Structure Patents (Class 706/26)
  • Patent number: 12238126
    Abstract: Systems and methods are disclosed for improving on-chip security, while minimizes the latency and cost of security techniques to improve system-level performance and power simultaneously. The framework uses machine learning algorithms, such as an artificial neural network (ANN), for runtime attack detection with higher accuracy. Further, a learning-based attack mitigation method using deep reinforcement learning is disclosed, where the method may be used to isolate the malicious components and to optimize network latency and energy-efficiency.
    Type: Grant
    Filed: May 4, 2021
    Date of Patent: February 25, 2025
    Assignee: The George Washington University
    Inventors: Ke Wang, Hao Zheng, Ahmed Louri
  • Patent number: 12233860
    Abstract: Human drivers generally cannot plan a collision evasion maneuver in the brief interval before impact, other than simply slamming on the brakes and hoping for the best. Often the collision could have been avoided by swerving or other sequence of actions. Therefore, improved collision avoidance and mitigation procedures are disclosed, based on a well-trained artificial intelligence (AI) model that takes over the accelerator, brake, and steering in an emergency. With fast electronic reflexes and AI-based computational power, the AI model can find a more effective avoidance maneuver, or at least an action that would minimize the harm (for example, by swerving to miss the passenger compartment). The AI model can then implement the sequence instantly, without fear or hesitation. The result—fewer collisions and less fatality on our highways.
    Type: Grant
    Filed: February 5, 2024
    Date of Patent: February 25, 2025
    Inventors: David E. Newman, R. Kemp Massengill
  • Patent number: 12229680
    Abstract: A method comprises receiving an input signal for processing in one or more neurons of a neural network, wherein the neural network has zero bias neurons and includes a plurality of resistive processing unit (RPU) weights and each neuron has an activation function. The method also includes applying an arbitrary amplification factor to activation function outputs of the one or more neurons in the neural network, wherein the arbitrary amplification factor is based on a dynamic range of components in the neural network and compensates for conductance drift in values of the RPU weights. The method also includes performing a calculation with the neural network using the amplified activation function outputs of the one or more neurons.
    Type: Grant
    Filed: September 28, 2020
    Date of Patent: February 18, 2025
    Assignee: International Business Machines Cororation
    Inventors: HsinYu Tsai, Stefano Ambrogio, Sanjay Kariyappa, Mathieu Gallot
  • Patent number: 12224756
    Abstract: The present invention includes a CDR circuit including a phase detector, a neural network circuit, a controller and a clock signal generator is disclosed. The phase detector is configured to use a clock signal to sample an input signal to generate a plurality of phase detection results. The neural network circuit is coupled to the phase detector, and is configured to receive the plurality of phase detection results to determine information of a frequency difference between the clock signal and the input signal. The controller is configured to generate a control signal according to the information of the frequency difference between the clock signal and the input signal. The clock signal generator is configured to use the control signal to adjust a phase or frequency of the clock signal outputted to the phase detector.
    Type: Grant
    Filed: January 30, 2023
    Date of Patent: February 11, 2025
    Assignee: MEDIATEK INC.
    Inventors: Chien-Kai Kao, Shih-Che Hung, Tse-Hsien Yeh
  • Patent number: 12206535
    Abstract: Systems, methods, and apparatuses for efficiently transmitting wireless communication signals are provided. An artificial neural network (ANN) is configured to take in an input data symbol sequence and generate a corresponding discrete-time Orthogonal Frequency Division Multiplexing (OFDM) sequence therefrom. The ANN combines multiple baseband signal-processing operations, one of which includes OFDM modulation. Training data tunes the ANN to provide the discrete-time OFDM signal with at least one of a low multiple input multiple output (MIMO) condition number, a predetermined number of eigenvalues above a threshold value, low peak-to-average-power ratio (PAPR), a low bit error probability, or a high bandwidth efficiency.
    Type: Grant
    Filed: March 14, 2023
    Date of Patent: January 21, 2025
    Assignee: Tybalt, LLC
    Inventor: Steve Shattil
  • Patent number: 12198020
    Abstract: Systems and computer-implemented methods for training a machine learnable model and for using the machine learned model for inference, both of which using only limited memory resources. During training and inference, the machine learnable model uses previous state information. A state memory is provided which efficiently stores this previous state information. Instead of storing each previous state individually and integrally, for each element of the internal state, a value is stored in the state memory which is indicative of a most recent occurrence of an element of the internal state of the machine learnable model holding or transitioning to a particular binary state value. The states of the machine learnable model are representable as binary values and when states infrequently hold or transition to a particular binary state value.
    Type: Grant
    Filed: November 24, 2020
    Date of Patent: January 14, 2025
    Assignee: ROBERT BOSCH GMBH
    Inventor: Volker Fischer
  • Patent number: 12197350
    Abstract: An accelerator is disclosed. A tier storage may store data. A circuit may process the data to produce a processed data. The accelerator may load the data from a device using a cache-coherent interconnect protocol.
    Type: Grant
    Filed: January 27, 2022
    Date of Patent: January 14, 2025
    Assignee: SAMSUNG ELECTRONICS CO., LTD.
    Inventors: Marie Mai Nguyen, Rekha Pitchumani, Yang Seok Ki, Krishna Teja Malladi
  • Patent number: 12182539
    Abstract: Systems and methods provide a first deployment criterion for deploying modified decision engines. A first existing decision engine is accessed, as well as a first modified decision engine that includes rule data generated by an artificial intelligence model based on the first existing decision engine. A first difference between a first output and a first modified output is determined, where the first output is generated by the first existing decision engine and the first modified output is generated by the first modified decision engine. A first selected decision engine is deployed to process subsequent data items to produce subsequent outputs, based on whether the first difference satisfies first deployment criterion. When metric generated based on the subsequent outputs satisfies a criterion modification condition, the artificial intelligence model is used to generate a second deployment criterion, wherein a second selected rule-based decision engine is deployed based on the second deployment criterion.
    Type: Grant
    Filed: May 20, 2024
    Date of Patent: December 31, 2024
    Assignee: Citibank, N.A.
    Inventors: James Myers, Miriam Silver
  • Patent number: 12182682
    Abstract: Provided is a ticketing system adapted to retrieve a recommendation from a knowledge database in response to a received query, the ticketing system including a processor adapted to perform semantic similarity learning in textual description pairs by calculating similarity scores for similarities between the received query and tickets stored in the knowledge database of the ticketing system, wherein each textual description pair includes a textual description of the received query and a textual description of a ticket of a plurality of tickets stored in the knowledge database of the ticketing system, wherein the ticket having the maximum similarity score is identified and a solution of the identified ticket is output as the retrieved recommendation for the received query by the ticketing system.
    Type: Grant
    Filed: January 23, 2018
    Date of Patent: December 31, 2024
    Assignee: Siemens Aktiengesellschaft
    Inventors: Bernt Andrassy, Pankaj Gupta
  • Patent number: 12174631
    Abstract: A method of operating an apparatus using a control system that includes at least one neural network. The method includes receiving an input value captured by the apparatus, processing the input value using the at least one neural network of the control system implemented on first one or more solid-state chips, and obtaining an output from the at least one neural network resulting from processing the input value. The method may also include processing the output with another neural network implemented on solid-state chips to determine whether the output breaches a predetermined condition that is unchangeable after an initial installation onto the control system. The aforementioned another neural network is prevented from being retrained. The method may also include the step of using the output from the at least one neural network to control the apparatus unless the output breaches the predetermined condition. Similar corresponding apparatuses are described.
    Type: Grant
    Filed: October 12, 2023
    Date of Patent: December 24, 2024
    Assignee: Apex AI Industries, LLC
    Inventor: Kenneth A. Abeloe
  • Patent number: 12165050
    Abstract: Networks for distributing parameters and data to neural network compute cores. In various embodiments, a neural inference chip comprises a plurality of neural cores and at least one network interconnecting the plurality of neural cores. Each of the plurality of neural cores is adapted to apply a plurality of synaptic weights to a plurality of input activations to produce a plurality of output activations. The at least one network is adapted to simultaneously deliver synaptic weights and/or input activations to the plurality of neural cores.
    Type: Grant
    Filed: October 11, 2018
    Date of Patent: December 10, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: John V. Arthur, Brian Taba, Rathinakumar Appuswamy, Andrew S. Cassidy, Pallab Datta, Steven K. Esser, Myron D. Flickner, Jennifer Klamo, Dharmendra S. Modha, Hartmut Penner, Jun Sawada
  • Patent number: 12133739
    Abstract: A method of predicting a brain atrophy condition for an individual using the individual's predicted age difference (PAD). The method comprises acquiring at least one brain image of the individual; processing the brain image to obtain at least one feature of the brain image; generating a PAD value of the individual based on the at least one feature of the image; and determining a brain atrophy condition of the individual based on the PAD value.
    Type: Grant
    Filed: December 14, 2023
    Date of Patent: November 5, 2024
    Assignees: ACROVIZ USA INC., TAIPEI MEDICAL UNIVERSITY
    Inventors: Wen-Yih Tseng, Yung-Chin Hsu, Lung Chan, Chien-Tai Hong, Yueh-Hsun Lu, Jia-Hung Chen, Li-Kai Huang
  • Patent number: 12135739
    Abstract: A system and method of generating conversation topics using neural networks. The method includes providing, by a processing device, a plurality of conversations to a neural network to generate a plurality of clusters. The method includes selecting, for each cluster of the plurality of clusters, a topic and one or more keywords from one or more n-grams. The method includes evaluating, for each cluster of the plurality of clusters, the topic and the one or more keywords by searching historical conversations and current conversations to identify one or more conversations related to the cluster.
    Type: Grant
    Filed: February 22, 2023
    Date of Patent: November 5, 2024
    Assignee: Intercom, Inc.
    Inventors: Fergal Reid, Cathal Horan, Mario Kostelac
  • Patent number: 12117946
    Abstract: The present specification discloses a calculation processing device which has a high processing rate with low cost. The calculation processing device according to the present specification is a calculation processing device including a fetch unit which reads, from a memory, data required for a calculation to perform processing of a neural network, and provides the data to a calculation unit. The fetch unit may comprise: multiple routers each having a data processing mapping table in which a scheme of processing input data is recorded according to a node identifier (ID) of the input data; and a fetch network controller which controls respective data processing mapping tables of the multiple routers.
    Type: Grant
    Filed: October 12, 2020
    Date of Patent: October 15, 2024
    Assignee: FuriosaAI Co.
    Inventors: Han Joon Kim, Young Geun Choi, Byung Chul Hong
  • Patent number: 12118880
    Abstract: Systems and methods described herein relate to coordinated vehicle lane assignment. One embodiment receives from a locality manager, at a section manager that communicates with one or more connected vehicles in a section of a roadway, target lateral flows for two or more lanes of the roadway in the section of the roadway; converts the target lateral flows to a target number of connected vehicles N at the section manager; selects for lane change, at the section manager, a set of N connected vehicles whose ranked distances from a following vehicle in a target lane are greatest among the one or more connected vehicles, when a direction of lane change is uniform among the set of N connected vehicles; and transmits lane-change actions from the section manager to the set of N connected vehicles.
    Type: Grant
    Filed: March 18, 2022
    Date of Patent: October 15, 2024
    Assignee: Toyota Motor Engineering & Manufacturing North America, Inc.
    Inventors: Abdul Rahman Kreidieh, Yashar Zeiynali Farid, Kentaro Oguchi
  • Patent number: 12112624
    Abstract: Systems and methods described herein relate to traffic-flow regulation via centralized lateral flow control. One embodiment receives, at a locality manager that regulates traffic flow on a roadway via lateral flow control, aggregated macroscopic traffic state information from a section manager that communicates with one or more connected vehicles in a section of the roadway; processes the aggregated macroscopic traffic state information at the locality manager using a reinforcement-learning-based model to determine target lateral flows for two or more lanes of the roadway in the section of the roadway; and transmits the target lateral flows from the locality manager to the section manager, which converts the target lateral flows to lane-change actions and transmits the lane-change actions to the one or more connected vehicles.
    Type: Grant
    Filed: March 18, 2022
    Date of Patent: October 8, 2024
    Assignee: Toyota Motor Engineering & Manufacturing North America, Inc.
    Inventors: Abdul Rahman Kreidieh, Yashar Zeiynali Farid, Kentaro Oguchi
  • Patent number: 12107741
    Abstract: Spatial-temporal informative patterns for users and devices associated with data networks can be predicted or determined. An information management component (IMC) can analyze respective groups of items of data stored in respective formats in respective databases. Some items of data can comprise respective signal measurement data representative of respective signal measurements associated with respective devices associated with a communication network. Based on the analysis results, IMC can determine a spatial-temporal pattern(s) associated with the respective groups of items of data, wherein the spatial-temporal pattern(s) can relate to a subject of interest. The IMC can utilize artificial intelligence and/or machine learning algorithms and models to facilitate determining the spatial-temporal pattern(s). In response to a query relating to the subject of interest, the IMC can provide information relating to the subject of interest and responsive to the query based on the spatial-temporal pattern(s).
    Type: Grant
    Filed: November 3, 2021
    Date of Patent: October 1, 2024
    Assignee: AT&T Intellectual Property I, L.P.
    Inventors: Mehdi Malboubi, Baofeng Jiang, Yuhong Zheng
  • Patent number: 12099914
    Abstract: It is possible to analyze what type of input/output mapping is mainly performed in the entire hidden layer of a neural network. A relationship analysis unit 30 calculates strength of a relationship of each combination of a dimension of the input data and a unit of the neural network and calculates strength of a relationship of each combination of the unit and a dimension of the output data. A role analysis unit 32 calculates a relationship between a prescribed number of types of roles and the unit and a relationship between the prescribed number of types of roles, the dimension of the input data, and the dimension of the output data on the basis of the strength of the relationship of each combination of the dimension of the input data and the unit of the neural network and the strength of the relationship of each combination of the unit and the dimension of the output data.
    Type: Grant
    Filed: April 23, 2019
    Date of Patent: September 24, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Chihiro Watanabe, Kaoru Hiramatsu, Kunio Kashino
  • Patent number: 12101683
    Abstract: Among other things, embodiments of the present disclosure help to overcome environment-specific dependency issues of conventional Wi-Fi-based sensing systems, thus allowing a neural network to make better proximity predictions in an unseen environment. Other embodiments may be described and claimed.
    Type: Grant
    Filed: December 21, 2020
    Date of Patent: September 24, 2024
    Assignee: Intel Corporation
    Inventors: Omer Sholev, Ofir Degani, Elan Banin, Uri Parker, Assaf Gurevitz
  • Patent number: 12094381
    Abstract: Provided is a display panel which may include a pixel array including a plurality of pixels connected to scan lines and data lines, a photonic synapse block including a plurality of photonic synapse elements, and a neuron block including a plurality of neuron elements electrically connected to the plurality of photonic synapse elements.
    Type: Grant
    Filed: May 31, 2022
    Date of Patent: September 17, 2024
    Assignee: Samsung Display Co., Ltd.
    Inventors: Jungyu Lee, Joon-Chul Goh, Kanghee Lee
  • Patent number: 12079728
    Abstract: The present invention enables the structure of a neural network to be quantitatively analyzed. An analyzing unit calculates, for each of combinations of a dimension of input data and a cluster, a sum of squared errors between an output of each unit belonging to the cluster when a value of the dimension of the input data is replaced with an average value of the dimension of the input data included in learning data and an output of each unit belonging to the cluster for the input data before replacement as a relationship between the combinations, and calculates, for each of combinations of the cluster and a dimension of output data, a squared error between the value of the dimension of the output data when an output value of each unit belonging to the cluster is replaced with an average output value of each unit of the cluster when the input data included in the learning data was input and the value of the dimension of the output data before replacement as a relationship between the combinations.
    Type: Grant
    Filed: March 7, 2019
    Date of Patent: September 3, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Chihiro Watanabe, Kaoru Hiramatsu, Kunio Kashino
  • Patent number: 12073322
    Abstract: A computer-implemented method for training a classifier (??), including: training a pretext model (??) to learn a pretext task, so as to minimize a distance between an output of a source sample via the pretext model (??) and an output of a corresponding transformed sample via the pretext model (??), the transformed sample being a sample obtained by applying a transformation (T) to the source sample; S20) determining a neighborhood (NXi) of samples (Xi) of a dataset (SD) in the embedding space; S30) training the classifier (??) to predict respective estimated probabilities ??j(Xi), j=1 . . . C, for a sample (Xi) to belong to respective clusters (Cj), by using a second training criterion which tends to: maximize a likelihood for a sample and its neighbors (Xj) of its neighborhood (Nxi) to belong to the same cluster; and force the samples to be distributed over several clusters.
    Type: Grant
    Filed: May 21, 2021
    Date of Patent: August 27, 2024
    Assignees: TOYOTA JIDOSHA KABUSHIKI KAISHA, KATHOLIEKE UNIVERSITEIT LEUVEN
    Inventors: Wim Abbeloos, Gabriel Othmezouri, Wouter Van Gansbeke, Simon Vandenhende, Marc Proesmans, Stamatios Georgoulis, Luc Van Gool
  • Patent number: 12067479
    Abstract: Systems and methods for heterogenous hardware acceleration are disclosed. The systems and methods can include a neural network processing unit comprising compute tiles. Each of a first set of the compute tiles can include a first tensor array configured to support operations in a first number format. Each of a second set of the compute tiles can include a second tensor array configured to support operations in a second number format, the second number format supporting a greater range or a greater precision than the first number format, and a de-quantizer configured to convert data in the first number format to data in the second number format. The systems and methods can include neural network processing units, multi-chip hardware accelerators and distributed hardware accelerators including low-precision components for performing interference tasks and high-precision components for performing training tasks.
    Type: Grant
    Filed: October 25, 2019
    Date of Patent: August 20, 2024
    Assignee: T-Head (Shanghai) Semiconductor Co., Ltd.
    Inventor: Liang Han
  • Patent number: 12055920
    Abstract: The systems and methods provide an action recognition and analytics tool for use in manufacturing, health care services, shipping, retailing and other similar contexts. Machine learning action recognition can be utilized to determine cycles, processes, actions, sequences, objects and or the like in one or more sensor streams. The sensor streams can include, but are not limited to, one or more video sensor frames, thermal sensor frames, infrared sensor frames, and or three-dimensional depth frames. The analytics tool can provide for process validation, anomaly detection and in-process quality assurance.
    Type: Grant
    Filed: November 5, 2018
    Date of Patent: August 6, 2024
    Assignee: APPLE INC.
    Inventors: Prasad Narasimha Akella, Ananya Honnedevasthana Ashok, Krishnendu Chaudhury, Ashish Gupta, Sujay Venkata Krishna Narumanchi, David Scott Prager, Devashish Shankar, Ananth Uggirala
  • Patent number: 12056614
    Abstract: Systems, apparatuses and methods may provide for technology that aggregates contextual information from a first network layer in a neural network having a second network layer coupled to an output of the first network layer, wherein the context information is to be aggregated in real-time and after a training of the neural network, and wherein the context information is to include channel values. Additionally, the technology may conduct an importance classification of the aggregated context information and selectively exclude one or more channels in the first network layer from consideration by the second network layer based on the importance classification.
    Type: Grant
    Filed: April 9, 2018
    Date of Patent: August 6, 2024
    Assignee: Intel Corporation
    Inventors: Dmitry Gorokhov, Alexander Kozlov
  • Patent number: 12050977
    Abstract: The present disclosure relates to a method for representing an ordered group of symbols with a hypervector. The method comprises sequentially applying on at least part of the input hypervector associated with a current symbol a predefined number of circular shift operations associated with the current symbol, resulting in a shifted hypervector. A rotate operation may be applied on the shifted hypervector, resulting in an output hypervector. If the current symbol is not the last symbol of the ordered group of symbols the output hypervector may be provided as the input hypervector associated with a subsequent symbol of the current symbol; otherwise, the output hypervector of the last symbol of the ordered group of symbols may be provided as a hypervector that represents the ordered group of symbols.
    Type: Grant
    Filed: May 27, 2021
    Date of Patent: July 30, 2024
    Assignee: International Business Machines Corporation
    Inventors: Kumudu Geethan Karunaratne, Abbas Rahimi, Manuel Le Gallo-Bourdeau, Giovanni Cherubini, Abu Sebastian
  • Patent number: 12050982
    Abstract: A delay spiking neural network (DSNN) may include a plurality of neurons arranged in a plurality of layers, with neurons spiking based on accumulation of delayed inputs. A first to spike neuron in an output layer may provide a result of the DSNN.
    Type: Grant
    Filed: September 28, 2020
    Date of Patent: July 30, 2024
    Assignee: REFLEX ARC, LLC
    Inventor: Livio Ricciulli
  • Patent number: 12045721
    Abstract: In a neural network (NN) based wireless communication system, a BS determines, for an one-round latency T and an overall model size L of the NN model, i) Tu that makes {circumflex over (L)}*(Tu) larger than L and ii) Tl that makes {circumflex over (L)}*(Tl)<L; repeats determining {circumflex over (L)}*(Tm), {R*k,n}, {{circumflex over (L)}*k}, and {C*k,n} by using Tm=(Tu+Tl)/2 for k=1, K, and n=1, . . . N, while Tu is different from Tl; allocates NN model parameters to user equipments 1 to K based on {R*k,n}, {L*k}, and {C*k,n} determined based on Tm when Tu=Tl; and updates the NN model based on update results of the NN model parameters received from user equipments 1 to K.
    Type: Grant
    Filed: October 8, 2021
    Date of Patent: July 23, 2024
    Assignee: LG ELECTRONICS INC.
    Inventors: Kijun Jeon, Kaibin Huang, Dingzhu Wen, Sangrim Lee, Sungjin Kim
  • Patent number: 12045985
    Abstract: A program causes a computer to execute processing including: acquiring an endoscope image captured by an endoscope; inputting the acquired endoscope image into a plurality of learning models learned so as to output diagnosis support information regarding a lesion included in the endoscope image; acquiring a plurality of pieces of diagnosis support information output from each of the learning models; and outputting a plurality of pieces of the acquired diagnosis support information and information regarding each of the learning models in association with each other. Alternatively, the program causes the computer to execute the processing of inputting the acquired endoscope image into one learning model, executing a plurality of determination logics to acquire a plurality of pieces of output diagnosis support information, and outputting a plurality of pieces of the acquired diagnosis support information and information regarding each of the learning models in association with each other is executed.
    Type: Grant
    Filed: October 26, 2020
    Date of Patent: July 23, 2024
    Assignee: HOYA CORPORATION
    Inventor: Akihiko Nishide
  • Patent number: 12039449
    Abstract: A processor-implemented neural network method includes: extracting, by a feature extractor of a neural network, a plurality of training feature vectors corresponding to a plurality of training class data of each of a plurality of classes including a first class and a second class; determining, by a feature sample generator of the neural network, an additional feature vector of the second class based on a mean vector and a variation vector of the plurality of training feature vectors of each of the first class and the second class; and training a class vector of the second class included in a classifier of the neural network based on the additional feature vector and the plurality of training feature vectors of the second class.
    Type: Grant
    Filed: December 11, 2020
    Date of Patent: July 16, 2024
    Assignees: Samsung Electronics Co., Ltd., Korea Advanced Institute of Science and Technology
    Inventors: Seong-Jin Park, Sung Ju Hwang, Seungju Han, Insoo Kim, Jiwon Baek, Jaejoon Han
  • Patent number: 12039432
    Abstract: An artificial neural network (ANN) apparatus can include processing component circuitry that receives linear inputs, and removes linearity from the one or more linear inputs based on an S-shaped saturating activation function that generates a continuous non-linear output. The neurons of the ANN comprise digital bit-wise components configured to transform the linear inputs into the continuous non-linear output.
    Type: Grant
    Filed: March 18, 2020
    Date of Patent: July 16, 2024
    Assignee: Infineon Technologies AG
    Inventor: Andrew Stevens
  • Patent number: 12033480
    Abstract: An image-based real-time intrusion detection method and a surveillance camera that use artificial intelligence are provided to sample a plurality of frames input at a first point in time, acquire a probability that at least one object corresponding to a type of a target object exists in an image of the respective sampled frames by using a first artificial neural network, adjust a sampling rate for a plurality of frames to be input at a second point in time after the first point in time according to processing time of each frame of the first artificial neural network required to acquire an existence probability of the at least one object, select each of the respective sampled frames as a frame of the target object according to a magnitude of the acquired probability, generate a movement trajectory of each object corresponding to the type of the target object from the frames selected as the frame of the target object, and acquire an intrusion occurrence probability from the generated movement trajectory by usin
    Type: Grant
    Filed: April 23, 2020
    Date of Patent: July 9, 2024
    Assignee: ESCA CO., LTD.
    Inventor: Tae Woong Jeong
  • Patent number: 12032907
    Abstract: Systems and methods for natural language processing are described. One or more embodiments of the present disclosure receive a span of text comprising an offensive span and a non-offensive span, generate a contextualized word embedding for each of a plurality of words of the span of text, generate a refined vector representation for each of the plurality of words based on the corresponding contextualized word embedding using a refinement network trained for offensive text recognition, generate label information for each of the plurality of words based on the corresponding refined vector representation, wherein the label information indicates whether each of the plurality of words includes offensive text, and transmit an indication of a location of the offensive span based on the label information.
    Type: Grant
    Filed: July 2, 2021
    Date of Patent: July 9, 2024
    Assignee: ADOBE INC.
    Inventors: Amir Pouran Ben Veyseh, Franck Dernoncourt
  • Patent number: 12026728
    Abstract: Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of accessing first transaction data stored in a transaction database, the first transaction data describing first transactions for first items from first users; determining, using the first transaction data, first micro-intents associated with the first transaction data; grouping the first micro-intents into clusters; labeling each cluster of the first micro-intents with a respective label; receiving second transaction data of a user, the second transaction data describing second transactions for second items for the user; determining, using the second transaction data, second micro-intents present in the second transactions; receiving current transaction data from a user interface of an electronic device of the user; determining, using the current transaction data, that the user is expressing a curre
    Type: Grant
    Filed: August 5, 2019
    Date of Patent: July 2, 2024
    Assignee: WALMART APOLLO, LLC
    Inventors: Kannan Achan, Abhimanya Mitra, Sushant Kumar, Evren Korpeoglu
  • Patent number: 12026601
    Abstract: An apparatus, such as a stacked artificial neural network, can include a semiconductor at a first level. The semiconductor can include first circuitry. A memory can be at a second level. Second circuitry can be at a third level such that the memory is between the first circuitry and the second circuitry. The first circuitry can be configured propagate a first signal to the memory. The memory can be configured to propagate a second signal, based on data stored in the memory, to the second circuitry in response to the first signal. The second circuitry can be configured to generate a data signal based on the second signal.
    Type: Grant
    Filed: June 26, 2019
    Date of Patent: July 2, 2024
    Assignee: Micron Technology, Inc.
    Inventor: Fabio Pellizzer
  • Patent number: 12011833
    Abstract: A system and a method for robot control based on a memristive crossbar array comprises a sensor group, an input sensing signal modulator, a neuromorphic circuit, an output control signal modulator, an output device, an external supervisor module and a training controller; the neuromorphic circuit performs robot control, and the main part thereof is a memristor crossbar array with a fully-connected neural network structure, wherein a differential amplifying circuit and a multiplexing switch in the neuromorphic circuit are connected to the memristor crossbar array, an input signal vector is multiplied by a weight matrix stored in the memristor crossbar array, and one or more channels of analog output signals are obtained through the differential amplifying circuit.
    Type: Grant
    Filed: November 1, 2019
    Date of Patent: June 18, 2024
    Assignee: NANJING UNIVERSITY
    Inventors: Feng Miao, Shijun Liang, Cong Wang, Zaizheng Yang
  • Patent number: 12014263
    Abstract: The present invention relates to methods and systems for encoding and processing representations that include continuous structures using vector-symbolic representations. The system is comprised of a plurality of binding subsystems that implement a fractional binding operation, a plurality of unbinding subsystems that implement a fractional unbinding operation, and at least one input symbol representation that propagates activity through a binding subsystem and an unbinding subsystem to produce a high-dimensional vector representation of a continuous space.
    Type: Grant
    Filed: March 18, 2020
    Date of Patent: June 18, 2024
    Assignee: APPLIED BRAIN RESEARCH INC.
    Inventors: Aaron Russell Voelker, Christopher David Eliasmith, Brent Komer, Terrence Stewart
  • Patent number: 11994852
    Abstract: For reducing oscillations in a technical system plurality of different controller settings for the technical system is received. For a respective controller setting signal representing a time series of operational data of the technical system controlled by the respective controller setting is received, the signal is processed, whereby the processing includes a transformation into a frequency domain, and an entropy value of the processed signal is determined. Depending on the determined entropy values a controller setting from the plurality of controller settings is selected, and the selected controller setting is output for configuring the technical system.
    Type: Grant
    Filed: November 23, 2017
    Date of Patent: May 28, 2024
    Assignee: Siemens Aktiengesellschaft
    Inventors: Siegmund Düll, Kai Heesche, Gurdev Singh, Marc Christian Weber
  • Patent number: 11997485
    Abstract: This disclosure provides systems, methods, and apparatus for determining whether an incident radio-frequency (RF) signal is from a known transmission source based on a match between a signature of the incident RF signal and at least one stored signature. One or more antennas can generate a plurality of electrical signals corresponding to a portion of a pulse of the incident RF signal. At least one of amplitude or phase values of a first electrical signal and phase coherent second electrical signal can be determined in the frequency domain. The signature of the incident RF signal based on at least one of amplitude or phase values of the first and the second electrical signals can be determined. This signature can be compared with stored signatures to determine whether the incident RF signal is from a known transmission source.
    Type: Grant
    Filed: March 18, 2022
    Date of Patent: May 28, 2024
    Assignee: ENDPOINT SECURITY, INC.
    Inventors: R. Page Heller, Jay T. Labhart
  • Patent number: 11995048
    Abstract: Systems and methods for lifelong schema matching are described. The systems and methods include receiving data comprising a plurality of information categories, classifying each information category according to a schema comprising a plurality of classes, wherein the classification is performed by a neural network classifier trained based on a lifelong learning technique using a plurality of exemplar training sets, wherein each of the exemplar training sets includes a plurality of examples corresponding to one of the classes, and wherein the examples are selected based on a metric indicating how well each of the examples represents the corresponding class, and adding the data to a database based on the classification, wherein the database is organized according to the schema.
    Type: Grant
    Filed: September 29, 2020
    Date of Patent: May 28, 2024
    Assignee: ADOBE INC.
    Inventors: Handong Zhao, Yikun Xian, Sungchul Kim, Tak Yeon Lee, Nikhil Belsare, Shashi Kant Rai, Vasanthi Holtcamp, Thomas Jacobs, Duy-Trung T Dinh, Caroline Jiwon Kim
  • Patent number: 11986966
    Abstract: A method for operating a multi-agent system including multiple robots. Each robot cyclically carries out the following: starting from an instantaneous system state, ascertaining possible options, the options defining actions via which a transition from an instantaneous system state to a subsequent system state may be achieved; for each possible option, ascertaining action costs for carrying out an action indicated by the option; carrying out an auction, the action cost values ascertained for each option being taken into account by each of the other robots; and executing an action that corresponds to one of the options as a function of all cost values ascertained or received for the option in question, the action costs for an option taking into account an empirical parameter that is a function of costs for past actions, which have already been carried out and which are associated with the option, of the multiple robots.
    Type: Grant
    Filed: March 3, 2020
    Date of Patent: May 21, 2024
    Assignee: ROBERT BOSCH GMBH
    Inventors: Mathias Buerger, Philipp Christian Schillinger
  • Patent number: 11983633
    Abstract: An information processing apparatus (2000) acquires input data (10) and generates, by use of a neural network (30), condition data (50) that indicate one or more conditions satisfied by the input data (10). The information processing apparatus (2000) determines prediction data (20) by use of a value determined based on correct answer data (42) associated with example data (40) that satisfy at least a part of conditions indicated by the condition data (50).
    Type: Grant
    Filed: March 1, 2018
    Date of Patent: May 14, 2024
    Assignee: NEC CORPORATION
    Inventors: Yuzuru Okajima, Kunihiko Sadamasa
  • Patent number: 11982993
    Abstract: A method for selecting an AI solution for an automated robotic process including receiving at least one functional media including information indicative of brain activity by a human engaged in a task of interest, analyzing the functional media, identifying an activity level in at least one brain region, identifying a brain region parameter and an activity parameter; identifying an action parameter based in part on the brain region parameter or the activity parameter; and selecting a component of the AI solution in part on the brain region parameter, the activity parameter, or the action parameter.
    Type: Grant
    Filed: March 24, 2022
    Date of Patent: May 14, 2024
    Assignee: Strong Force TX Portfolio 2018, LLC
    Inventors: Charles Howard Cella, Jenna Lynn Parenti, Taylor D. Charon
  • Patent number: 11977982
    Abstract: The network comprises at least one network layer in which a plurality of electronic oscillators, interconnected via programmable coupling elements storing respective network weights, generate oscillatory signals at time delays dependent on the input signal to propagate the input signal from an input to an output of that layer. The network is adapted to provide a network output signal dependent substantially linearly on phase of oscillatory signals in the last layer of the network. The method includes calculating a network error dependent on the output signal and a desired output for the training sample, and calculating updates for respective network weights by backpropagation of the error such that weight-updates for a network layer are dependent on a vector of time delays at the input to that layer and the calculated error at the output of that layer.
    Type: Grant
    Filed: July 2, 2020
    Date of Patent: May 7, 2024
    Assignee: International Business Machines Corporation
    Inventors: Siegfried Friedrich Karg, Elisabetta Corti
  • Patent number: 11962671
    Abstract: Examples of biomimetic codecs and biomimetic coding techniques are described herein. Morphologically-adaptive coding networks can be developed in accordance with energy dissipation driven “heat” generated by application of training data. The morphologically-adaptive coding networks may be representative of common features expected in an input signal or data stream. Decoding may proceed using the morphologically-adaptive coding network. Morphologically-adaptive coding networks may be used as a cortex that can be shared for boosting multimedia data compression rates and/or increasing the encode-decode fidelity of information content while the features remain queryable in encoded form. Examples of the biomimetic codecs and biomimetic coding techniques provide a broad-based technology platform that can be used in context-IDed multimedia storage, pattern recognition, and high-performance computing/big data management, the hallmarks of web- and cloud-based systems.
    Type: Grant
    Filed: May 3, 2018
    Date of Patent: April 16, 2024
    Assignee: University of Washington
    Inventors: Mehmet Sarikaya, Burak Berk Ustundag
  • Patent number: 11942163
    Abstract: In a case of achievement of a neural network circuit using a plurality of nonvolatile memory cells, a technique capable of accurately reading information recorded in the plurality of nonvolatile memory cells is provided. A semiconductor device includes: a plurality of nonvolatile memory cells; a plurality of reference-current cells; and a sense amplifier comparing an electric current flowing in each of the plurality of nonvolatile memory cells and an electric current flowing in each of the plurality of reference-current cells. In this case, each cross-sectional structure of the plurality of reference-current cells is the same as each cross-sectional structure of the plurality of nonvolatile memory cells. The writing operation or the erasing operation is also performed to each of the plurality of reference-current memory cells when the writing operation or the erasing operation is performed to each of the plurality of nonvolatile memory cells.
    Type: Grant
    Filed: October 15, 2021
    Date of Patent: March 26, 2024
    Assignee: RENESAS ELECTRONICS CORPORATION
    Inventor: Yoshiyuki Kawashima
  • Patent number: 11941376
    Abstract: A method of providing intelligent software is provided. According to the present disclosure, it is possible to request an optimal AI model on the basis of a pre-trained AI model and meta information of the AI model, and it is possible to easily provide an AI model optimized for an intelligence device by responding to the request by creating a plurality of AI differentiation models from the AI model in accordance with a plurality of differentiation levels.
    Type: Grant
    Filed: December 6, 2021
    Date of Patent: March 26, 2024
    Assignees: Korea University of Technology, Education Industry-University Cooperation Foundation
    Inventors: Won-Tae Kim, Young-Jin Kim, Deun-Sol Cho
  • Patent number: 11916754
    Abstract: Methods, systems, and devices for wireless communications are described. In some examples, a wireless communications system may support machine learning and may configure a user equipment (UE) for machine learning. The UE may transmit, to a base station, a request message that includes an indication of a machine learning model or a neural network function based at least in part on a trigger event. In response to the request message, the base station may transmit a machine learning model, a set of parameters corresponding to the machine learning model, or a configuration corresponding to a neural network function and may transmit an activation message to the UE to implement the machine learning model and the neural network function.
    Type: Grant
    Filed: September 3, 2021
    Date of Patent: February 27, 2024
    Assignee: QUALCOMM Incorporated
    Inventors: Xipeng Zhu, Gavin Bernard Horn, Vanitha Aravamudhan Kumar, Vishal Dalmiya, Shankar Krishnan, Rajeev Kumar, Taesang Yoo, Eren Balevi, Aziz Gholmieh, Rajat Prakash
  • Patent number: 11907817
    Abstract: A simulation test is run on a first machine learning model trained using first training data historically collected over a time period. The first training data includes a set of training inputs and a set of target outputs. In response to a determination that a result of the simulation test run on the first machine learning model satisfies one or more criteria, a size of the set of target outputs of the first training data is determined. Second training data for training a second machine learning model is obtained. A size of a set of target outputs of the second training data meets or exceeds the size of the target outputs of the first training data. The second machine learning model is trained using the second training data.
    Type: Grant
    Filed: December 5, 2022
    Date of Patent: February 20, 2024
    Assignee: Google LLC
    Inventors: Chetan Pitambar Bhole, Tanmay Khirwadkar, Sourabh Prakash Bansod, Sanjay Mangla, Deepak Ramamurthi Sivaramapuram Chandrasekaran
  • Patent number: 11899763
    Abstract: Systems are provided for improving computer security systems that are based on user risk scores. These systems can be used to improve both the accuracy and usability of the user risk scores by applying multiple tiers of machine learning to different the user risk profile components used to generate the user risk scores and in such a manner as to dynamically generate and modify the corresponding user risk scores.
    Type: Grant
    Filed: October 19, 2018
    Date of Patent: February 13, 2024
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Sayed Hassan Abdelaziz, Maria Puertas Calvo, Laurentiu Bogdan Cristofor, Rajat Luthra