Patents Examined by Daniel C Puentes
  • Patent number: 11157802
    Abstract: The method of present disclosure relates to neural chip and optimizing operation of a neural chip. The method includes sensing current values of physical parameters indicating an environment. Sensed current values are stored in a memory unit. The memory unit also stores previously sensed values of physical parameters. The current values and the previously sensed values are compared by the neural chip. Based on the comparison, one or more actions are applied using the previously sensed values, for completing the task, if the current values and the previously sensed values are matched. In case there is no matching, the neural chip uses the current valises for applying the one or more actions. The neural chip learns from applying of the actions and updates itself accordingly.
    Type: Grant
    Filed: July 19, 2017
    Date of Patent: October 26, 2021
    Assignee: Wipro Limited
    Inventor: Rishav Das
  • Patent number: 11151461
    Abstract: A system includes a processor configured to wirelessly receive data indicating vehicle-feature usage for an individual vehicle. The processor is also configured to aggregate received data to form a feature-usage customer profile defining feature preferences. The processor is further configured to select vehicles associated with a customer-classification, including predefined feature-usage characteristics, the customer-classification determined based on a correlation between the predefined feature-usage characteristics and the aggregated data in the feature-usage profile defining feature preferences. The processor is also configured to compare the aggregated data to the selected vehicles to determine a vehicle having features preferred by a customer as indicated by the aggregated data in the feature-usage profile and recommend the determined vehicle to the customer.
    Type: Grant
    Filed: July 5, 2017
    Date of Patent: October 19, 2021
    Assignee: Ford Global Technologies
    Inventors: Kenneth James Miller, Thomas G. Leone
  • Patent number: 11152181
    Abstract: A method includes performing by a processor: estimating a total cathode space current for a thermionic vacuum tube having at least one grid and a plate, such that at least one amplification factor associated with the at least one grid is determined by a polynomial based on a variable that represents at plurality of voltages associated with the at least one grid and the plate, the variable being heuristically determine. Transitions between positive and negative grid operation may experience a step change in estimated current value caused by the inclusion or elimination of grid current. A part of the grid current may be added back into the plate current during transition. This small contribution to plate current may gradually diminish as tube operation moves farther away from the transition boundary.
    Type: Grant
    Filed: May 17, 2019
    Date of Patent: October 19, 2021
    Assignee: Panayotis Tsambos
    Inventor: Panayotis Tsambos
  • Patent number: 11132613
    Abstract: Systems and methods for mapping configuration items to business functions within a corporate infrastructure are disclosed. Discovery processes to automatically create and update service maps may introduce an artificial dependency between configuration items that is not necessary to the business function represented in the service map. These unnecessary dependencies may be considered “noise” and unnecessarily complicate the service map. Using machine learning techniques and procedures to identify short lived connections embodiments in accordance with this disclosure, dependency connections that may be considered noise may be detected and flagged. Once detected, these connections may be automatically removed from the service map to improve its accuracy and usefulness. Additionally, a user interface is provided that explains the “reason codes” for identification of noise connections.
    Type: Grant
    Filed: September 28, 2017
    Date of Patent: September 28, 2021
    Assignee: ServiceNow, Inc.
    Inventors: Yuval Rimar, Stephen Scott Tucker, Evan Qu, Vishal Rao, Haviv Rosh, Hardik Modi, Chris Nguyen, Amit Chandulal Dhuleshia, Oron Subayi
  • Patent number: 11132609
    Abstract: A method is proposed for training a multitask computer system, such as a multitask neural network system. The system comprises a set of trainable workers and a shared module. The trainable workers and shared module are trained on a plurality of different tasks, such that each worker learns to perform a corresponding one of the tasks according to a respective task policy, and said shared policy network learns a multitask policy which represents common behavior for the tasks. The coordinated training is performed by optimizing an objective function comprising, for each task: a reward term indicative of an expected reward earned by a worker in performing the corresponding task according to the task policy; and at least one entropy term which regularizes the distribution of the task policy towards the distribution of the multitask policy.
    Type: Grant
    Filed: November 19, 2019
    Date of Patent: September 28, 2021
    Assignee: DeepMind Technologies Limited
    Inventors: Razvan Pascanu, Raia Thais Hadsell, Victor Constant Bapst, Wojciech Czarnecki, James Kirkpatrick, Yee Whye Teh, Nicolas Manfred Otto Heess
  • Patent number: 11123002
    Abstract: This invention, which focuses on personality and aptitude matching by psychophysiologic response to stimuli, is referred to as Brain Matching. In general terms, this invention starts by selecting highly specialized skill sets and top performer group for each skill set. The various groups are analyzed though psychophysiologic stimuli testing by using basically the same testing consisting of large numbers stimuli tests in a consistent testing environment. Stimuli tests can range from hundreds to thousands of images each producing a brainwave response. Neural Networks, Artificial Intelligence, Deep Learning computers look at the test results, highly specialized group by other highly specialized group to reduce the groups signature/response commonality into a template. Test subjects are then tested using the same stimuli. The subject's test results are analyzed for correlation with the various specialized expert groups.
    Type: Grant
    Filed: August 12, 2020
    Date of Patent: September 21, 2021
    Inventors: Robert William Kocher, Loran Dean Ambs
  • Patent number: 11121705
    Abstract: A DC voltage switch may include: a first node and a second node for series integration into a pole of a DC voltage line; a third node for the other pole of the line; a mechanical switch between the first and second nodes; a pulse-current module in parallel with the switch; four semiconductor switches connected as bridges comprising two series of two semiconductor switches; a pulse-current capacitor in parallel with the two series; and a switchable semiconductor element. The pulse-current module includes three module nodes. Potential points between the semiconductor switches of the two series correspond to the first and second module node and the outer ends of the two series of in each case two of the semiconductor switches are connected in pairs to a fourth module node and a fifth module node and the semiconductor element is between the fifth and third module node.
    Type: Grant
    Filed: January 27, 2017
    Date of Patent: September 14, 2021
    Assignee: SIEMENS AKTIENGESELLSCHAFT
    Inventors: Jaganath Krishnan, Henry Gueldner, Karsten Handt, Sebastian Nielebock
  • Patent number: 11106974
    Abstract: A technique for training a neural network including an input layer, one or more hidden layers and an output layer, in which the trained neural network can be used to perform a task such as speech recognition. In the technique, a base of the neural network having at least a pre-trained hidden layer is prepared. A parameter set associated with one pre-trained hidden layer in the neural network is decomposed into a plurality of new parameter sets. The number of hidden layers in the neural network is increased by using the plurality of the new parameter sets. Pre-training for the neural network is performed.
    Type: Grant
    Filed: July 5, 2017
    Date of Patent: August 31, 2021
    Assignee: International Business Machines Corporation
    Inventors: Takashi Fukuda, Osamu Ichikawa
  • Patent number: 11100410
    Abstract: Systems and methods for probability forecasts and an energy transmission and/or energy distribution network are provided. Operational management may be carried out using a network control system with systematic consideration of forecast uncertainties. The probability of a distribution network being operable in a stable manner (e.g., with N-1 certainty) in a planning period is included. The system includes a forecaster for forecasts for a planning period, a forecast analyzer connected to the forecasts from the at least one forecaster, and elements for further information for outputting estimated forecast uncertainties. The system also includes a stability probability analyzer connected to the forecasts from the at least one forecaster, the estimated forecast uncertainties from the forecast analyzer, and elements for further information for outputting at least one item of information relating to an N-1 stability of the distribution network in the planning period.
    Type: Grant
    Filed: April 28, 2017
    Date of Patent: August 24, 2021
    Assignee: SIEMENS AKTIENGESELLSCHAFT
    Inventors: Mathias Duckheim, Arvid Amthor, Markus Reischböck
  • Patent number: 11093855
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for an crowd sourced training of an artificial intelligence system. One of the methods includes generating a training set using the customer communication information. The method includes training an artificial intelligence system using the training set. The method includes extracting at least one conversation pattern using the artificial intelligence system. The method includes the actions of instructing a chat application to process the at least one conversation pattern.
    Type: Grant
    Filed: January 24, 2017
    Date of Patent: August 17, 2021
    Assignee: United Services Automobile Association (USAA)
    Inventors: Kevin K. Fiedler, Jeffrey William Gallagher, Justin Leggett
  • Patent number: 11093793
    Abstract: Various embodiments described herein provide for a neural network tailored, based on user-provided input data, to detect user-specified objects in image data. An architecture of an embodiment may use unlabeled data from the user, such as a set of images from a video camera stream, while parameters of a tailored neural network (CNN) are trained or adapted.
    Type: Grant
    Filed: August 29, 2017
    Date of Patent: August 17, 2021
    Assignee: Vintra, Inc.
    Inventors: Ariel Amato, Angel Domingo Sappa, Carlo Gatta, Brent Boekestein
  • Patent number: 11093853
    Abstract: A system combines inputs from human processing and machine processing, and employs machine learning to improve processing of individual tasks based on comparison of human processing results. Once performance of a particular task by machine processing reaches a threshold, the level of human processing used on that task is reduced.
    Type: Grant
    Filed: November 6, 2016
    Date of Patent: August 17, 2021
    Assignees: Tagasauris, Inc., New York University
    Inventors: Joshua M. Attenberg, Panagiotis G. Ipeirotis
  • Patent number: 11093857
    Abstract: A method and apparatus for generating information. A specific embodiment of the method includes: acquiring a set of geographic information point sequences and a set of identifiers comprising an identifier of each geographic information point sequence in the set of the geographic information point sequences; for the each geographic information point sequence in the set of the geographic information point sequences, clustering geographic information points in the each geographic information point sequence and generating an element sequence corresponding to the each geographic information point sequence; learning, by utilizing a machine learning method based on the set of identifiers and the generated element sequences, to obtain a matrix for the identifiers in the set of identifiers; and generating, for each identifier in the set of identifiers, based on the identifier and the matrix, information of a user to which the geographic information point sequence indicated by the identifier belongs.
    Type: Grant
    Filed: September 28, 2017
    Date of Patent: August 17, 2021
    Assignee: Baidu Online Network Technology (Beijing) Co., Ltd.
    Inventors: Jingbo Zhou, Mengwen Xu, Yuan Xia, Haishan Wu
  • Patent number: 11094029
    Abstract: One embodiment provides for a method of transmitting data between multiple compute nodes of a distributed compute system, the method comprising creating a global view of communication operations to be performed between the multiple compute nodes of the distributed compute system, the global view created using information specific to a machine learning model associated with the distributed compute system; using the global view to determine a communication cost of the communication operations; and automatically determining a number of network endpoints for use in transmitting the data between the multiple compute nodes of the distributed compute system.
    Type: Grant
    Filed: April 10, 2017
    Date of Patent: August 17, 2021
    Assignee: INTEL CORPORATION
    Inventors: Dhiraj D. Kalamkar, Karthikeyan Vaidyanathan, Srinivas Sridharan, Dipankar Das
  • Patent number: 11087201
    Abstract: A method for determining an architecture for a task neural network configured to perform a particular machine learning task is described.
    Type: Grant
    Filed: April 29, 2020
    Date of Patent: August 10, 2021
    Assignee: Google LLC
    Inventors: Wei Hua, Barret Zoph, Jonathon Shlens, Chenxi Liu, Jonathan Huang, Jia Li, Fei-Fei Li, Kevin Patrick Murphy
  • Patent number: 11087206
    Abstract: A mechanism is described for facilitating memory handling and data management in machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting multiple tables associated with multiple neural networks at multiple autonomous machines, where each of the multiple tables include an index. The method may further include combining the multiple tables and multiple indexes associated with the multiple tables into a single table and a single index, respectively, where the single table is communicated to the multiple autonomous machines to allow simultaneous processing of one or more portions of the single table using one or more memory devices and one or more processors of one or more of the multiple autonomous machines.
    Type: Grant
    Filed: April 28, 2017
    Date of Patent: August 10, 2021
    Assignee: INTEL CORPORATION
    Inventors: Tomer Schwartz, Ehud Cohen, Uzi Sarel, Amitai Armon, Yaniv Fais, Lev Faivishevsky, Amit Bleiweiss, Yahav Shadmiy, Jacob Subag
  • Patent number: 11080608
    Abstract: In one or more embodiments, one or more methods, processes, and/or systems may receive data associated with effective completion of tasks by agents and determine a positive correlation within the data between first particular feature values of feature vectors associated with the tasks and second particular feature values of feature vectors associated with the agents. A first agent associated with a feature vector that matches, within a first threshold, the second particular feature values may be selected, and a probability that the first agent will effectively complete a first task based on a feature vector associated with the first task matching, within a second threshold, the first particular feature values may be determined.
    Type: Grant
    Filed: May 5, 2017
    Date of Patent: August 3, 2021
    Assignee: WorkFusion, Inc.
    Inventors: Andrii Volkov, Maxim Yankelevich, Mikhail Abramchik, Abby Levenberg
  • Patent number: 11080586
    Abstract: A computer-implement method and an apparatus are provided for neural network reinforcement learning. The method includes obtaining, by a processor, an action and observation sequence. The method further includes inputting, by the processor, each of a plurality of time frames of the action and observation sequence sequentially into a plurality of input nodes of a neural network. The method also includes updating, by the processor, a plurality of parameters of the neural network by using the neural network to approximate an action-value function of the action and observation sequence.
    Type: Grant
    Filed: November 6, 2017
    Date of Patent: August 3, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Sakyasingha Dasgupta, Takayuki Osogami
  • Patent number: 11062792
    Abstract: A facility for identifying combinations of feature and machine learning algorithm parameters, where each combination can be combined with one or more machine learning algorithms to train a model, is disclosed. The facility evaluates each genome based on the ability of a model trained using that genome and a machine learning algorithm to produce accurate results when applied to a validation data set by, for example, generating a fitness or validation score for the trained model and the corresponding genome used to train the model. Genomes that produce fitness scores that exceed a fitness threshold are selected for mutation, mutated, and the process is repeated. These trained models can then be applied to new data to generate predictions for the underlying subject matter.
    Type: Grant
    Filed: July 18, 2017
    Date of Patent: July 13, 2021
    Assignee: Analytics For Life Inc.
    Inventors: Paul Grouchy, Timothy Burton, Ali Khosousi, Abhinav Doomra, Sunny Gupta, Ian Shadforth
  • Patent number: 11055607
    Abstract: A neural network device includes a crossbar grid including first metal lines running in a first direction and second metal lines running transversely to the first metal lines and being electrically isolated from the first metal lines. An array of cross-over elements is included. Each cross-over element is connected between a first metal line and a second metal line. The cross-over elements each include a floating gate transistor device having a floating node. The floating node is configured to store a programmable weight value.
    Type: Grant
    Filed: June 20, 2016
    Date of Patent: July 6, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventor: Effendi Leobandung