the second abnormal sound among the first abnormal sounds.
    Type: Grant
    Filed: July 8, 2022
    Date of Patent: April 22, 2025
    Assignee: TOYOTA JIDOSHA KABUSHIKI KAISHA
    Inventor: Yu Ueda
  • Patent number: 12277489
    Abstract: The present invention provides a system for processing user queries through an artificial intelligence (“AI”) pipeline, utilizing data chunking, question generation, and AI models to deliver contextually relevant responses. The system includes a server that ingests and chunks datasets, generates vector embeddings, and stores the data in one or more vector databases. A pipeline engine sends the chunked data to an AI model that generates potential questions tailored to different user personas. These questions, along with their corresponding data chunks, are stored in the database for future retrieval. When a user submits a query, the system semantically compares the query to the pre-generated question vectors and retrieves the most relevant question and associated data chunk. The query is then sent to an external AI model for final response generation. The system provides seamless interaction, delivering optimized, context-aware responses to user queries in real-time.
    Type: Grant
    Filed: November 13, 2024
    Date of Patent: April 15, 2025
    Assignee: Airia LLC
    Inventor: Rohit Pradeep Shetty
  • Patent number: 12273278
    Abstract: The present disclosure relates to a method comprising receiving a request to execute a workload using an artificial intelligence model. A current resource utilization status in the distributed system may be determined. The current resource utilization status may be used to define a deployment configuration of the artificial intelligence model, wherein the deployment configuration is defined by: a number and structure of input blocks, a number and structure of output blocks and the intermediate block of the artificial intelligence model, a second computer system to execute the intermediate block, and one or more first computer systems to execute the input and output blocks. The artificial intelligence model may be deployed in accordance with the defined deployment configuration and the workload may be executed.
    Type: Grant
    Filed: October 10, 2023
    Date of Patent: April 8, 2025
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Aladin Djuhera, Alecio Pedro Delazari Binotto, Fernando Luiz Koch, Rob High
  • Patent number: 12271939
    Abstract: An online concierge system includes a marketplace automation engine for setting various control parameters affecting marketplace operation. The marketplace automation engine applies a hyperparameter learning model to the marketplace state data to predict a set of hyperparameters affecting a set of respective parameterized control decision models. The hyperparameter learning model is trained on historical marketplace state data and a configured outcome objective for the online concierge system. The marketplace automation engine independently applies the set of parameterized control decision models to the marketplace state data using the hyperparameters to generate a respective set of control parameters affecting marketplace operation of the online concierge system. The marketplace automation engine applies the respective set of control parameters to operation of the online concierge system.
    Type: Grant
    Filed: June 30, 2022
    Date of Patent: April 8, 2025
    Assignee: Maplebear Inc.
    Inventors: Sonali Deepak Chhabria, Xiangyu Wang, Aman Jain, Ganesh Krishnan, Trace Levinson, Jian Wang
  • Patent number: 12259735
    Abstract: Aspects of the subject disclosure may include, for example, determining, at a slower time-scale, inner layer weights of an inner layer of a deep neural network; providing periodically to an outer layer of the deep neural network from the inner layer, a feature vector based upon the inner layer weights; and determining, at a faster time-scale, outer layer weights of the outer layer, wherein the outer layer weights are determined in accordance with a Model Reference Adaptive Control (MRAC) update law that is based upon the feature vector from the inner layer, and wherein the outer layer weights are determined more frequently than the inner layer weights. Other embodiments are disclosed.
    Type: Grant
    Filed: June 22, 2021
    Date of Patent: March 25, 2025
    Assignee: THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS
    Inventors: Girish Chowdhary, Girish Joshi, Jasvir Virdi
  • Patent number: 12260660
    Abstract: A feature extraction system, method and apparatus based on neural network optimization by gradient filtering is provided. The feature extraction method includes: acquiring, by an information acquisition device, input information; constructing, by a feature extraction device, different feature extraction networks, performing iterative training on the networks in combination with corresponding training task queues to obtain optimized feature extraction networks for different input information, and calling a corresponding optimized feature extraction network to perform feature extraction according to a class of the input information; performing, by an online updating device, online updating of the networks; and outputting, by a feature output device, a feature of the input information. The new feature extraction system, method and apparatus avoids the problem of catastrophic forgetting of the artificial neural network in continuous tasks, and achieves high accuracy and precision in continuous feature extraction.
    Type: Grant
    Filed: August 25, 2021
    Date of Patent: March 25, 2025
    Assignee: INSTITUTE OF AUTOMATION, CHINESE ACADEMY OF SCIENCES
    Inventors: Yang Chen, Guanxiong Zeng, Shan Yu
  • Patent number: 12260314
    Abstract: For machine-based prediction of visitation, a machine-learned network embeds the visitation and metadata information. Since the trace data used to show access may be sparse, another machine-learned network completes the route data. Another machine-learned network recommends effectiveness of content based on routes, the graph, metadata, and/or other information. The recommendation is based on training using counterfactual and/or other causal modeling.
    Type: Grant
    Filed: May 22, 2023
    Date of Patent: March 25, 2025
    Assignee: Billups LLC
    Inventor: Shawn Spooner
  • Patent number: 12253266
    Abstract: A household appliance device includes a control unit configured to output during performance of an appliance function a suggestion relating to an appliance function parameter assigned to the appliance function, with the control unit configured to take into account a history for the suggestion.
    Type: Grant
    Filed: May 12, 2020
    Date of Patent: March 18, 2025
    Assignee: BSH Hausgeräte GmbH
    Inventors: Carlos Franco Gutierrez, Teresa Del Carmen Marzo Alvarez, Maria Parra Borderías, Agostina Rodriguez Larrosa, Beatriz Villanueva Valero
  • Patent number: 12248880
    Abstract: Some embodiments provide a method for training a machine-trained (MT) network that processes inputs using network parameters. The method propagates a set of input training items through the MT network to generate a set of output values. The set of input training items comprises multiple training items for each of multiple categories. The method identifies multiple training item groupings in the set of input training items. Each grouping includes at least two training items in a first category and at least one training item in a second category. The method calculates a value of a loss function as a summation of individual loss functions for each of the identified training item groupings. The individual loss function for each particular training item grouping is based on the output values for the training items of the grouping. The method trains the network parameters using the calculated loss function value.
    Type: Grant
    Filed: August 27, 2023
    Date of Patent: March 11, 2025
    Assignee: Amazon Technologies, Inc.
    Inventors: Eric A. Sather, Steven L. Teig, Andrew C. Mihal
  • Patent number: 12243211
    Abstract: In a method for training a neural network to recognize a tool condition based on image data, the neural network is trained to recognize the tool condition of a first tool type, and image data of a second tool type is applied. The image data is subjected to image processing. Via this, the image data of the second tool type is converted into image data of the first tool type. The neural network is trained based on the converted image data. In a method for machining and/or production via the first tool type, the tool condition of the first tool type is recognized via a neural network that is trained in accordance with such a method.
    Type: Grant
    Filed: August 27, 2021
    Date of Patent: March 4, 2025
    Assignee: Siemens Aktiengesellschaft
    Inventors: Benjamin Samuel Lutz, Daniel Regulin
  • Patent number: 12242923
    Abstract: Systems and methods are described herein which may be implemented using computer programs comprising instructions that replicate the neural synchronization algorithm of the human brain. These implementations result in reduction, optimization, security and acceleration of data records/frames and processing in a computer system or network. An embodiment of the invention comprises motion decimation, motions reactor, motion replicator and motion aggregator modules for replicating higher intelligence functions, and a management module for configuring resources and monitoring system operation. Systems and methods as described herein may operate on wired or wireless computer networks. Data are translated from original format into thalamic motion and further encoded with motion signal protocol, then reproduced and aggregated using thalamic motion for integration with higher forms of intelligence.
    Type: Grant
    Filed: September 20, 2019
    Date of Patent: March 4, 2025
    Inventor: David Allan Edgar
  • Patent number: 12210945
    Abstract: A method of defining an implementation of circuits in a programmable device can be provided by receiving a plurality of specifications for a hyperdimensional (HD) computing machine learning application for execution on a programmable device, determining parameters for a template architecture for HD computing machine learning using the plurality of specifications, the template architecture including an HD hypervector encoder, an HD associative search unit, programmable device pre-defined processing units, and programmable device pre-defined processing elements within the pre-defined processing units, and generating programmable device code configured to specify resources to be allocated within the programmable device using pre-defined circuits defined for use in the programmable device using the determined parameters for the template architecture.
    Type: Grant
    Filed: April 21, 2021
    Date of Patent: January 28, 2025
    Assignee: The Regents of the University of California
    Inventors: Sahand Salamat, Mohsen Imani, Behnam Khaleghi, Tajana Rosing
  • Patent number: 12210949
    Abstract: The systems and methods provide a model deployment criterion. The model deployment criterion indicates a difference in a value against which the proxy model may be measured to determine when, if ever, the proxy model should be deployed to replace the existing rule engine. The model deployment criterion may be keyed to the proxy model (e.g., based on a difference in its size, throughput speed, number of changes, etc.), the existing rule engine (e.g., based on a difference in its age, update occurrences to its rule base, etc.), and/or comparisons between models (e.g., based on differences in results, throughput speed, efficiency, etc.).
    Type: Grant
    Filed: July 23, 2024
    Date of Patent: January 28, 2025
    Assignee: Citibank, N.A.
    Inventors: Miriam Silver, James Myers
  • Patent number: 12210942
    Abstract: Provided are a method and device for data processing and a storage medium. The method includes: inputting labeled training data in a training set into a preset model to be trained and updating the model parameters of the preset model; inputting labeled verification data in a verification set into the preset model after the model parameters are updated to obtain a first prediction label; obtaining a verification loss value based on a difference between the first prediction label and a marked label of the labeled verification data; determining an auxiliary loss value based on current structural parameters of the preset model; determining whether to stop training the preset model based on the verification loss value and the auxiliary loss value; and classifying data to be classified based on a target network model constructed by a network structure included in the trained preset model to obtain a classification result.
    Type: Grant
    Filed: January 12, 2021
    Date of Patent: January 28, 2025
    Assignee: Beijing Xiaomi Pinecone Electronics Co., Ltd.
    Inventors: Xiangxiang Chu, Bo Zhang, Tianbao Zhou, Bin Wang
  • Patent number: 12198327
    Abstract: The present invention proposes a technique for enabling the execution of measurement processing without referring to a design drawing for which it is difficult to adjust or obtain parameters for image processing that requires knowhow. This measurement system according to the present disclosure refers to a learning model generated on the basis of teaching data, which is generated from a sample image of a semiconductor, and the sample image, generates a region-segmented image from an input image (measurement subject) of a semiconductor having a predetermined structure, and uses the region-segmented image to perform image measurement. Here, the teaching data is an image in which labels, which include a structure of the semiconductor in the sample image, are assigned to each pixel of the image, and the learning model includes parameters for deducing teaching data from the sample image (see indicator 1).
    Type: Grant
    Filed: August 30, 2019
    Date of Patent: January 14, 2025
    Assignee: Hitachi High-Tech Corporation
    Inventors: Ryou Yumiba, Kei Sakai, Satoru Yamaguchi
  • Patent number: 12188360
    Abstract: A system and process for restarting a turbomachine includes a shutdown cooldown protection process implemented by a plant level control system or direct control system of the turbomachine. The system and process for restarting ensure rotating components are cooled as expected prior to a unit restart. This system and process for restarting will lockout an ability to restart if an improper cooldown of rotating components is detected. If this lockout is enabled, delaying restart for the rotating components to cool naturally is needed, or the operator could decide to force cool the components.
    Type: Grant
    Filed: March 4, 2024
    Date of Patent: January 7, 2025
    Assignee: GE Infrastructure Technology, LLC
    Inventors: Garth Curtis Frederick, Brett Darrick Klingler, Kenneth Damon Black, Radu Ioan Danescu
  • Patent number: 12169790
    Abstract: An abduction apparatus 1 includes: a probability calculation unit 2 configured to calculate, with respect to each of candidate hypotheses generated using observation information and knowledge information, a probability that the candidate hypothesis is an explanation regarding the observation information; a closed world assumption probability calculation unit 3 configured to calculate, with respect to the candidate hypotheses, a closed world assumption probability that the candidate hypothesis is an explanation regarding a first-order predicate logic literal to which a new truth value is determined as a result of assuming a closed world assumption; and a solution hypothesis determination unit 4 configured to determine a solution hypothesis that is a best explanation regarding the observation information from the candidate hypotheses using the probability and the closed world assumption probability.
    Type: Grant
    Filed: August 27, 2018
    Date of Patent: December 17, 2024
    Assignee: NEC CORPORATION
    Inventor: Kazeto Yamamoto
  • Patent number: 12169785
    Abstract: An embodiment includes parsing an input dataset associated with a first node of a decision tree, where the input dataset includes a set of profile values for a set of projected usage parameters for a computing environment. The embodiment identifies a structure of the dataset using a recursive neural network that predicts a question sequence in a hierarchical tree format. The embodiment calculates a first deviation from the predicted question sequence and determines whether the deviation exceeds a threshold value. The embodiment generates a modified input dataset using a disambiguation rule and calculates a second deviation of the modified structure from the predicted question sequence and determines whether the deviation exceeds the threshold value. The embodiment assembles a customized hierarchical path using a generative model and assembles the customized hierarchical path by performing iterations of generating a series of candidate questions until a leaf node is reached.
    Type: Grant
    Filed: April 15, 2021
    Date of Patent: December 17, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Indervir Singh Banipal, Shikhar Kwatra, Nadiya Kochura, Sourav Mazumder
  • Patent number: 12169777
    Abstract: Artificial-intelligence-based river information system. In an embodiment, a first training dataset is used to train a travel time prediction model to predict a travel time along the waterway for a given trip. In addition, a second training dataset is used to train a river level prediction model to predict a river level along the waterway for a given time. For each of a plurality of trips, a request is received that specifies the trip and a time of the trip, and, in response to the request, the travel time prediction model is used to predict a travel time for the trip, and the river level prediction model is used to predict a river level of the waterway at one or more points along the trip. Then, a voyage plan is generated based on one or both of the predicted travel time and the predicted river level.
    Type: Grant
    Filed: March 30, 2023
    Date of Patent: December 17, 2024
    Assignee: TRABUS
    Inventors: Joseph Celano, David Sathiaraj, Eric Ho, Andrew Nolan Smith, Eric Vincent Rohli
  • Patent number: 12165035
    Abstract: The systems and methods may use one or more artificial intelligence models that predict an effect of a predicted event on a current state of the system. For example, the model may predict how a rate of change in time-series data may be altered throughout the first time period based on the predicted event. In addition, the system may use a machine learning model to classify a user, based on current state characteristics, into a class of users and identify peers of the user. Based on those peers, the system may identify items for the user and generate a predetermined output variable.
    Type: Grant
    Filed: January 19, 2024
    Date of Patent: December 10, 2024
    Assignee: Citibank, N.A.
    Inventors: Prasanth Babu Madakasira Ramakrishna, Girish Wali, Deepali Tuteja, Ernst Wilhelm Spannhake, II, Thomas Gianelle, Milan Shah
  • Patent number: 12130938
    Abstract: A computer implemented data product release method or system. The data product release is derived from a sensitive dataset using a privacy protection system such as a differentially private system. The privacy protection parameters, such as noise addition magnitude, are configurable as part of the data product release method or system to alter the balance between maintaining privacy of the sensitive dataset and making the data product release useful.
    Type: Grant
    Filed: December 18, 2018
    Date of Patent: October 29, 2024
    Assignee: PRIVITAR LIMITED
    Inventors: Charles Codman Cabot, Kieron Francois Pascal Guinamard, Jason Derek McFall, Pierre-Andre Maugis, Hector Page, Benjamin Thomas Pickering, Theresa Stadler, Jo-anne Tay, Suzanne Weller
  • Patent number: 12124252
    Abstract: A server displays information about a plurality of industrial machines on a display of a client computer. The server includes a storage device, a processor, and a communication device. The storage device stores state data indicative of states of a plurality of industrial machines. The processor determines remaining lives of the plurality of industrial machines from the state data. The processor generates data indicative of a machine list screen. The machine list screen includes identifiers of the plurality of industrial machines and the remaining lives. The communication device outputs the data indicative of the machine list screen to a client computer via a communication network.
    Type: Grant
    Filed: December 17, 2019
    Date of Patent: October 22, 2024
    Assignee: KOMATSU INDUSTRIES CORPORATION
    Inventors: Kouji Funabashi, Yusuke Masato, Taketoshi Fukumura, Eiji Doba
  • Patent number: 12100051
    Abstract: According to some embodiments, a hail history storage device may store information periodically received from a remote third-party weather reporting service. A hail history score request associated with a geographic location and a date range may be received from a remote requester device. Responsive to the received hail history score request, a computer processor of a hail history server may automatically access information in the hail history storage device based on the geographic location and date range. Moreover, the computer processor may automatically evaluate accessed information to calculate a hail history score value. The computer processor may then transmit, to the remote requester device, historical hail evaluation data including the calculated hail history score value.
    Type: Grant
    Filed: September 9, 2021
    Date of Patent: September 24, 2024
    Assignee: Hartford Fire Insurance Company
    Inventor: Seth J. Boutin
  • Patent number: 12093821
    Abstract: The present teaching relates to method, system, medium, and implementation of a global model update center. At least one model is established at the model update center for detecting objects surrounding each of autonomous driving vehicles of a fleet. A plurality of labeled data items are received, from the fleet of autonomous driving vehicles, where each of the labeled data items is detected, based on the at least one model, from sensor data characterizing surroundings of the autonomous driving vehicles. The labeled data items are generated automatically on-the-fly by the autonomous driving vehicles. Based on the received labeled data items, at least some of the models are updated and model update information is accordingly generated. Such generated model update information is then distributed to the fleet of autonomous driving vehicles.
    Type: Grant
    Filed: June 10, 2021
    Date of Patent: September 17, 2024
    Assignee: PlusAI, Inc.
    Inventors: Hao Zheng, David Wanqian Liu, Timothy Patrick Daly, Jr.
  • Patent number: 12094142
    Abstract: Based on ICESat-2 high-resolution data, the disclosure proposes a method for mapping tree height.
    Type: Grant
    Filed: October 19, 2023
    Date of Patent: September 17, 2024
    Assignee: WUHAN UNIVERSITY
    Inventors: Zhaocong Wu, Haoyu Lin
  • Patent number: 12073729
    Abstract: A computing device may include operational processors, configured to execute a set of program instructions, wherein the set of program instructions is configured to cause the operational processors to: receive input signals indicative of input conditions; determine input conditions based input signals; determine output signals based on the determined input conditions; and provide determined output signals. The computing device may further include machine-learning processors, wherein the machine-learning processors are configured to develop machine-learning analyzers, wherein the machine-learning analyzers are configured to: identify operational parameters of the operational processors; determine modifications to the set of program instructions, wherein the modifications satisfy a selected quality metric; and provide the modifications to the operational processors.
    Type: Grant
    Filed: April 27, 2021
    Date of Patent: August 27, 2024
    Assignee: Rockwell Collins, Inc.
    Inventors: John W. Borghese, Ryan M. Murphy, Ella M. Atkins
  • Patent number: 12073440
    Abstract: Tiered advertisement bidding is disclosed. One or more quality metrics associated with a user profile are determined. An advertisement bid is selected from a plurality of tiered bids based at least in part on the determined quality metrics. Determining the quality metrics can include determining a conversion assessment. Determining the quality metric can also include determining whether a need associated with a user profile has been met for a category. In some cases, persona detection is performed with respect to the user profile.
    Type: Grant
    Filed: August 31, 2023
    Date of Patent: August 27, 2024
    Assignee: Security Technology, LLC
    Inventor: Bjorn Markus Jakobsson
  • Patent number: 12056583
    Abstract: Respective statistical distributions of a target variable within a proposed training data set and a proposed test data set for a machine learning model are obtained. A metric indicative of the difference between the two statistical distributions is computed. The difference metric is used to determine whether the proposed test data set is acceptable to evaluate the machine learning model.
    Type: Grant
    Filed: July 26, 2020
    Date of Patent: August 6, 2024
    Assignee: Amazon Technologies, Inc.
    Inventors: Saman Zarandioon, Robert Matthias Steele
  • Patent number: 12056203
    Abstract: Described herein are systems and methods for determining key website pages based on automated website analysis. A method can include identifying, by a computing system, a website to evaluate, the website having webpages, locally executing and interpreting webpages code to render the webpages as they would appear on user devices, receiving an indication that user input was received at a user device indicating selection of criteria that specify webpage characteristics, determining an initial quantity of webpages that satisfy the criteria, providing information to the user device to cause the device to present an indication of the initial quantity of webpages, designating multiple webpages as key webpages of the website based on determining that each of the multiple webpages satisfies the criteria, adding the multiple webpages to a list of key pages, and providing information to the user device to cause the device to present the list of key pages.
    Type: Grant
    Filed: February 1, 2022
    Date of Patent: August 6, 2024
    Assignee: Siteimprove A/S
    Inventors: Cavit Ilker, Ana Urcelay Lorenzo, Martin Birkebæk
  • Patent number: 12044540
    Abstract: Systems and methods are provided for assisting the navigation function based in part on detection of disconnection from vehicle integration functions by other devices navigating to the same destination, where the disconnections occurred outside of a predetermined boundary associated with the destination.
    Type: Grant
    Filed: March 30, 2024
    Date of Patent: July 23, 2024
    Inventor: Noel Francis Igoe
  • Patent number: 12019412
    Abstract: An autonomous module for processing stored data includes a multithreaded processor core (MPC) and a plurality of autonomous memories. Each of the plurality of autonomous memories has a memory bank, a data operator (DO) configured to implement a plurality of selectable memory behaviors, an autonomous memory operator (AMO) configured to implement a state machine to control the memory bank independently of the MPC, and at least one memory input/output (IO) port communicatively coupled with the memory bank, the AMO, and the DO. The at least one memory IO port is configured to receive a read instruction from the AMO, retrieve data from the memory bank, and send the data to the DO. The DO is configured to implement one of the plurality of selectable memory behaviors to update the data and send the updated data to the AMO via the at least one memory IO port.
    Type: Grant
    Filed: June 26, 2023
    Date of Patent: June 25, 2024
    Assignee: THE TRUSTEES OF DARTMOUTH COLLEGE
    Inventors: Richard Granger, Elijah Floyd William Bowen, Antonio Rodriguez, Andrew Felch
  • Patent number: 12020136
    Abstract: Disclosed is an operation method of a neural network including a first network and a second network, the method including acquiring state information output from the first network based on input information, determining whether the state information satisfies a condition using the second network, iteratively applying the state information to the first network in response to determining that the state information does not satisfy the condition, and outputting the state information in response to determining that the state information satisfy the condition.
    Type: Grant
    Filed: March 5, 2019
    Date of Patent: June 25, 2024
    Assignee: Samsung Electronics Co., Ltd.
    Inventors: Junhwi Choi, Young-Seok Kim, Jeong-Hoon Park, Seongmin Ok, Jehun Jeon
  • Patent number: 12019704
    Abstract: Systems, methods, and computer-readable media for achieving privacy for both data and an algorithm that operates on the data. A system can involve receiving an algorithm from an algorithm provider and receiving data from a data provider, dividing the algorithm into a first algorithm subset and a second algorithm subset and dividing the data into a first data subset and a second data subset, sending the first algorithm subset and the first data subset to the algorithm provider and sending the second algorithm subset and the second data subset to the data provider, receiving a first partial result from the algorithm provider based on the first algorithm subset and first data subset and receiving a second partial result from the data provider based on the second algorithm subset and the second data subset, and determining a combined result based on the first partial result and the second partial result.
    Type: Grant
    Filed: February 13, 2023
    Date of Patent: June 25, 2024
    Assignee: TRIPLEBLIND HOLDING COMPANY
    Inventors: Greg Storm, Riddhiman Das, Babak Poorebrahim Gilkalaye
  • Patent number: 12020085
    Abstract: Examples described herein include systems and methods for prioritizing workloads, such as virtual machines, to enforce quality of service (“QoS”) requirements. An administrator can assign profiles to workloads, the profiles representing different QoS categories. The profiles can extend scheduling primitives that can determine how a distributed resource scheduler (“DRS”) acts on workloads during various workflows. The scheduling primitives can be used to prioritize workload placement, determine whether to migrate a workload during load balancing, and determine an action to take during host maintenance. The DRS can also use the profile to determine which resources at the host to allocate to the workload, distributing higher portions to workloads with higher QoS profiles. Further, the DRS can factor in the profiles in determining total workload demand, leading to more efficient scaling of the cluster.
    Type: Grant
    Filed: July 26, 2021
    Date of Patent: June 25, 2024
    Assignee: VMware LLC
    Inventors: Zhelong Pan, Matthew Kim, Varun S. Lingaraju
  • Patent number: 12014398
    Abstract: Deep neural network (DNN) models have been widely used for user-relevance content prediction. Presented herein are embodiments of a new user-relevance framework, which may be referred as Gating-Enhanced Multi-task Neural Networks (GemNN) embodiments. Neural network-based multi-task learning model embodiments herein predict user engagement with content in a coarse-to-fine manner, which gradually reduces content candidates and allows parameter sharing from upstream tasks to downstream tasks to improve the training efficiency. Also, in one or more embodiments, a gating mechanism was introduced between embedding layers and multi-layer perceptions to learn feature interactions and control the information flow fed to MLP layers. Tested embodiments demonstrated considerable improvements over prior approaches.
    Type: Grant
    Filed: July 7, 2021
    Date of Patent: June 18, 2024
    Assignees: Baidu USA LLC, Baidu.com Times Technology (Beijing) Co., Ltd.
    Inventors: Hongliang Fei, Jingyuan Zhang, Xingxuan Zhou, Junhao Zhao, Banghu Yin, Ping Li
  • Patent number: 12010302
    Abstract: Disclosed according to one exemplary embodiment includes not limited to: a filtering unit configured to generate filtering information by filtering a residual image corresponding to a difference between an original image and a prediction image; an inverse filtering unit configured to generate inverse filtering information by inversely filtering the filtering information; an estimator configured to generate the prediction image based on the original image and reconstruction information; a CNN-based in-loop filter configured to receive the inverse filtering information and the prediction image and to output the reconstruction information; and an encoder configured to perform encoding based on the filtering information and information of the prediction image, and wherein the CNN-based in-loop filter is trained for each of the plurality of artefact sections according to an artefact value or for each of the plurality of quantization parameter sections according to a quantization parameter.
    Type: Grant
    Filed: December 26, 2022
    Date of Patent: June 11, 2024
    Assignee: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY
    Inventor: Mun Churl Kim
  • Patent number: 12007899
    Abstract: Disclosed in some examples are improved address prediction and memory preloading that leverages next-delta prediction and/or far-delta prediction for scheduling using a DNN. Previous memory access sequence data that identify one or more memory addresses previously accessed by one or more processors of a system may be processed and then converted into a sequence of delta values. The sequence of delta values are then mapped to one or more classes that are then input to a DNN. The DNN then outputs a predicted future class identifier sequence that represents addresses that the DNN predicts will be accessed by the processor in the future. The predicted future class identifier sequence is then converted back to a predicted delta value sequence and back into a set of one or more predicted addresses.
    Type: Grant
    Filed: July 18, 2022
    Date of Patent: June 11, 2024
    Assignee: Micron Technology, Inc.
    Inventors: Aliasger Tayeb Zaidy, David Andrew Roberts, Patrick Michael Sheridan, Lukasz Burzawa
  • Patent number: 11989658
    Abstract: A method and an apparatus for exclusive reinforcement learning are provided, comprising: collecting information of states of an environment through the communication interface and performing a statistical analysis on the states using the collected information; determining a first state value of a first state among the states in a training phase and a second state value of a second state among the states in an inference phase based on analysis results of the statistical analysis; performing reinforcement learning by using one reinforcement learning unit of a plurality of reinforcement learning unit which performs reinforcement learnings from different perspectives according to the first state value; and selecting one of actions determined by the plurality of reinforcement learning unit based on the second state value and applying selected action to the environment.
    Type: Grant
    Filed: July 15, 2020
    Date of Patent: May 21, 2024
    Assignee: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE
    Inventors: Hyunseok Kim, Myung Eun Kim, Seonghyun Kim, Young Sung Son, Jongkwon Son, Soonyong Song, Donghun Lee, Ingook Jang, Jin Chul Choi
  • Patent number: 11989676
    Abstract: Various embodiments relate to data science and data analysis, computer software and systems, and computing architectures and data models configured to facilitate management of enterprise functions, and, more specifically, to an enterprise computing and data processing platform configured to activate risk management transformations of enterprise data in-situ, responsive to identifying a risk event, and further configured to implement a risk management data channel to facilitate analyses and responses associated with an enterprise computing device. In some examples, a method may include receiving a risk data signal, identifying a portion of the risk data signal, computing data representing a risk level, classifying data associated with a hierarchical business data object in accordance with a risk level, aggregating classified data with other data associated with other business data objects classified as a function of risk to form aggregated data, causing presentation of aggregated data as a function of risk.
    Type: Grant
    Filed: May 4, 2020
    Date of Patent: May 21, 2024
    Assignee: Certinia Inc.
    Inventors: Paul Shane Ripley, Simon Kristiansen Ejsing, Daniel Christian Brown, Matthew Lowell Cox
  • Patent number: 11983236
    Abstract: A computer-implemented method, computer program product and computing system for executing a description model when utilizing a website; detecting a failure associated with the execution of the description model; re-executing the description model one or more times in an attempt to utilize the website; and if a failure is detected one or more times, reporting the failure to a user.
    Type: Grant
    Filed: July 6, 2021
    Date of Patent: May 14, 2024
    Assignee: THE IREMEDY HEALTHCARE COMPANIES, INC.
    Inventors: James A. Harding, Anthony J. Paquin, Scott Thibault, Jason A. Boatman
  • Patent number: 11974863
    Abstract: Disclosed herein are techniques related to glucose estimation without continuous glucose monitoring. In some embodiments, the techniques may involve receiving input data associated with a user. The input data may comprise discrete blood glucose measurement data associated with the user, activity data associated with the user, contextual data associated with the user, or a combination thereof. The techniques may also involve using an estimation model and the input data associated with the user to generate one or more estimated blood glucose values associated with the user.
    Type: Grant
    Filed: January 5, 2023
    Date of Patent: May 7, 2024
    Assignee: MEDTRONIC MINIMED, INC.
    Inventors: Arthur Mikhno, Yuxiang Zhong, Pratik Agrawal
  • Patent number: 11961013
    Abstract: Disclosed is an electronic apparatus. The electronic apparatus may include a memory configured to store one or more training data generation models and an artificial intelligence model, and a processor configured to generate personal training data that reflects a characteristic of a user using the one or more training data generation models, train the artificial intelligence model using the personal learning data as training data, and store the trained artificial intelligence model in the memory.
    Type: Grant
    Filed: July 8, 2020
    Date of Patent: April 16, 2024
    Assignee: SAMSUNG ELECTRONICS CO., LTD.
    Inventors: Chiyoun Park, Jaedeok Kim, Youngchul Sohn, Inkwon Choi
  • Patent number: 11960575
    Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.
    Type: Grant
    Filed: October 27, 2022
    Date of Patent: April 16, 2024
    Assignee: Splunk Inc.
    Inventors: Manish Sainani, Sergey Slepian, Di Lu, Adam Oliner, Jacob Leverich, Iryna Vogler-Ivashchanka, Iman Makaremi
  • Patent number: 11941513
    Abstract: Provided is a device for ensembling data received from prediction devices and a method of operating the same. The device includes a data manager, a learner, and a predictor. The data manager receives first and second device prediction results from first and second prediction devices, respectively. The learner may adjust a weight group of a prediction model for generating first and second item weights, first and second device weights, based on the first and second device prediction results. The first and second item weights depend on first and second item values, respectively, of the first and second device prediction results. The first device weight corresponds to the first prediction device, and the second device weight corresponds to the second prediction device. The predictor generates an ensemble result of the first and second device prediction results, based on the first and second item weights and the first and second device weights.
    Type: Grant
    Filed: November 28, 2019
    Date of Patent: March 26, 2024
    Assignee: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE
    Inventors: Myung-Eun Lim, Jae Hun Choi, Youngwoong Han
  • Patent number: 11941439
    Abstract: According to an embodiment, an information processing device is configured to assign a first computing device one or more first tasks of processing respective one or more first partial data of a plurality of partial data included in an n-dimensional target data, n being an integer greater than or equal to 2, the target data being to be processed using a neural network, the one or more first partial data including first data and second data adjacent to the first data in a direction of m-dimension, m being an integer satisfying 1?m?n; and instruct the first computing device to execute a second task included in the one or more first tasks, according to an execution status of second partial data of the plurality of partial data included in the target data, the second partial data being executed by the second computing device.
    Type: Grant
    Filed: August 27, 2021
    Date of Patent: March 26, 2024
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Ryota Tamura, Mizuki Ono, Masanori Furuta
  • Patent number: 11926332
    Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, a first probability distribution may be generated for the vehicle at a first future point in time using a generative model for predicting expected behaviors of objects and a set of characteristics for the vehicle at an initial time expected to be perceived by an observer. Planning system software of the vehicle may be used to generate a trajectory for the vehicle to follow. A second probability distribution may be generated for a second future point in time using the generative model based on the trajectory and a set of characteristics for the vehicle at the first future point expected to be perceived by the observer. A surprise assessment may be generated by comparing the first probability distribution to the second probability distribution. The vehicle may be controlled based on the surprise assessment.
    Type: Grant
    Filed: September 16, 2022
    Date of Patent: March 12, 2024
    Assignee: Waymo LLC
    Inventors: Johan Engstrom, Jared Russell
  • Patent number: 11930089
    Abstract: A highway detection system may include a telematics device associated with a vehicle having one or more sensors arranged therein, a mobile device associated with a user traveling in the vehicle, and a server computer. The server computer may receive traveling data for a trip of the user from the one or more sensors and via the telematics device. The server computer may then determine whether the user is traveling within a city or on a highway based on analysis of the traveling data for the trip of the user, which may include a statistical analysis to calculate standard deviations of metrics in the traveling data. In response to the determination, the server computer may generate a notification to transmit to the user based on whether the user is traveling within a city or on a highway and transmit the notification to the mobile device associated with the user.
    Type: Grant
    Filed: December 7, 2022
    Date of Patent: March 12, 2024
    Assignee: Allstate Solutions Private Limited
    Inventors: Rahul Kothari, Payal Patel, Anirudha S I
  • Patent number: 11928593
    Abstract: Among a great deal of other disclosure and scope, systems and methods are enclosed that enable for highly efficient labeling of data. For example, in some of many cases, a novel methodology for ranking vectors most useful to label next is disclosed. In such an example, a neural network is trained to predict this ranking methodology upon being given a set of heuristics from which to assess the given problem space. A user can continue the cycle of identifying a set of candidate vectors to label, compiling relevant heuristics from said vectors, ranking vectors via the trained neural network, selecting a subset of the ranked vectors, inquiring an oracle regarding the true labels of the vectors, and then appending the subset of newly labelled vectors to the labelled set of vectors until satisfaction.
    Type: Grant
    Filed: June 15, 2021
    Date of Patent: March 12, 2024
    Assignee: Fortinet, Inc.
    Inventor: Sameer T. Khanna
  • Patent number: 11916773
    Abstract: A system, method, and computer-readable medium for performing a data center management and monitoring operation. The data center management and monitoring operation includes: receiving data center data from a plurality of data center assets within a data center, the data center data comprising outlier data detection data; assigning the data center data to a vectorized input space; reducing a dimension of the vectorized input space to a latent space; decoding the latent space to provide a vectorized decoded output space; and, performing an outlier data detection operation using the vectorized decoded output space, wherein the outlier data detection operation is performed to detect data center asset outlier data.
    Type: Grant
    Filed: January 24, 2023
    Date of Patent: February 27, 2024
    Assignee: Dell Products L.P.
    Inventors: Raja Neogi, Khayam Anjam