Microsoft Technology Licensing, LLC patent applications on January 2nd, 2025
Patent Applications by Microsoft Technology Licensing, LLC on January 2nd, 2025
Microsoft Technology Licensing, LLC: 44 patent applications
Microsoft Technology Licensing, LLC has applied for patents in the areas of G06N20/00 (6), G06F11/36 (3), G06F21/57 (2), G06F16/335 (2), G06F21/62 (2) G06N20/00 (4), G06F21/577 (2), G06F11/3688 (2), G06F1/26 (1), H01L21/02178 (1)
With keywords such as: user, data, based, search, node, systems, destination, input, query, and video in patent application abstracts.
Patent Applications by Microsoft Technology Licensing, LLC
Inventor(s): Ann Hampton THOMAS of Raleigh NC (US) for microsoft technology licensing, llc, Richard Gerard HOFMANN of Cary NC (US) for microsoft technology licensing, llc, Thomas BASNIGHT of Raleigh NC (US) for microsoft technology licensing, llc, Mohammed A. EL-TANANI of Hillsboro OR (US) for microsoft technology licensing, llc
IPC Code(s): G06F1/26
CPC Code(s): G06F1/26
Abstract: aggregation circuits provided in each of the nodes of an ic chip are employed to, based on indications of power consumption in an aggregation zone of the ic chip, reduce power consumption in the nodes in the aggregation zone to mitigate voltage droop. each aggregation zone includes a first node that receives indications of power consumption associated with the first node and indications of power consumption associated with other nodes in the aggregation zone. the first node generates a control signal based on the received indications, and each of the plurality of nodes in the aggregation zone reduces power consumption based on the control signal. in some examples, the aggregation circuit in any node may be configured to operate in a first mode as the first node or in a second mode as one of the second nodes, providing flexibility in the configuration of aggregation zones.
Inventor(s): Taylor Alexis GUERRA of Seattle WA (US) for microsoft technology licensing, llc, Lia JOHANSEN of Kirkland WA (US) for microsoft technology licensing, llc, Kyle Matthew MILLER of Lynnwood WA (US) for microsoft technology licensing, llc, Jianjun YAN of Beijing (CN) for microsoft technology licensing, llc, Yu HE of Beijing (CN) for microsoft technology licensing, llc, Yang HUANGFU of Suzhou (CN) for microsoft technology licensing, llc
IPC Code(s): G06F3/0482, G06F9/451
CPC Code(s): G06F3/0482
Abstract: systems and methods for generating dynamic quick actions for an application in a web browser. the dynamic quick actions correspond to various functions of an application accessible via a web browser sidebar interface. when a hover event is detected in association with an icon of the application, a quick-actions card is generated that includes quick actions of the application from which the user can select. for instance, a selection of a quick action triggers the web browser to execute an action that causes the application function to be performed. thus, application functions are able to be surfaced and controlled via a single input device selection (e.g., a mouse click).
Inventor(s): Bryan D. KELLY of Carnation WA (US) for microsoft technology licensing, llc, Neeraj LADKANI of Bothell WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F9/445
CPC Code(s): G06F9/44505
Abstract: methods, systems, apparatuses, and computer-readable storage mediums described herein are configured to dynamically configure a baseboard management controller to monitor a state of a server. for example, a configuration schema may be provided to the baseboard management controller. the configuration schema specifies each of the devices of the server that is to be monitored by the baseboard management controller. the configuration schema also specifies additional configuration details with respect to each of the devices. based on the configuration information included in the configuration schema, the baseboard management controller performs a discovery sequence with respect to each of the devices to verify that such devices are communicatively coupled to the baseboard management controller. if the discovery sequence is successful, the baseboard management controller begins monitoring the devices. however, if the discovery sequence is unsuccessful, the baseboard management controller issues an error, thereby enabling the proper personnel to remediate the issue.
Inventor(s): Gerald Roy DE GRACE of Atlanta GA (US) for microsoft technology licensing, llc, Srikanth KANDULA of Redmond WA (US) for microsoft technology licensing, llc, Avijit GUPTA of Redmond WA (US) for microsoft technology licensing, llc, Rishabh TEWARI of Sammamish WA (US) for microsoft technology licensing, llc, Arun JEEDIGUNTA VENKATA SATYA of Seattle WA (US) for microsoft technology licensing, llc, Zexuan ZHAO of Bellevue WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F9/455
CPC Code(s): G06F9/45558
Abstract: techniques are disclosed for managing connections or bidirectional flows of a communication session in a software defined network (sdn). a virtual machine determines that the communication session meets a criterion for offloading policy enforcement of the communication session to an acceleration device. the virtual machine sends to the connection processing engine, a request to offload policy enforcement of the communication session from the virtual machine to the acceleration device.
Inventor(s): Shekhar AGRAWAL of Kirkland WA (US) for microsoft technology licensing, llc, Abhay Sudhir KETKAR of Redmond WA (US) for microsoft technology licensing, llc, Gaurav JAGTIANI of Kirkland WA (US) for microsoft technology licensing, llc, Binit Ranjan MISHRA of Kenmore WA (US) for microsoft technology licensing, llc, Emma Sutherland BOYD of Richmond VA (US) for microsoft technology licensing, llc, Scott Chao-Chueh LEE of Bellevue WA (US) for microsoft technology licensing, llc, James Anthony SCHWARTZ, JR. of Seattle WA (US) for microsoft technology licensing, llc, Hari R. PULAPAKA of Redmond WA (US) for microsoft technology licensing, llc, Karan MEHRA of Sammamish WA (US) for microsoft technology licensing, llc, Shailesh Padmakar JOSHI of Hyderabad, Telangana (IN) for microsoft technology licensing, llc, Jason Stewart WOHLGEMUTH of Seattle WA (US) for microsoft technology licensing, llc, David WIMMEL of Cincinnati OH (US) for microsoft technology licensing, llc
IPC Code(s): G06F11/14
CPC Code(s): G06F11/1415
Abstract: a computer system identifies an event from a management system log associated with a first container host. the presence of the event in the management system log is indicative that the first container host identified a fatal system error at the first container host. based on the event, the computer system determines that a first instance of a container that is provisioned at the first container host has been isolated to the first container host. based on the first instance of the container having been isolated to the first container host, the computer system instructs a second container host to provision a second instance of the container at the second container host.
Inventor(s): William Tigard BAKER of Redmond WA (US) for microsoft technology licensing, llc, Swamy V. P. L. N. NALLAMALLI of Bothell WA (US) for microsoft technology licensing, llc, Dallas Allen WARREN of Redmond WA (US) for microsoft technology licensing, llc, Piyush GUPTA of Sammamish WA (US) for microsoft technology licensing, llc, Aaron Edward DIETRICH of Kirkland WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F11/36, G06F16/33
CPC Code(s): G06F11/3612
Abstract: aspects of the disclosure include methods and systems for performing automated software testing. the method can include executing software under test and determining that the user interface of the software includes a textual input field. the method includes identifying a label of the textual input field, inputting into a natural language processing system the label as a query and receiving, from the natural language processing system in response to the query, a first input text. the method also includes inputting the first input text into the textual input field and recording a first response of the software to the first input text.
Inventor(s): COLIN BRUCE CLEMENT of SEATTLE WA (US) for microsoft technology licensing, llc., DAVID ALBERTO NADER PALACIO of WILLIAMSBURG VA (US) for microsoft technology licensing, llc., NEELAKANTAN SUNDARESAN of BELLEVUE WA (US) for microsoft technology licensing, llc., ALEXEY SVYATKOVSKIY of BELLEVUE WA (US) for microsoft technology licensing, llc., MICHELE TUFANO of BELLEVUE WA (US) for microsoft technology licensing, llc.
IPC Code(s): G06F11/36
CPC Code(s): G06F11/3636
Abstract: a debugging tool identifies the smallest subset of an input sequence or rationales that influenced a neural language model to generate an output sequence. the debugging tool uses the rationales to understand why the model made its predictions and in particular, the particular input tokens that had the most impact on the output sequence. in the case of erroneous output, the rationales are used to alter the input sequence to avoid the error or to tailor a new training dataset to retrain the model to improve its performance.
Inventor(s): William Tigard BAKER of Redmond WA (US) for microsoft technology licensing, llc, Swamy V. P. L. N. NALLAMALLI of Bothell WA (US) for microsoft technology licensing, llc, Dallas Allen WARREN of Redmond WA (US) for microsoft technology licensing, llc, Piyush GUPTA of Sammamish WA (US) for microsoft technology licensing, llc, Aaron Edward DIETRICH of Kirkland WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F11/36
CPC Code(s): G06F11/3688
Abstract: aspects of the disclosure include methods and systems for performing automated software testing. the method includes obtaining a test script for software, executing the test script, and determining that the test script includes an action that cannot be completed. the method also includes identifying elements of a user interface of the software, inputting, into a natural language processing system, a query including the action and the elements, and receiving, in response to the query, an identified element. the method further includes continuing the executing of the software by performing the action on the identified element and determining that an updated user interface includes an element associated with the action of the test script. the method also includes updating the test script by adding a new action to the test script based on a determination that the updated user interface includes the element associated with the action.
Inventor(s): Vikram D. Gaitonde of Sunnyvale CA (US) for microsoft technology licensing, llc, Peter Michael Humke of Pearland TX (US) for microsoft technology licensing, llc, Michael E. Pascual of Santa Clara CA (US) for microsoft technology licensing, llc, Smriti R. Ramakrishnan of Belmont CA (US) for microsoft technology licensing, llc, Ajith Muralidharan of Sunnyvale CA (US) for microsoft technology licensing, llc, Yao Pan of Mountain View CA (US) for microsoft technology licensing, llc, Lingjie Weng of Sunnyvale CA (US) for microsoft technology licensing, llc, Keren Wang of Santa Clara CA (US) for microsoft technology licensing, llc, Anjian Wu of Newark CA (US) for microsoft technology licensing, llc, Daniel Chi Peng Lau of San Francisco CA (US) for microsoft technology licensing, llc
IPC Code(s): G06F11/36
CPC Code(s): G06F11/3688
Abstract: systems and methods are directed to providing multilevel chained testing. a modeling manager receives a request for data associated with an experience having multiple levels of testing, whereby each lower level of testing has a set of one or more variants chained to a variant of a higher level. based on the request, the model manager determines which variant of the multiple levels of testing to provide to a user. the determining comprises detecting a lowest segment the user is a member of, whereby each segment level corresponds to a level of testing, and selecting a variant from a corresponding set of one or more variants of the lowest sub-segment, a chained variant of a parent segment, or a control value. the modeling manager transmits a response to an experience component that includes the selected variant, and the experience component causes presentation of the experience with the selected variant.
Inventor(s): Omar CAREY of () for microsoft technology licensing, llc, Rajsekhar DAS of Sammamish WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F16/185
CPC Code(s): G06F16/185
Abstract: a processing system dynamically adjusts the size of root nodes in hierarchical data structures, such as b+ trees. upon creation, a root node has a predefined initial size. when a request is received to insert a new record, a determination is made as to whether the size of the root node has reached a predefined maximum size. if the root node has not reached the predefined maximum size, the size of the root node is increased to accommodate the new record and the new record is added to the root node. if the root node has reached the predefined maximum size, one or more new child nodes are created, and records are moved from the root node to the new child nodes. the size of the root node is then reduced to a predefined minimum size.
Inventor(s): Muwu Hou of San Jose CA (US) for microsoft technology licensing, llc, Xiuyuan Li of Milpitas CA (US) for microsoft technology licensing, llc, Farhan Rohan Toddywala of Jersey City NJ (US) for microsoft technology licensing, llc, Yue Ying of San Jose CA (US) for microsoft technology licensing, llc, Choong Soon Chang of Palo Alto CA (US) for microsoft technology licensing, llc
IPC Code(s): G06F16/31, G06F16/2455, G06F16/332, G06F16/335
CPC Code(s): G06F16/328
Abstract: techniques for implementing a hybrid search for documents having a parent-child relationship are disclosed. in some embodiments, a computer-implemented method comprises: building a base index using a first table of parent documents and a second table of child documents, the base index storing document identifiers of the parent and child documents in contiguous document blocks, where each document block stores the document identifier of a parent documents and the document identifier of each one of the child documents that is related to the parent document in a sorted order; subsequent to the building of the base index, updating a live index to include document identifiers of additional parent documents that have been added the first table and document identifiers of additional child documents that have been added to the second table; and computing a hybrid set of search results for a search query using the base index and the live index.
Inventor(s): Aparna Krishnan of San Jose CA (US) for microsoft technology licensing, llc, Christopher Wright Lloyd, II of Brooklyn NY (US) for microsoft technology licensing, llc, Jeremy K. Owen of Mountain View CA (US) for microsoft technology licensing, llc, Christopher J. Fong of San Mateo CA (US) for microsoft technology licensing, llc, Suman Sundaresh of Los Altos CA (US) for microsoft technology licensing, llc, Lavish Shah of New York NY (US) for microsoft technology licensing, llc, Muhammad Basit Khurram of Bellevue WA (US) for microsoft technology licensing, llc, Michaela Jillings of Seattle WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F16/332, G06F16/33, G06F16/338
CPC Code(s): G06F16/3329
Abstract: embodiments of the disclosed technologies include generating a search prompt based on an input portion of an online dialog involving a user of a computing device. the search prompt includes a dialog summarization instruction configured to instruct a generative artificial intelligence model to generate and output a dialog summary. the search prompt is sent to a first generative model. in response to the search prompt, a search query is generated and output by the first generative model based on the dialog summary. the search query is sent to a search system. search result data is determined based on an execution of the search query by the search system. at least some of the search result data is included in an output portion of the online dialog. the output portion is configured to be displayed at the computing device in response to the input portion of the online dialog.
Inventor(s): Scott COUNTS of Redmond WA (US) for microsoft technology licensing, llc, Roberta R. MOEUR of Redmond WA (US) for microsoft technology licensing, llc, Curtis N. von VEH of Redmond WA (US) for microsoft technology licensing, llc, Justin Brooks CRANSHAW of Seattle WA (US) for microsoft technology licensing, llc, Stevie Nicole CHANCELLOR of Atlanta GA (US) for microsoft technology licensing, llc, Anthony CARBARY of Redmond WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F16/35, G06F3/0481, G06F16/335, G06F16/9537, G06F18/2431, G06F40/211, G06N20/10
CPC Code(s): G06F16/358
Abstract: a user interface (ui) for visualizing search data provides techniques for grouping and organizing aggregate data that shows the categories of topics included in search queries from a large number of individual users. raw search queries are categorized into one of a number of topical categories. the search queries are assigned to a geographic location based on geolocations of computing devices generating the search queries. the ui presents a map that shows the number of search queries per topical category for each geographic location displayed in the current ui view. as a result of this ui design, a user can easily understand the interaction between geographic location and frequency of search query topics. trends in the geographic distribution of searches and in the categories of topics searched are also easily understood from this ui design by changing the time range of the search queries displayed.
Inventor(s): Elizabeth Picchietti SALOWITZ of Kirkland WA (US) for microsoft technology licensing, llc, David Ben PERRY of Redmond WA (US) for microsoft technology licensing, llc, Carlos A.C. PESSOA of Redmond WA (US) for microsoft technology licensing, llc, Vivek PRADEEP of Bellevue WA (US) for microsoft technology licensing, llc, Sharath VISWANATHAN of Seattle WA (US) for microsoft technology licensing, llc, Nathan James LUQUETTA-FISH of San Francisco CA (US) for microsoft technology licensing, llc, Steven BATHICHE of Redmond WA (US) for microsoft technology licensing, llc, Eric Chris Wolfgang SOMMERLADE of Oxford (GB) for microsoft technology licensing, llc, Jose Antonio LARA SILVA of Seattle WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F16/44, G06F16/438
CPC Code(s): G06F16/447
Abstract: machine learning techniques are leveraged to provide personalized assistance on a computing device. in some configurations a timeline of a user's interactions with the computing device is generated. for example, screenshots and audio streams may be saved as entries in the timeline. contextâthe state of the computing device when the entry is created, such as which documents and websites are openâis also stored. entries in the timeline are processed by a model to generate embedding vectors. the timeline may be searched by finding the embedding vector that is closest to an embedding vector derived from a search query. the user may select a query result, causing the associated context to be restored. for example, if the query is âshow me all documents related to my upcoming trip to japanâ, the query result may open documents and websites that were open when booking a flight to japan.
Inventor(s): Chandrasekhar Subramanya AKKIRAJU VENKATA of Woodinville WA (US) for microsoft technology licensing, llc, Rakesh CHAKARI MALLAREPPA of Bothell WA (US) for microsoft technology licensing, llc, Rohit SHARMA of Issaquah WA (US) for microsoft technology licensing, llc, Joel RAMOS-MUNOZ of Redmond WA (US) for microsoft technology licensing, llc, Bo WANG of Kirkland WA (US) for microsoft technology licensing, llc, Kailun QIAN of Kirkland WA (US) for microsoft technology licensing, llc, Kishore SERALATHAN of Bothell WA (US) for microsoft technology licensing, llc, Anick SAHA of Bellevue WA (US) for microsoft technology licensing, llc, Luana Martins DOS SANTOS of SĂŁo Paulo (BR) for microsoft technology licensing, llc, Venkata Surya Lakshmi Jogi Raju VEGIRAJU of Redmond WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F16/951, G06F16/953
CPC Code(s): G06F16/951
Abstract: systems and methods are provided for implementing a universal search indexer for enterprise and cloud accessible websites. a universal search indexer, using a crawling agent, crawls a target website and/or web documents in the target website, which includes a plurality of webpages including at least one of one or more static webpages or one or more dynamic webpages. the universal search indexer extracts website content and/or web documents as the target website is being crawled, and ingests the extracted website content and/or web documents within a data store, by indexing the extracted website content and/or web documents in a search index of the data store. the extracted website content and/or web documents are indexed to be searchable and refinable using a search engine, the extracted website content and/or web documents being retrievable via the search engine.
Inventor(s): Ayan Acharya of Santa Clara CA (US) for microsoft technology licensing, llc, Siyuan Gao of San Mateo CA (US) for microsoft technology licensing, llc, Kinjal Basu of Stanford CA (US) for microsoft technology licensing, llc, Ankan Saha of San Francisco CA (US) for microsoft technology licensing, llc, Sathiya K. Selvaraj of Sunnyvale CA (US) for microsoft technology licensing, llc, Parag Agrawal of Mountain View CA (US) for microsoft technology licensing, llc, Borja Ocejo Elizondo of Chicago IL (US) for microsoft technology licensing, llc, Aman Gupta of San Jose CA (US) for microsoft technology licensing, llc, Rahul Mazumder of Sommerville MA (US) for microsoft technology licensing, llc
IPC Code(s): G06F16/9536, G06Q50/00
CPC Code(s): G06F16/9536
Abstract: a method may comprise, for each one of a plurality of destination users, computing a score using a first function based on a probability of a source user performing a source action directed towards the destination user, a second function based on a probability of the destination user performing a destination action in response to the source action, and a third function based on a measure of interaction by the destination user with an online service to result from the destination action being performed by the destination user. the score for inactive users may be boosted using an optimization algorithm with a first constraint comprising a maximum threshold number of the inactive users to display as recommendations to the source user and a second constraint comprising a minimum threshold number of the inactive users for which the source user to perform the source action.
20250005136. ENCLAVE CLONING_simplified_abstract_(microsoft technology licensing, llc)
Inventor(s): Alexander SHAMIS of Cambridge (GB) for microsoft technology licensing, llc, Yoshimichi NAKATSUKA of Irvine CA (US) for microsoft technology licensing, llc, Peter Robert PIETZUCH of Cambridge (GB) for microsoft technology licensing, llc, Andrew James PAVERD of Cambridge (GB) for microsoft technology licensing, llc, Ercan OZTURK of Irvine CA (US) for microsoft technology licensing, llc
IPC Code(s): G06F21/53
CPC Code(s): G06F21/53
Abstract: a source enclave of a source application includes: at least one process thread; a respective at least one process stack memory; a heap memory; and a thread context area. an interrupt is sent to the source enclave which causes the process thread to exit. a migrator thread is sent to the source enclave to save to an external memory, using a migrator stack memory, the thread context area, the at least one process stack memory, and the heap memory, but not the migrator stack memory. a destination enclave is instantiated at a destination application. an initiator thread is sent to the destination enclave to clone, using an initiator stack memory, the state of the source enclave from the external memory.
Inventor(s): Andrey KARPOVSKY of Kiryat Motzkin (IL) for microsoft technology licensing, llc, Michael MAKHLEVICH of Sderot (IL) for microsoft technology licensing, llc, Tomer ROTSTEIN of Haifa (IL) for microsoft technology licensing, llc
IPC Code(s): G06F21/56, G06F21/62
CPC Code(s): G06F21/566
Abstract: the detection and alerting on malicious queries that are directed towards a data store. the detection is done by using syntax metrics of the query. this can be done without evaluating (or at least without retaining) the unmasked query. in order to detect a potentially malicious query, syntax metric(s) of that query are accessed. the syntax metric(s) are then fed into a model that is configured to predict maliciousness of the query based on the one or more syntax metrics. the output of the model then represents a prediction of maliciousness of the query. based on the output of the model representing the predicted maliciousness, a computing entity associated with the data store is then alerted.
Inventor(s): William Tigard BAKER of Redmond WA (US) for microsoft technology licensing, llc, Dallas Allen WARREN of Redmond WA (US) for microsoft technology licensing, llc, Aaron Edward DIETRICH of Kirkland WA (US) for microsoft technology licensing, llc, Piyush GUPTA of Sammamish WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F21/57
CPC Code(s): G06F21/577
Abstract: aspects of the disclosure include methods and systems for performing automated software testing using chaos engineering. an exemplary method can include obtaining a plurality of fault scenarios and executing a test script on software under test during application of each of the plurality of fault scenarios, wherein the test script simulates the execution of a function of the software under test. the method also includes recording, for each of the plurality of fault scenarios, telemetry data regarding the execution of the function of the software under test and identifying a vulnerability of the software under test based on the recorded telemetry data.
Inventor(s): Gustavo Kenneth CONTRERAS MUNOZ of Westborough MA (US) for microsoft technology licensing, llc, Connor William SHUGG of Chapel Hill NC (US) for microsoft technology licensing, llc, Aidan Dexter MAYCOCK of Durham NC (US) for microsoft technology licensing, llc, Oleksii OLEKSENKO of Cambridge (GB) for microsoft technology licensing, llc, Boris Alexander KOEPF of Cambridge (GB) for microsoft technology licensing, llc
IPC Code(s): G06F21/57, G06F21/56
CPC Code(s): G06F21/577
Abstract: embodiments of systems and methods utilizing hardware models to detect side-channel vulnerabilities in processor designs are disclosed. programs and inputs are tested in an instruction set simulator. implementing the processor design in the instruction set simulator generates contract traces. a hardware simulator is implemented of the processor design. implementing the hardware simulator results in hardware traces that indicate the data and execution are observable as a result of the hardware simulation. if the data and execution indicated by any of the hardware traces is not the same as that the data and execution indicated by at least one of the contract traces, a side-channel vulnerability is detected. since the side-channel vulnerability was detected using a hardware simulation, an actual physical processor with the hardware design does not have to be used to test the hardware for the processor design.
Inventor(s): Jordi MOLA of Bellevue WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F21/62, G06F11/34
CPC Code(s): G06F21/62
Abstract: using entropy to prevent inclusion of payload data in code execution log data. embodiments determine that a payload data item associated with code execution log data has entropy exceeding a defined entropy threshold and identify a particular executable code that interacted with the payload data item. embodiments then take a preventative action that excludes the payload data item from inclusion with a record of execution of the particular executable code. examples of preventative actions include preventing the payload data item from being exported from the computer system, preventing the payload data item from being included in the code execution log data, and adding the payload data item to a block list in reference to the particular executable code.
Inventor(s): Xavier Amatriain-Rubio of Los Gatos CA (US) for microsoft technology licensing, llc, Christopher M. Bremer of Santa Barbara CA (US) for microsoft technology licensing, llc, Carlos H. Lopez of Westfield NJ (US) for microsoft technology licensing, llc, Pierre Y. Monestie of Half Moon Bay CA (US) for microsoft technology licensing, llc, Laura Teclemariam of Hayward CA (US) for microsoft technology licensing, llc, Yamini Kasera of San Francisco CA (US) for microsoft technology licensing, llc, Michaeel Kazi of Foster City CA (US) for microsoft technology licensing, llc, Zhoutong Fu of Milpitas CA (US) for microsoft technology licensing, llc, Muchen Wu of Mountain View CA (US) for microsoft technology licensing, llc, Winnie Narang of San Carlos CA (US) for microsoft technology licensing, llc, Yiyuan Tu of Milpitas CA (US) for microsoft technology licensing, llc, Jaime Munoz Alcalde of Brooklyn NY (US) for microsoft technology licensing, llc, Nitin Pasumarthy of Sunnyvale CA (US) for microsoft technology licensing, llc, Thao Bach of Mountain View CA (US) for microsoft technology licensing, llc, David Williams of Seattle WA (US) for microsoft technology licensing, llc, Priyanka Gariba of San Francisco CA (US) for microsoft technology licensing, llc
IPC Code(s): G06F40/35, G06F9/445
CPC Code(s): G06F40/35
Abstract: embodiments of the disclosed technologies include generating a first thread classification prompt based on a first thread portion of an online dialog involving a user of a computing device, sending the first thread classification prompt to a first large language model, receiving a first thread classification generated and output by the first large language model based on the first thread classification prompt, formulating a plan execution prompt based on the first thread classification, sending the plan execution prompt to a second large language model, receiving a second thread portion generated and output by the second large language model based on the plan execution prompt and the online dialog, and generating a label for a third thread portion of the online dialog.
Inventor(s): Poonam Ganesh HATTANGADY of Seattle WA (US) for microsoft technology licensing, llc, Michael Ivan BORYSENKO of Brighton (CA) for microsoft technology licensing, llc, Alexander Ian Pfister TRZYNA of Seattle WA (US) for microsoft technology licensing, llc
IPC Code(s): G06F40/40, G06F40/103, G06F40/166, G06F40/30
CPC Code(s): G06F40/40
Abstract: systems and methods for generating advanced feedback for draft messages using a language model are disclosed. prior messages, along with corresponding reactions, may be incorporated into an ai prompt that is processed by a language model to generate an output payload. the output payload is processed to generate custom profiles for users that have provided the reactions to the messages. at runtime, while a draft message is being composed within a messaging application, the data from the draft message (and message thread where applicable) are received. the custom profiles for recipients of the draft message are then retrieved from the database of custom profiles. the data from the draft message as well as the retrieved custom profiles are incorporated into another ai prompt that is processed by the language model to produce another output payload. the output payload is post-processed to extract advanced feedback for the draft message.
Inventor(s): Jinyu LI of Redmond WA (US) for microsoft technology licensing, llc, Liang LU of Redmond WA (US) for microsoft technology licensing, llc, Changliang LIU of Bothell WA (US) for microsoft technology licensing, llc, Yifan GONG of Sammamish WA (US) for microsoft technology licensing, llc
IPC Code(s): G06N3/048, G06F18/21, G06N3/08, G06N20/00, G10L15/06, G10L15/16
CPC Code(s): G06N3/048
Abstract: representative embodiments disclose machine learning classifiers used in scenarios such as speech recognition, image captioning, machine translation, or other sequence-to-sequence embodiments. the machine learning classifiers have a plurality of time layers, each layer having a time processing block and a depth processing block. the time processing block is a recurrent neural network such as a long short term memory (lstm) network. the depth processing blocks can be an lstm network, a gated deep neural network (dnn) or a maxout dnn. the depth processing blocks account for the hidden states of each time layer and uses summarized layer information for final input signal feature classification. an attention layer can also be used between the top depth processing block and the output layer.
Inventor(s): Chun Lo of Mountain View CA (US) for microsoft technology licensing, llc, Lu Chen of Sunnyvale CA (US) for microsoft technology licensing, llc, Ajith Muralidharan of Sunnyvale CA (US) for microsoft technology licensing, llc, Lingjie Weng of Sunnyvale CA (US) for microsoft technology licensing, llc, Mohan Premchand Bhambhani of Sunnyvale CA (US) for microsoft technology licensing, llc, Zichu Li of San Jose CA (US) for microsoft technology licensing, llc
IPC Code(s): G06N3/08, H04L67/1396, H04L67/50
CPC Code(s): G06N3/08
Abstract: in an example embodiment, a user's session sequence data is utilized to provide a universal member representation that achieves one or more of the following goals:
Inventor(s): Yang WANG of Beijing (CN) for microsoft technology licensing, llc, Ting CAO of Beijing (CN) for microsoft technology licensing, llc, Li ZHANG of Beijing (CN) for microsoft technology licensing, llc, Qi CHEN of Beijing (CN) for microsoft technology licensing, llc, Mao YANG of Beijing (CN) for microsoft technology licensing, llc
IPC Code(s): G06N3/084, G06N3/047
CPC Code(s): G06N3/084
Abstract: according to implementations of the subject matter described herein, a solution for neural network inference based on table lookup is provided. according to this solution, respective centroids in a first plurality of codebooks for a first layer of a neural network are determined along with a first weight matrix through a training procedure of the neural network. a first input for the first layer is divided into a first plurality of input sub-vectors, and target centroids are determined for the input sub-vectors based on respective distances between the input sub-vectors and the centroids. target computation results of the target centroids with the first weight matrix are selected from a lookup table. a first output for the first layer is determined based on aggregation of the target computation results. in this way, better model accuracy can be achieved while leveraging the computation acceleration in table lookup-based model inference.
Inventor(s): Daniela ALEXANDER of Bellevue WA (US) for microsoft technology licensing, llc, Ahsanul HAQUE of Bellevue WA (US) for microsoft technology licensing, llc, Rajesh Shashikant KORDE of Sammamish WA (US) for microsoft technology licensing, llc, Minglei HUANG of Bothell WA (US) for microsoft technology licensing, llc, Rui ZHU of Sammamish WA (US) for microsoft technology licensing, llc
IPC Code(s): G06N5/04, G06N20/00
CPC Code(s): G06N5/04
Abstract: methods and systems are provided for determining the category of a software application utilizing machine learning (ml) and knowledge graph techniques, and for controlling access to the application by a user based on the category and configured time restrictions for the user. the system includes a feature set extractor and a category predictor with a trained ml model. the trained ml model generates the category of the application based on a feature(s) of the application. the generated category is indicated in a data structure. an access request handler receives a request related to access to the application from a user device. a category determiner determines the category of the application from the data structure. a time usage manager determines an available time usage for the category and the specified user. the access arbiter responds to the request from the user device with the available time usage.
Inventor(s): Vikram Gaitonde of Sunnyvale CA (US) for microsoft technology licensing, llc, Peter Michael Humke of Pearland TX (US) for microsoft technology licensing, llc, Michael E. Pascual of Santa Clara CA (US) for microsoft technology licensing, llc, Smriti R. Ramakrishnan of Belmont CA (US) for microsoft technology licensing, llc, Ajith Muralidharan of Sunnyvale CA (US) for microsoft technology licensing, llc, Yao Pan of Mountain View CA (US) for microsoft technology licensing, llc, Lingjie Weng of Sunnyvale CA (US) for microsoft technology licensing, llc, Keren Wang of Santa Clara CA (US) for microsoft technology licensing, llc, Anjian Wu of Newark CA (US) for microsoft technology licensing, llc, Daniel Chi Peng Lau of San Francisco CA (US) for microsoft technology licensing, llc
IPC Code(s): G06N20/00, G06F9/451
CPC Code(s): G06N20/00
Abstract: methods, systems, and computer programs are presented for implementing an artificial-intelligence modeling utility system. one method includes receiving, by a modeling manager, a schema from an experience module that implements features of an online service. the modeling manager manages a plurality of machine-learning (ml) models, provides a user interface (ui) based on the schema for entering experiment parameter values, and configures one or more ml models for the experiment. the experiment is initialized, and during the experiment, the modeling manager receives a request from the experience module for data associated with the experiment and selects one of the configured ml models for providing a response to the request. the response is obtained from the selected ml model based on input provided to the ml model based on the request, and the modeling manager sends the response to the experience. further, results of the experiment are presented.
Inventor(s): Lijun Peng of Sunnyvale CA (US) for microsoft technology licensing, llc, Yi Zhang of Sunnyvale CA (US) for microsoft technology licensing, llc, Mindaou Gu of Sunnyvale CA (US) for microsoft technology licensing, llc, Yingxia Shi of Sunnyvale CA (US) for microsoft technology licensing, llc
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: in an example embodiment, a solution is provided that enables end-to-end automation across many different components in an online network. end-to-end optimization is a machine learning approach where the entire system, from input to output, is optimized as a whole, without breaking it down into separate components. in other words, the optimization is performed over the entire pipeline of the system, rather than optimizing each component separately.
Inventor(s): Zhiyun Ren of Cupertino CA (US) for microsoft technology licensing, llc, Padmini Jaikumar of Los Altos CA (US) for microsoft technology licensing, llc
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: an extended two tower network is used to make both a recommendation of a content item that a given user may be interested in, and a recommendation of a user that may be interested in a given content item. the extended two tower network includes a content item sub-tower, a user sub-tower, and a fusion sub-model that are jointly trained to predict a probability that a given user is interested in a given content item. the content item sub-tower and the user sub-tower are used to make an initial prediction that the given user will be interested in the given content item. the initial prediction is then input to the fusion sub-model to make a final prediction. in the case of a candidate invitee recommendation, the initial prediction may be combined with one or more interaction features and the combination input to the fusion sub-model to make the final prediction.
Inventor(s): Ryota TOMIOKA of Cambridge (GB) for microsoft technology licensing, llc, Juliana PatrĂcia VICENTE FRANCO of Cambridge (GB) for microsoft technology licensing, llc, Alberto MAGNI of Cambridge (GB) for microsoft technology licensing, llc, Nuno CLAUDINO PEREIRA LOPES of Cambridge (GB) for microsoft technology licensing, llc, Siddharth KRISHNA of Cambridge (GB) for microsoft technology licensing, llc, Renato GOLIN of Cambridge (GB) for microsoft technology licensing, llc
IPC Code(s): G06N20/00, G06F9/38
CPC Code(s): G06N20/00
Abstract: a computation graph of a machine learning model is accessed from memory and a constraint solver is used to compute a partition of the computation graph into ordered stages of an execution pipeline. in use, when inference or training of the machine learning model takes place by executing the pipeline, execution cost of the stages are balanced according to the computed partition.
Inventor(s): Hong XUAN of Bellevue WA (US) for microsoft technology licensing, llc, Li HUANG of Sammamish WA (US) for microsoft technology licensing, llc, Huangxing LI of Bellevue WA (US) for microsoft technology licensing, llc, Xi CHEN of Issaquah WA (US) for microsoft technology licensing, llc
IPC Code(s): G06T11/60, G06F16/532, G06F16/535, G06T7/13, G06T7/73
CPC Code(s): G06T11/60
Abstract: aspects of the disclosure include methods and systems for leveraging a controllable diffusion model for dynamic image search in an image gallery recommendation service. an exemplary method can include displaying an image gallery having a plurality of gallery images and a dynamic image frame. the dynamic image frame can include a generated image and an interactive widget. the method can include receiving a user input in the interactive widget and generating, responsive to receiving the user input, an updated generated image by inputting, into a controllable diffusion model, the user input. the method can include replacing the generated image in the dynamic image frame with the updated generated image.
Inventor(s): Lili QIU of Shanghai (CN) for microsoft technology licensing, llc, Hao PAN of Shanghai (CN) for microsoft technology licensing, llc, Ruichun MA of Gaoyou (CN) for microsoft technology licensing, llc, Shicheng ZHENG of Shanghai (CN) for microsoft technology licensing, llc
IPC Code(s): G06T17/00
CPC Code(s): G06T17/00
Abstract: a method of designing a passive metasurface system within an environment includes receiving a three-dimensional model of the environment including one or more transmitter locations and one or more target locations, and determining one or more metasurface designs and placements to achieve a given objective. the method may also include computing a received signal strength at the one or more target locations based on the three-dimensional model of the environment, computing the received signal strength at the one or more target locations based on the three-dimensional model of the environment and the one or more metasurface designs and placements, and/or calculating ray traces and/or using machine learning to determine the received signal strength at the one or more target locations on the three-dimensional model of the environment and the one or more metasurface designs and placements.
Inventor(s): Haoxuan LI of Beijing (CN) for microsoft technology licensing, llc, Rui JIANG of Beijing (CN) for microsoft technology licensing, llc, Yang LIU of Beijing (CN) for microsoft technology licensing, llc, Edward C LIN of Beijing (CN) for microsoft technology licensing, llc, Lei SUN of Beijing (CN) for microsoft technology licensing, llc, Che ZHAO of Beijing (CN) for microsoft technology licensing, llc
IPC Code(s): G10L15/01, G10L15/06, G10L15/19
CPC Code(s): G10L15/01
Abstract: systems and methods are provided for identifying targeted datasets that are configured to facilitate an improvement in the accuracy of an acoustic model included in the automatic speech recognition system. systems obtain a obtain a test dataset comprising (i) audio data having natural speech utterances and (ii) a transcription of the natural speech utterances. systems generate a text-to-speech dataset comprising audio data having synthesized speech utterances based on the transcription of the natural speech utterances. systems apply the test dataset and the text-to-speech dataset to the acoustic model to obtain a first acoustic model output and a second acoustic model output, respectively. systems identify a first set of errors in the first acoustic model output and a second set of errors in the second acoustic model output. finally, based on comparing the first set of errors and the second set of errors, an acoustic model error ratio is generated.
Inventor(s): Harsh SHRIVASTAVA of Redmond WA (US) for microsoft technology licensing, llc, Robin ABRAHAM of Redmond WA (US) for microsoft technology licensing, llc
IPC Code(s): G16B25/10, G06N20/20, G16B40/20, G16B45/00
CPC Code(s): G16B25/10
Abstract: an ensemble machine learning model is used to visualize complex data relationships. complex data is provided to multiple generator models that each independently create a graph representing relationships in the data. at least one of the generator models is a machine learning model that can be trained with a generator model loss function. the graphs produced by the separate generator models are combined by an ensemble model to create a consensus graph. the ensemble model may be implemented as an edge-selector neural network. the models are trained jointly with a ensemble model loss function that includes the loss functions of the generator models added as regularization terms. a visualization of the ensemble graph is created to aid a user in understanding the complex data relationships.
Inventor(s): Asbjørn Cennet Cliff Drachmann of Copenhagen (DK) for microsoft technology licensing, llc, Charles Masamed Marcus of Copenhagen (DK) for microsoft technology licensing, llc
IPC Code(s): H01L21/02, H10N60/01
CPC Code(s): H01L21/02178
Abstract: in one example of the disclosed technology, a method of fabricating a device comprises forming a patterned layer of a material on a surface of a substrate by depositing the material through a stencil mask, and forming a passivating layer over the patterned layer and the substrate surface in a sealed apparatus, the substrate being maintained under a vacuum until after the passivating layer has been formed. in some examples, the passivation is performed by oxidising a deposited aluminium layer within a deposition chamber. in some examples, the method can be used for fabricating hybrid semiconductor-superconductor devices, such as majorana zero mode (mzm) nanowire structures for topological quantum bits.
Inventor(s): Ann Hampton THOMAS of Raleigh NC (US) for microsoft technology licensing, llc, Thomas BASNIGHT of Raleigh NC (US) for microsoft technology licensing, llc, Thomas DETWILER of Huntsville AL (US) for microsoft technology licensing, llc
IPC Code(s): H03K17/082, H03K3/84
CPC Code(s): H03K17/0822
Abstract: a traffic control circuit in a node of a mesh network receives indications that circuit switching in the area of the node needs to be reduced and selectively inhibits traffic in selected channels of the network segments in a configurable manner to mitigate a voltage droop while allowing traffic to continue to the extent possible. the indications of circuit switching may include indicators of traffic generated in the node or in another node and an indicator that the power rail voltage level has dropped to a lower threshold. the traffic control circuit may determine a traffic reduction is needed based on combinations of the indicators. based on configurable selections, the traffic control circuit may cause traffic to be inhibited in certain channels of network segments. a configurable linear feedback shift register may be employed to inhibit traffic in each channel according to a configured traffic profile.
Inventor(s): Jouya JADIDIAN of Mountain View CA (US) for microsoft technology licensing, llc, Ashley N. SAULSBURY of Redmond WA (US) for microsoft technology licensing, llc, Mohit NARANG of Cupertino CA (US) for microsoft technology licensing, llc, Ruben CABALLERO of San Jose CA (US) for microsoft technology licensing, llc
IPC Code(s): H04B10/116, H04B10/114, H04B10/2575
CPC Code(s): H04B10/116
Abstract: an extended reality headset has light-based communication transceivers coupled to the extended reality headset. the relative position of a remote transceiver with respect to the current position and orientation of the extended reality headset is determined. a line-of-sight is calculated from the light-based communication transceivers to the remote transceiver. the light-based communication transceivers emit a light-based communications beam in accordance with the calculated line-of-sight. the light-based communications beam is adjusted in response to changes to the relative position of the remote transceiver with respect to the current position and orientation of the extended reality headset.
Inventor(s): Prashant DEWAN of Portland OR (US) for microsoft technology licensing, llc, Andreea Mihaela PINTILIE of Cambridge (GB) for microsoft technology licensing, llc, Mark Andrew CAWSTON of King's Lynn (GB) for microsoft technology licensing, llc, Kaloyan Aleksandro ALEKSIEV of London (GB) for microsoft technology licensing, llc
IPC Code(s): H04L9/32, H04L9/08, H04L9/14
CPC Code(s): H04L9/3268
Abstract: systems and methods are provided for implementing a cluster-wide root secret (âcwrsâ) key for distributed node clusters. in a multi-node cluster, a leader node has a leader node security system that generates the cwrs key, which is a common secret key for all workloads (e.g., containers or vms) in the multi-node cluster. the leader node security system encrypts the generated cwrs key using a public key and/or a bootstrap key received from a non-leader node that requests the cwrs key. in examples, the leader node security system signs the encrypted cwrs key using its private key for subsequent verification, by the requesting non-leader node, that the cwrs key was generated by the leader node security system. the cwrs thus encrypted can be securely sent to the requesting non-leader node for subsequent encryption or decryption of secret data by the security system of the non-leader node.
Inventor(s): Kristopher Aaron MAKEY of Kirkland WA (US) for microsoft technology licensing, llc, Alexis DESCRE of Seattle WA (US) for microsoft technology licensing, llc, Donald T. SPRAGUE of Seattle WA (US) for microsoft technology licensing, llc, William Sean SHEEHAN of Seattle WA (US) for microsoft technology licensing, llc, Warren Michael ALPERT of Cambridge MA (US) for microsoft technology licensing, llc, Robert Mitchell SMITH of Seattle WA (US) for microsoft technology licensing, llc, Arnav Kumar AGRAWAL of Bellevue WA (US) for microsoft technology licensing, llc
IPC Code(s): H04L9/40, G06Q50/00
CPC Code(s): H04L63/10
Abstract: aspects of the present disclosure relate to adverse user behavior detection and mitigation. in examples, a user account of a social platform may be trusted or untrusted. if the user account is untrusted, activity of the user account may be buffered so as to not directly affect social metrics of the social platform. for example, if the untrusted user account follows a target user account, the untrusted user account may be added to a separate set of followers or otherwise separated from a set of trusted followers of the target user account. eventually, each user account in the separate set is evaluated to determine whether the user account has transitioned to a trusted user. if the user account is now trusted, it may be migrated to the set of trusted followers. however, if the user account is untrusted, it may be removed from the separate set, thereby reverting the activity.
Inventor(s): Yichen JIA of Kirkland WA (US) for microsoft technology licensing, llc, Samuel CHUNG of Seattle WA (US) for microsoft technology licensing, llc
IPC Code(s): H04L65/1093, G06F3/0482, H04L9/40
CPC Code(s): H04L65/1093
Abstract: the disclosed techniques provide features for managing conference user interfaces and access rights to content teams for event subgroups. movement of an avatar or a user representation in a user interface and selective audio streaming can be achieved in response to a selection of a command, e.g., a âlistenâ command, corresponding to a specific subgroup. the disclosed techniques include a number of types of commands that are used to control the movement of an avatar and control access to a number of select audio streams for a computer of a user. the system moves the avatar from an original position to a second position near or within a graphical representation of the subgroup in response to the command. access to audio streams can be modified to be bidirectional or unidirectional in response to the command.
Inventor(s): Jeffrey A. WEST of Redmond WA (US) for microsoft technology licensing, llc, William Harry SCHULDEN, JR. of Laurel MD (US) for microsoft technology licensing, llc
IPC Code(s): H04L65/613, H04N21/6377, H04N21/643
CPC Code(s): H04L65/613
Abstract: examples of the present disclosure describe systems and methods relating to full motion video (fmv) routing in one-way transfer (owt) systems. the present technology reserves a particular channel for transmission of a video stream, and then transmits the video stream from a low-trust computing environment to a high-trust computing environment along a data path defined by the channel. when the video stream is received on the high-trust side, the channel, on which the video stream is received, is determined and used to query a routing table that returns destination addresses of destination devices to which the video stream is to be transmitted. the video stream is then delivered to the destination devices having the corresponding addresses.
Inventor(s): Jeffrey A. WEST of Redmond WA (US) for microsoft technology licensing, llc, William Harry SCHULDEN of Laurel MD (US) for microsoft technology licensing, llc
IPC Code(s): H04N21/238, H04N21/235, H04N21/8352
CPC Code(s): H04N21/238
Abstract: the present disclosure describes systems and methods relating to full motion video (fmv) routing in one-way transfer (owt) systems. the present technology enriches the datagrams of the video stream that are sent from the low-trust side of the owt system with a global unique identifier (guid) that is used as an identifier to determine a particular destination on the high-trust side of the owt system. the enriched video stream is then transmitted through an owt system that provide high reliability for the enriched video stream. when the enriched video stream is received on the high-trust side, the guid in the datagram is extracted and used to identify destination addresses for destination devices in the high-trust computing environment. the video stream is then delivered to the destination devices having the corresponding destination addresses.
Inventor(s): Jeffrey A. WEST of Redmond WA (US) for microsoft technology licensing, llc, William Harry SCHULDEN, JR. of Laurel MD (US) for microsoft technology licensing, llc
IPC Code(s): H04N21/434, H04N21/4385, H04N21/643, H04N21/84
CPC Code(s): H04N21/4348
Abstract: systems and methods relating to full motion video (fmv) routing in one-way transfer (owt) systems are described herein. the present technology modifies or adds packetized elementary streams (pess) of video streams, that are sent from the low-trust side of the owt system, with a global unique identifier (guid) that is used as an identifier to determine a particular destination on the high-trust side of the owt system. the enriched video stream is then transmitted through an owt system that provide high reliability for the enriched video stream. when the enriched video stream is received on the high-trust side, the guid from the pes is extracted and used to identify destination addresses for destination devices in the high-trust computing environment. the video stream is then delivered to the destination devices having the corresponding destination addresses.
20250008220. MEMS-based Imaging Devices_simplified_abstract_(microsoft technology licensing, llc)
Inventor(s): Gritsko PEREZ NOGUERA of Tampere (FI) for microsoft technology licensing, llc
IPC Code(s): H04N23/68, B81B7/04, G02B26/08, H04N23/54, H04N23/57
CPC Code(s): H04N23/687
Abstract: this document relates to devices employing imaging devices, such as cameras and improved camera performance. in one example the device includes an optical element and a sensing element configured to sense light passing through the optical element. this example includes a set of mems actuators configured to be individually selectively controlled to create six degrees of freedom (6dof) movement between the sensing element and the optical element.
Microsoft Technology Licensing, LLC patent applications on January 2nd, 2025
- Microsoft Technology Licensing, LLC
- G06F1/26
- CPC G06F1/26
- Microsoft technology licensing, llc
- G06F3/0482
- G06F9/451
- CPC G06F3/0482
- G06F9/445
- CPC G06F9/44505
- G06F9/455
- CPC G06F9/45558
- G06F11/14
- CPC G06F11/1415
- G06F11/36
- G06F16/33
- CPC G06F11/3612
- CPC G06F11/3636
- Microsoft technology licensing, llc.
- CPC G06F11/3688
- G06F16/185
- CPC G06F16/185
- G06F16/31
- G06F16/2455
- G06F16/332
- G06F16/335
- CPC G06F16/328
- G06F16/338
- CPC G06F16/3329
- G06F16/35
- G06F3/0481
- G06F16/9537
- G06F18/2431
- G06F40/211
- G06N20/10
- CPC G06F16/358
- G06F16/44
- G06F16/438
- CPC G06F16/447
- G06F16/951
- G06F16/953
- CPC G06F16/951
- G06F16/9536
- G06Q50/00
- CPC G06F16/9536
- G06F21/53
- CPC G06F21/53
- G06F21/56
- G06F21/62
- CPC G06F21/566
- G06F21/57
- CPC G06F21/577
- G06F11/34
- CPC G06F21/62
- G06F40/35
- CPC G06F40/35
- G06F40/40
- G06F40/103
- G06F40/166
- G06F40/30
- CPC G06F40/40
- G06N3/048
- G06F18/21
- G06N3/08
- G06N20/00
- G10L15/06
- G10L15/16
- CPC G06N3/048
- H04L67/1396
- H04L67/50
- CPC G06N3/08
- G06N3/084
- G06N3/047
- CPC G06N3/084
- G06N5/04
- CPC G06N5/04
- CPC G06N20/00
- G06F9/38
- G06T11/60
- G06F16/532
- G06F16/535
- G06T7/13
- G06T7/73
- CPC G06T11/60
- G06T17/00
- CPC G06T17/00
- G10L15/01
- G10L15/19
- CPC G10L15/01
- G16B25/10
- G06N20/20
- G16B40/20
- G16B45/00
- CPC G16B25/10
- H01L21/02
- H10N60/01
- CPC H01L21/02178
- H03K17/082
- H03K3/84
- CPC H03K17/0822
- H04B10/116
- H04B10/114
- H04B10/2575
- CPC H04B10/116
- H04L9/32
- H04L9/08
- H04L9/14
- CPC H04L9/3268
- H04L9/40
- CPC H04L63/10
- H04L65/1093
- CPC H04L65/1093
- H04L65/613
- H04N21/6377
- H04N21/643
- CPC H04L65/613
- H04N21/238
- H04N21/235
- H04N21/8352
- CPC H04N21/238
- H04N21/434
- H04N21/4385
- H04N21/84
- CPC H04N21/4348
- H04N23/68
- B81B7/04
- G02B26/08
- H04N23/54
- H04N23/57
- CPC H04N23/687
