Abrégé

Various embodiments provide a so-called companion experience in which content consumed on a primary screen can serve as a source for an automatic search that returns related content that can be presented on an auxiliary screen. The companion experience can be considered to reside in a layer that can be moved across different screens. The different screens can include different physical screens, such as those associated with different computing devices, or the same physical screen in which the companion experience would be rendered in a frame or sub-window.

Classes IPC  ?

• G06F 16/248 - Présentation des résultats de requêtes
• G06F 3/14 - Sortie numérique vers un dispositif de visualisation
• G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
• H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau

Abrégé

A call model is generated that takes into account location-specific information and target attributes such as throughput per user. A cluster of different machine learning models is utilized to compute dynamic call model characteristics for each location, and merges the outputs into a dynamic call model. Additionally, techniques such as feature vector extraction, clustering algorithms, and ensemble models are employed to improve the accuracy and predictive performance of the machine learning models.

Classes IPC  ?

• G06N 5/022 - Ingénierie de la connaissanceAcquisition de la connaissance
• H04L 41/14 - Analyse ou conception de réseau
• H04L 47/70 - Contrôle d'admissionAllocation des ressources

Abrégé

A fine-grain selectable partially privileged container virtual computing environment provides a vehicle by which processes that are directed to modifying specific aspects of a host computing environment can be delivered to, and executed upon, the host computing environment while simultaneously maintaining the advantageous and desirable protections and isolations between the remaining aspects of the host computing environment and the partially privileged container computing environment. Such partial privilege is provided based upon directly or indirectly delineated actions that are allowed to be undertaken on the host computing environment by processes executing within the partially privileged container virtual computing environment and actions which are not allowed. Aspects of the host computing environment operating system, such as the kernel, are extended to interface with container-centric mechanisms to receive information upon which actions can be allowed or denied by the kernel even if the process attempting such actions would otherwise have sufficient privilege.

Classes IPC  ?

• G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
• G06F 9/54 - Communication interprogramme
• G06F 21/53 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p. ex. "boîte à sable" ou machine virtuelle sécurisée

Abrégé

Systems and methods for resource-efficient retrieval of information using a generative AI model are disclosed. An input query requesting information from a set of documents is used in a prompt for a generative AI model to generate a search query to identify the documents relevant to the input query and their respective relevancy scores. The input query is used as an input another model to determine a depth score indicating a predicted number of documents needed to retrieve the information. Based on the depth score and the relevancy scores of the relevant documents, the system extracts grounding data from the identified relevant documents to generate an answer synthesis prompt for the generative AI model. The generative AI model processes the second to produce a response to the input query including the requested information.

Classes IPC  ?

• G06F 16/383 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
• G06F 16/332 - Formulation de requêtes
• G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
• G06F 40/40 - Traitement ou traduction du langage naturel

Abrégé

Techniques are described herein that are capable of converting pages written in page storage during a user session to page-embedded blocks in block storage for reading. Blocks of first data are read from block storage during a user session. Pages of second data are written to page storage during the user session. The pages of the second data indicate changes to be made with regard to at least a subset of the blocks of the first data in the block storage. At a time instance at which no pages are being written to the page storage, the pages of the second data are transferred from the page storage to the block storage by converting the pages of the second data, which are configured to have a page format associated with the page storage, to page-embedded blocks, which are configured to have a block format associated with the block storage.

Classes IPC  ?

• G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement

Abrégé

A server computing device is provided, including a processor configured to receive a homomorphically encrypted input embedding vector from a client computing device. At a transformer network, the processor may generate a plurality of homomorphically encrypted intermediate vectors at least in part by performing inferencing on the homomorphically encrypted input embedding vector. The processor may transmit the plurality of homomorphically encrypted intermediate output vectors to the client computing device. The processor may receive a plurality of homomorphically encrypted intermediate input vectors from the client computing device subsequently to transmitting the homomorphically encrypted intermediate output vectors to the client computing device. At the transformer network, the processor may generate a homomorphically encrypted output vector at least in part by performing additional inferencing on the homomorphically encrypted intermediate input vectors. The processor may transmit the homomorphically encrypted output vector to the client computing device.

Classes IPC  ?

• H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité

Abrégé

Large language models (LLMs) and visual-language models (VLMs) are able to provide robust results based on specified formatting and organization. Although LLMs and VLMs are designed to receive natural language input, users often lack the skill, knowledge, or patience to utilize LLMs and VLMs to their full potential. By leveraging screen understanding, AI prompts (or “pills”) may automatically be generated for artificial-intelligence (AI) assistance and query resolution in a VLM/LLM environment. Using an image encoder, a current screenshot is processed into an image embedding and compared to text embeddings representing screenshot activities. By identifying the text embedding having the closest similarity to the image embedding, a screen activity being performed by the user may be determined. Suggested AI prompts (or “pills”) may then be generated in real-time to assist the user in performing the screen activity.

Classes IPC  ?

• G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
• G06V 30/19 - Reconnaissance utilisant des moyens électroniques

Abrégé

Methods for fabricating packages with dummy dies having a construction that mimics warpage of the other components included in the package are described. A method for fabricating a package with a floor plan having sections for placement of components includes arranging a first component in a first section of the floor plan and arranging a second component in a second section of the floor plan, where each of the first component and the second component comprises active circuitry for providing at least one of compute, storage, or communication functionality. The method further includes forming a dummy die having a construction that mimics warpage of at least one of the first component or the second component. The method further includes arranging the dummy die in an unoccupied section of the floor plan for the package.

Classes IPC  ?

• H01L 23/31 - Encapsulations, p. ex. couches d’encapsulation, revêtements caractérisées par leur disposition
• H01L 21/56 - Encapsulations, p. ex. couches d’encapsulation, revêtements
• H01L 23/00 - Détails de dispositifs à semi-conducteurs ou d'autres dispositifs à l'état solide
• H01L 23/498 - Connexions électriques sur des substrats isolants
• H01L 25/00 - Ensembles consistant en une pluralité de dispositifs à semi-conducteurs ou d'autres dispositifs à l'état solide
• H01L 25/065 - Ensembles consistant en une pluralité de dispositifs à semi-conducteurs ou d'autres dispositifs à l'état solide les dispositifs étant tous d'un type prévu dans une seule des sous-classes , , , , ou , p. ex. ensembles de diodes redresseuses les dispositifs n'ayant pas de conteneurs séparés les dispositifs étant d'un type prévu dans le groupe
• H01L 25/16 - Ensembles consistant en une pluralité de dispositifs à semi-conducteurs ou d'autres dispositifs à l'état solide les dispositifs étant de types couverts par plusieurs des sous-classes , , , , ou , p. ex. circuit hybrides

Abrégé

Eye and hand tracking systems in head-mounted display (HMD) devices are arranged with lensless camera systems using optical masks as encoding elements that apply convolutions to optical images of body parts (e.g., eyes or hands) of HMD device users. The convolved body images are scrambled or coded representations that are captured by a sensor in the system, but are not human-recognizable. A machine learning system such as a neural network is configured to extract body features directly from the coded representation without performance of deconvolutions conventionally utilized to reconstruct the original body images in human-recognizable form. The extracted body features are utilized by the respective eye or hand tracking systems to output relevant tracking data for the user's eyes or hands which may be utilized by the HMD device to support various applications and user experiences. The lensless camera and machine learning system are jointly optimizable on an end-to-end basis.

Classes IPC  ?

• G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
• G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
• G02B 27/01 - Dispositifs d'affichage "tête haute"
• G06N 3/084 - Rétropropagation, p. ex. suivant l’algorithme du gradient
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains
• G06V 40/18 - Caractéristiques de l’œil, p. ex. de l’iris

Abrégé

Systems and methods for converting the result of a radio frequency (RF) measurement into the quantum capacitance of a device are described. An example method includes, by performing a radio frequency (RF) measurement, extracting frequency shift and resonator loss shift of a resonator relative to a reference trace of the resonator, where the resonator is coupled to a quantum device. The method further includes from the extracted frequency shift and the resonator loss shift, without resonator fitting, deriving both a real part and an imaginary part of a quantum capacitance associated with the quantum device.

Classes IPC  ?

• G01R 29/08 - Mesure des caractéristiques du champ électromagnétique

Abrégé

A computing system including one or more processing devices configured to identify one or more severe hook faults in a stabilizer channel. Identifying the severe hook faults includes receiving a circuit channel check matrix, the columns of which indicate values of checks associated with elementary faults of the stabilizer channel. Identifying the severe hook faults further includes receiving a phenomenological channel check matrix as a sub-matrix of the circuit channel check matrix, receiving a logical effect matrix, and receiving a weight vector that indicates probability weights of the elementary faults. Based at least in part on the circuit channel check matrix, the logical effect matrix, the phenomenological channel check matrix, and the weight vector, identifying the severe hook faults further includes computing column indices of columns of the circuit channel check matrix that correspond to the severe hook faults. The processing devices output an indication of the severe hook faults.

Classes IPC  ?

• G06N 10/70 - Correction, détection ou prévention d’erreur quantique, p. ex. codes de surface ou distillation d’état magique

Abrégé

Systems and techniques for facilitating unified multichannel communication are provided. The described systems and techniques improve communication technology through an encompassing, channel-agnostic approach which unifies disparate communication modes into a singular coherent thread. A unified multichannel communication ("UMC") service of a UMC platform can initialize a UMC thread for a UMC session, where the UMC thread can be used to facilitate unified multichannel communication. The UMC session can involve multiple participants, including human users and software agents (e.g., conversational bots, virtual agents, digital assistants, and other dialog interfaces). The UMC platform can facilitate creating and interacting with a digital assistant providing unified multichannel communication.

Classes IPC  ?

• H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
• H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
• H04L 51/56 - Messagerie unifiée, p. ex. interactions entre courriel, messagerie instantanée ou messagerie IP convergente [CPM]

Abrégé

Disclosed herein is a system for implementing a management controller on a node, or network server, that is dedicated to monitoring the individual health of a plurality of accelerator modules configured on the node. Based on the monitored health, the management controller is configured to implement autonomous power cycle control of individual accelerator modules. The autonomous power cycle control is implemented without violating the requirements of standards established for accelerator modules (e.g., OPEN COMPUTE PROJECT requirements, PERIPHERAL COMPONENT INTERCONNECT EXPRESS (PCIe) interface requirements).

Classes IPC  ?

• G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts

Abrégé

This disclosure describes utilizing a generative document system to dynamically build and provide generative search result documents. The generative document system utilizes an aggregated framework that leverages one or more large generative models (LGMs). For example, the aggregated framework includes three stages where local processes are applied to generative outputs from LGMs, with each stage building upon the generative inputs from previous stages. The generative document system uses the aggregated framework to create generative search result documents based on search queries and their corresponding search result links. These generative search result documents provide interactive, intuitive, comprehensive, and flexible curation of answers that address the respective search queries.

Classes IPC  ?

• G06F 16/3329 - Formulation de requêtes en langage naturel
• G06F 16/338 - Présentation des résultats des requêtes
• G06F 16/34 - NavigationVisualisation à cet effet
• G06F 16/951 - IndexationTechniques d’exploration du Web
• G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus

Abrégé

A computing device assembly (100) is provided, including a rack (10), and a plurality of compute units (12) that are horizontally oriented and mounted within the rack (10) in one of two vertical stacks (12A, 12B). The computing device assembly (100) further includes a plurality of switches (16) that are vertically oriented and mounted along a front side (24) of the rack (10) laterally between the two vertical stacks (12A, 12B) of compute units (12). The computing device assembly (100) further includes a plurality of horizontal cable backplanes (14) mounted in a vertical stack along a rear side (22) of the rack (10). The computing device assembly (100) further includes a plurality of vertical cable shuffles (20) mounted between the two vertical stacks (12A, 12B) of compute units (12) and between the vertically oriented switches (16) and the vertical stack of horizontal cable backplanes (14).

Classes IPC  ?

• G06F 1/18 - Installation ou distribution d'énergie
• H05K 7/14 - Montage de la structure de support dans l'enveloppe, sur cadre ou sur bâti
• H04L 49/40 - Détails de construction, p. ex. alimentation électrique, construction mécanique ou fond de panier

Abrégé

A method, computer program product, and computing system for speech language identification. An input speech signal is received in a particular language. The input speech signal is processed by a plurality of speech recognition processing paths, each speech recognition processing path to recognize an associated subset of the languages. Processing, with each of the speech recognition processing paths, the input speech signal using machine learning to identify a language which is a closest match to the particular language of the input speech signal, resulting in a plurality of identified languages. The input speech signal and an indication of each of the plurality of identified languages is received in a further speech recognition processing path. The input speech signal is processed, using machine learning, to recognize one of the identified languages as a closest match to the particular language.

Classes IPC  ?

• G10L 15/00 - Reconnaissance de la parole
• G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
• G10L 15/32 - Reconnaisseurs multiples utilisés en séquence ou en parallèleSystèmes de combinaison de score à cet effet, p. ex. systèmes de vote
• G10L 15/28 - Détails de structure des systèmes de reconnaissance de la parole
• G10L 15/30 - Reconnaissance distribuée, p. ex. dans les systèmes client-serveur, pour les applications en téléphonie mobile ou réseaux

Produits et services

Downloadable software in the nature of a mobile application; downloadable computer software that enables users to access and interact with information and databases; downloadable computer software for collecting, editing, organizing, modifying, bookmarking, storing, sharing and publishing data and information; downloadable computer software for uploading, managing, tracking, and sharing customized content; downloadable computer software for searching, accessing, displaying, sharing and reviewing newsletters, research reports, blogs, and articles; downloadable computer software featuring multimedia content; downloadable computer software for enabling transmission of images and audiovisual and video content; downloadable computer software for use in creating, downloading, uploading, designing, modifying, reproducing, transmitting, and sharing images, graphics, fonts, photographs, text, videos, and data; downloadable recreational game software; downloadable mobile applications for interactive and recreational games; downloadable software for games and social networking; downloadable logic, word, trivia, and puzzle game software via a global computer network and wireless devices; downloadable electronic publications in the nature of newsletters, research reports, articles and white papers on topics of professional interest; downloadable computer software development tools; downloadable computer software that provides web-based access to applications and services through a web-operating system or portal interface; downloadable computer software for use in business analytics and database management; downloadable computer software for social media, marketing, merchandising, customer service, website performance, search engine optimization, technology, consumer goods, retail, and manufacturing; downloadable computer software for tracking and analyzing user interaction with customized content; downloadable education software; downloadable computer software for providing online courses, seminars, interactive classes, educational instruction, and course materials; downloadable computer software for providing access to internet search engines featuring information for obtaining job listings, resume postings, and other job searches; downloadable job searching, sourcing and recruiting software using artificial intelligence (AI) for users on a social networking, employment, and business networking communication platform; downloadable chatbot software using artificial intelligence (AI) for users on a social networking, employment, and business networking communication platform; downloadable writing and communication software using artificial intelligence (AI) for assisting platform users with employment, job sourcing and recruiting, lead generation, and business-related inquiries; content creation software using artificial intelligence for users on a social networking, employment, and business networking communication platform; downloadable computer software using artificial intelligence (AI) for employee training and professional development; downloadable computer software using artificial intelligence (AI) for providing online courses, seminars, interactive classes, educational instruction, and course materials; downloadable podcasts in the field of in the field of employment, recruitment of personnel, careers, job resources and listings, and professional networking and wide field of topics; downloadable computer software using artificial intelligence (AI) for providing online courses, seminars, interactive classes, educational instruction, and course materials. Providing online employment information and employment services; providing online business networking services; providing online career networking services; recruitment and placement services; providing online employment counseling, career placement services, and personnel recruitment; providing an online searchable databases and interactive databases featuring employment and career opportunities (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing online information in the fields of employment, recruitment of personnel, careers, job resources and listings, career development, professional networking, and employment advertising; providing an interactive computer database featuring recruitment and employment information, employment advertising, job listings, career information and resources via a global computer network (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing an online artificial intelligence (AI) enhanced searchable database featuring employment and career opportunities and business, employment and professional queries and answers (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); business research and survey services utilizing artificial intelligence; providing artificial intelligence (AI) enhanced online computer databases and online searchable databases in the fields of marketing, lead generation, sourcing, recruiting, and business and professional networking (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); online business networking services featuring artificial intelligence (AI) solutions; advertising services; marketing services; marketing consulting services; advertising, marketing, and promotion services for businesses; providing advertising and advertisement services; providing marketing and advertising solutions for marketing campaigns across a wide range of industries; providing resources for creating advertising and marketing campaigns that meet business specific business and b2b needs; creating, placing, displaying, targeting and disseminating online advertisements for others; providing a web site which features advertisements for the goods and services of others on a global computer network (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing advertising and marketing services via an online platform featuring sponsored ad content, sponsored ad messaging, text ads, dynamic ads, and ad placements; advertising, marketing, and promotion services for businesses; providing online advertising on a computer network; providing business and business networking information; advertising and marketing services rendered using artificial intelligence (AI); lead generation activities and services; advertising and marketing services in the nature of accessing, extracting, and organizing information from the internet and other sources regarding people, companies, products, marketing, industries and other categories; lead generation services rendered using artificial intelligence; employment recruiting services; professional, staff, personnel and talent recruiting services; providing an online searchable database featuring employment and career opportunities and business information (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing an online searchable database featuring business, employment and professional queries and answers (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing information online regarding recruiting and talent solutions; providing an online searchable database featuring professional queries and answers concerning staffing and hiring information (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); charitable services, namely, promoting public awareness about charitable, philanthropic, community service, humanitarian activities and volunteer activities; providing online career networking services and information in the fields of employment, recruitment, job resources, job listings and career path suggestions; providing business information; providing a web site featuring business information in the form of audio, video, transcripts, and other educational materials (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing information, news and commentary in the field of business; providing online information in the fields of employment, staffing, recruiting, career development, professional networking; providing assessment of job and employment skills utilizing artificial intelligence (AI). Electronic messaging services; providing online information, forums, groups, and communities for transmission of messages among users in the fields of employment, staffing, recruiting, career development, professional networking, and training, as well as concerning job searching, and general business topics (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing information, advisory, and consultancy services in the fields of communications via global computer networks, transmission of electronic mail, electronic messaging, and the provision of online forums, groups, and communities (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); provision of online forums, groups, and communities for transmission of messages among computer users concerning job searching, professional networking, and general business topics, as well as for employment, staffing, recruiting, career development, professional training, and educational course materials (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing access to computer, electronic, and online databases; transmission of podcasts and webcasts; electronic transmission and streaming of digital media content for others via global and local computer networks. Providing online non-downloadable news articles relating to business, current events, education, entertainment, technology, culture, entrepreneurship, leadership, management, marketing, recruiting, career, and professional development; online publication of journals and articles; publication of online text, graphics, content, information, and multimedia content; publication of content regarding current events and news, employment, workforce, career and personal development, jobs, finance, economy, careers, and recruiting; providing online information in the fields of training; providing online digital libraries containing online training courses, videos, articles, and customized content; providing online digital libraries containing online training courses, videos, articles, and customized content; providing online resources in the fields of business skills, technical skills, and professional development (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing online educational programs in the fields of employment, staffing, recruiting, career development, professional networking, and training; education and entertainment services, namely, providing non-downloadable publications in the nature of newsletters featuring text, graphics, audio and video clips featuring news, information, and commentary relating to business, current events, education, entertainment, technology, culture, entrepreneurship, leadership, management, marketing, recruiting, career and professional development; providing on-line educational courses and educational course materials in the fields of employment, staffing, recruiting, career development, professional networking, and training; providing educational and professional training assessments; providing educational and professional conversation assessments rendered with Artificial Intelligence (AI); entertainment services, namely, providing online electronic recreational games; providing entertainment information in the field of interactive games and recreational game playing; entertainment services, namely, providing a website featuring logic, word, trivia, and puzzle games (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); multimedia publishing of journals, software, games, and electronic publications; entertainment services, namely, providing podcasts and webcasts in the field of employment, recruitment of personnel, careers, job resources and listings, news and current events, professional networking, and wide field of topics (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing educational content and information online in the field of global labor markets, workforce reports, skills reports, green skills reports, economic development, and the global economy; providing an online newsletter featuring economic data, economic insights, workforce data and research, data sets, and policy information on the global economy (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing educational and learning services, namely providing a website featuring generative artificial intelligence that develops and simulates speaking, listening, interpersonal and conversational skills (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing training and education preparation programs to certify job skills online; business education and training services; educational services in the nature of business schools; teaching and training in business; providing continuing business education courses; college educational services; educating at university or colleges; providing information about education; educational services, namely, conducting classes, seminars, conferences, and workshops in the field of business and distribution of educational materials in connection therewith; providing certification of job skill assessments online. Providing temporary use of on-line non-downloadable software; providing a website featuring temporary use of non-downloadable software (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); application service provider (ASP) services; providing an online software platform; providing temporary use of on-line non-downloadable software that enables users to access and interact with information and databases; providing customized web pages featuring user-defined information, audio, text, video, and images (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); hosting an interactive website featuring technology that allows users to create, download, upload, design, modify, reproduce, transmit, and share images, graphics, fonts, photographs, text, videos, and data; providing temporary use of on-line non-downloadable software for collecting, editing, organizing, modifying, bookmarking, storing, sharing and publishing data and information; providing temporary use of on-line non-downloadable software for uploading, managing, tracking, and sharing customized content; providing temporary use of on-line non-downloadable software for searching, accessing, displaying, sharing and reviewing newsletters, research reports, blogs, and articles; providing general and customized information in a wide variety of fields (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing general and customized information relating to business, current events, education, entertainment, technology, culture, entrepreneurship, leadership, management, marketing, recruiting, career, and professional development (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing temporary use of on-line non-downloadable software featuring multimedia content; providing temporary use of on-line non-downloadable software for enabling transmission of images and audiovisual and video content; providing temporary use of on-line non-downloadable software for use in creating, downloading, uploading, designing, modifying, reproducing, transmitting, and sharing images, graphics, fonts, photographs, text, videos, and data; providing temporary use of online non-downloadable recreational game software; providing temporary use of online non-downloadable software for interactive games and recreational game playing purposes; providing temporary use of online non-downloadable software for games and social networking; providing temporary use of online non-downloadable logic, word, trivia, and puzzle game software; providing a website featuring temporary use of non-downloadable software featuring electronic publications in the nature of newsletters, research reports, articles and white papers on topics of professional interest (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing temporary use of on-line non-downloadable software development tools; providing temporary use of on-line non-downloadable software that provides web-based access to applications and services through a web-operating system or portal interface; providing temporary use of on-line non-downloadable software for use in business analytics and database management; providing temporary use of on-line non-downloadable software for social media, marketing, merchandising, customer service, website performance, search engine optimization, technology, consumer goods, retail, and manufacturing; providing temporary use of on-line non-downloadable software for tracking and analyzing user interaction with customized content; providing an online education software platform; providing temporary use of on-line non-downloadable software for providing online courses, seminars, interactive classes, educational instruction, and course materials; providing an online software platform for employee training and professional development; providing temporary use of on-line non-downloadable software for providing access to internet search engines featuring information for obtaining job listings, resume postings, and other job searches; providing an online software platform for employee training and professional development that allows users to upload, manage, and share customized content, access online courses and content, receive data analytics and insights on learning and skills development, host online web facilities, links, webcasts and podcasts for managing and sharing online content; providing non-downloadable job searching, sourcing and recruiting software using artificial intelligence (AI) for users on a social networking, employment, and business networking communication platform; providing non-downloadable chatbot using artificial intelligence (AI) for users on a social networking, employment, and business networking communication platform; non-downloadable writing and communication software using artificial intelligence (AI) for assisting platform users with writing, communicating, and with employment, job, recruiting, lead generation, and business-related inquiries (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); non-downloadable content creation software using artificial intelligence for users on a social networking, employment, and business networking communication platform (term considered too vague by the International Bureau pursuant to Rule 13 (2) (b) of the Regulations); providing non-downloadable software using artificial intelligence (AI) for employee training and professional development; providing non-downloadable software platform tools for creating, placing, displaying, controlling and tracking advertising and marketing content; providing non-downloadable software platform tools for use in customer relationship management (CRM), lead generation activities and services, and tracking, accessing, extracting and organizing sales information; hosting digital content on internet. Providing social networking services via global communication networks; providing information in the field of personal development, namely, self-improvement and self-fulfillment; online social networking services; providing social networking services utilizing artificial intelligence (AI) online.

Abrégé

Computer-implemented techniques for multimodal content relevance prediction using neural networks involves processing multimodal content comprising a digital image and text. Initially, dense embeddings are obtained: an image embedding from a pretrained convolutional neural network, and a text embedding from a pretrained transformer network. These embeddings encapsulate the features of the image and text respectively. Two pretrained dense neural sub-networks then reduce the dimensionality of these embeddings. A third dense neural sub-network determines a numerical score for the multimodal content using the reduced embeddings and an additional feature embedding. This score reflects various aspects of the multimodal content, leading to an action taken based on this numerical evaluation, providing a comprehensive and nuanced understanding and management of multimodal digital content.

Classes IPC  ?

• G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
• G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
• G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
• G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence

Abrégé

A signal conditioning connector assembly is provided, including an enclosure, and a plurality of signal conditioner layers mounted within the enclosure. Each signal conditioner layer includes a substrate, signal conditioner circuitry mounted to the substrate, first electrodes forming a first connector on a first side of the signal conditioner circuitry, second electrodes forming a second connector on a second side of the signal conditioner circuitry, a heat spreader in thermal communication with a side of the signal conditioner circuitry opposite the substrate, and a liquid cooling pipe positioned adjacent and in thermal communication with the heat spreader. The liquid cooling pipe is configured to draw heat away from the heat spreader for thermal management. The signal conditioning connector assembly can be positioned adjacent an interface between the vertical cable shuffle and the horizontal cable backplane within the rack of the computing device assembly of the first and second aspects.

Classes IPC  ?

• H05K 7/20 - Modifications en vue de faciliter la réfrigération, l'aération ou le chauffage

Abrégé

A computer-implemented method includes obtaining a training data set for multiple monitors for various services, which includes service properties and monitor metadata. The metadata for a given monitor defines resources utilized by a corresponding service. The method determines N feature vectors and a target resource class for each service based on the training data set. A machine learning model is trained in multiple training iterations using the training data set. In a given training iteration, N feature vectors of a selected service are provided to the machine learning model, which predicts a resource class of the selected service. A difference between the predicted resource class and the target resource class for the selected service is determined, based on which one or more parameters of the machine learning model can be updated. The trained machine learning model can be used to recommend a new monitor for a new service.

Classes IPC  ?

• G06N 20/00 - Apprentissage automatique

Abrégé

Example solutions enhance security of bootable media images during bare metal restores. A boot image generation request and original image integrity data is received from a first computing device. An original image timestamp associated with the boot image generation request is stored. A message is received from a second computing device that includes current image integrity data generated by the second computing device using a current boot image. The original image integrity data is verified to match the current image integrity data. The message is determined to have been received within a length of time from the original image timestamp. A registration of the second computing device is performed within the device management system based on the verification and the determination.

Classes IPC  ?

• G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité

Abrégé

A method of and system for method for ensuring data compliance in a computer environment includes retrieving data rules from a rule repository, the rule repository being a repository that stores one or more rules that are associated with storage or transfer of data by one or more devices in the computing environment, retrieving metadata about data flow in the computing environment from a policy governor, retrieving information about a data classification of data used by one or more services provided by the computing environment, and retrieving data about a network topography of the computing environment. The retrieved data is then used to generate a configuration file for configuring a Field Programmable Gate Array (FPGA) based on at least one of the retrieved data. The configuration file is transmitted to an FPGA configuration loader for loading the configuration file onto the FPGA, where the FPGA utilizes the configuration file to implement the data rules in the computing environment to ensure compliance with the rules.

Classes IPC  ?

• H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
• H04L 41/084 - Configuration en utilisant des informations préexistantes, p. ex. en utilisant des gabarits ou en copiant à partir d’autres éléments

Abrégé

Techniques, software, and systems for enhanced management of computing system battery charge rates are included. In one implementation, a method includes identifying a preference level for battery charging performance for a computing system when supplied by a power supply having a power supply capacity. Based at least on the preference level, the method includes allocating the power supply capacity to bias a primary allocation of the power supply capacity to charging operations of a battery of the computing system while providing a remainder allocation to at least a system processor of the computing system.

Classes IPC  ?

• G06F 1/26 - Alimentation en énergie électrique, p. ex. régulation à cet effet
• H02J 7/00 - Circuits pour la charge ou la dépolarisation des batteries ou pour alimenter des charges par des batteries

Abrégé

A heuristic that solves an optimization problem is analyzed to determine how and why it underperforms a benchmark solution. A novel intermediate representation (IR) is used to construct a network flow graph that models the optimization problem. Solutions to the optimization problem are defined programmatically with reference to the network flow graph. A compiler translates the programmatic definitions of the heuristic and a benchmark solution to a low-level model of constraints and objectives. A heuristic analyzer iteratively analyzes the constraints and objectives to identify inputs that cause the heuristic to yield inefficient results relative to the benchmark. Properties of inputs and properties of the heuristic that cause the heuristic to underperform are identified, and an explanation of when, how, and why the heuristic underperforms is generated.

Classes IPC  ?

• G06F 17/11 - Opérations mathématiques complexes pour la résolution d'équations

Abrégé

A computing device assembly is provided, including a rack, and a plurality of compute units that are horizontally oriented and mounted within the rack in one of two vertical stacks. The computing device assembly further includes a plurality of switches that are vertically oriented and mounted along a front side of the rack laterally between the two vertical stacks of compute units. The computing device assembly further includes a plurality of horizontal cable backplanes mounted in a vertical stack along a rear side of the rack. The computing device assembly further includes a plurality of vertical cable shuffles mounted between the two vertical stacks of compute units and between the vertically oriented switches and the vertical stack of horizontal cable backplanes.

Classes IPC  ?

• H05K 7/14 - Montage de la structure de support dans l'enveloppe, sur cadre ou sur bâti

Abrégé

The technology described herein provides an improved framework for novel view synthesis utilizing scene-level features and pixel-level features. In particular, the technology provides semantic representations corresponding to the scene, along with semantic representations corresponding to the each pixel, so that inherent interconnections within objects in the scene can be determined by transformer encoders that would not otherwise be determined by the pixel-level feature representations alone. In this regard, the technology described herein improves the generalizability of Neural Radiance Fields (NeRF) based techniques to novel scenes to avoid the need for retraining for specific scenes and the few-shot capability of NeRF-based techniques to render novel views using a limited number of reference images.

Classes IPC  ?

• H04N 13/117 - Transformation de signaux d’images correspondant à des points de vue virtuels, p. ex. interpolation spatiale de l’image les positions des points de vue virtuels étant choisies par les spectateurs ou déterminées par suivi du spectateur
• G06T 7/90 - Détermination de caractéristiques de couleur
• G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
• G06V 10/56 - Extraction de caractéristiques d’images ou de vidéos relative à la couleur
• G06V 10/771 - Sélection de caractéristiques, p. ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques

Abrégé

A computer-implemented technique is described herein for defining and applying constraints that regulate a supervisee's interaction with applications. In one implementation, the technique provides a user interface presentation to a supervisor that lists a set of applications that run on plural application execution platforms. The user interface presentation also allows the supervisor to set platform-agnostic constraint information for any identified application. The platform-agnostic constraint information, once set for an application, constrains interaction by a supervisee with all versions of that same application. That is, the constraint information is said to be agnostic with respect to platform in the sense that it applies to a variety of application execution platforms that run the application. In one example, the platform-agnostic constraint information specifies a permitted amount of an activity that the supervisee is permitted to perform across all versions of an application.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité
• G06F 21/10 - Protection de programmes ou contenus distribués, p. ex. vente ou concession de licence de matériel soumis à droit de reproduction

Abrégé

Bidirectional flows of a communication session in a software defined network (SDN) are efficiently managed. A smart switch comprises a digital processing unit (DPU) complex comprising one or more DPUs, and a switching complex comprising one or more network processing units (NPUs). The DPU complex is configured to disaggregate enforcement of policies of the SDN from hosts of the SDN. The switching complex is configured to perform network routing of packets in the SDN. The hosts are implemented on servers communicatively coupled to network interfaces of the SDN. The switching complex is configured to perform policy enforcement of data flows for communication sessions that are offloaded from the DPU complex to the switching complex.

Classes IPC  ?

• H04L 45/00 - Routage ou recherche de routes de paquets dans les réseaux de commutation de données
• H04L 45/74 - Traitement d'adresse pour le routage

Abrégé

The techniques disclosed herein enhance the functionality of network computing infrastructure in resource constrained processes. This is accomplished by assigning differentiated weights to instances of a software service based on the role of the instance. In the context of the present disclosure, a role is a defined set of functionalities within a software service. An individual weight quantitatively represents the computing resource demand imposed by the functionalities of the role. A software orchestration system subsequently places the instances of the software service within a computing environment (e.g., a node, a cluster) for execution. As such, the computing environment can include a resource constraint that represents the capacity of the constituent computing resources to execute the instances of the software service. Accordingly, the instances are placed such that the sum of the weights of the instances is less than or equal to the resource constraint.

Classes IPC  ?

• H04L 47/80 - Actions liées au type d'utilisateur ou à la nature du flux
• H04L 47/70 - Contrôle d'admissionAllocation des ressources
• H04L 47/74 - Mesures pour pallier la non-disponibilité des ressources

Abrégé

A method, computer program product, and computing system for speech language identification. An input speech signal in a particular language of a plurality of languages is received and processed by a plurality of speech recognition processing paths, each speech recognition processing path being configured to recognize a subset of the plurality languages. Each of the plurality of speech recognition processing paths processes the input speech signal using machine learning to identify a language in the associated subset of languages which is a closest match to the particular language of the input speech signal. The processing of the input speech signal by the plurality of speech recognition processing paths results in a plurality of identified languages. The input speech signal and an indication of each of the plurality of identified languages are processed in a further speech recognition processing path to recognize one of the plurality of identified languages as a closest match to the particular language of the input speech signal.

Classes IPC  ?

• G10L 15/00 - Reconnaissance de la parole

Abrégé

Techniques are described for a multi-platform test framework that is configured to generate a target test script indicative of commands and responses for verifying virtual functions implemented in a virtualized computing environment executing a plurality of virtual machines or containers. A translation layer is used to translate the commands and responses of the source test script to equivalent commands and responses usable to verify the virtual function in a second node configured to operate on a second platform of the virtualized computing environment.

Classes IPC  ?

• G06F 11/36 - Prévention d'erreurs par analyse, par débogage ou par test de logiciel

Abrégé

This document relates to providing adaptive teleconferencing experiences using generative image models. For example, the disclosed implementations can employ inpainting and/or image-to-image restyling modes of a generative image model to generate images for a teleconference. The images can be generated based on prompts relating to the teleconference. Users can be superimposed on the generated images, thus giving the appearance that the users are present in an environment generated by the generative image model.

Classes IPC  ?

• G06T 11/40 - Remplissage d'une surface plane par addition d'attributs de surface, p. ex. de couleur ou de texture
• G06T 7/10 - DécoupageDétection de bords
• G06T 7/60 - Analyse des attributs géométriques

Abrégé

Disclosed herein is a system for implementing a management controller on a node, or network server, that is dedicated to monitoring the individual health of a plurality of accelerator modules configured on the node. Based on the monitored health, the management controller is configured to implement autonomous power cycle control of individual accelerator modules. The autonomous power cycle control is implemented without violating the requirements of standards established for accelerator modules (e.g., OPEN COMPUTE PROJECT requirements, PERIPHERAL COMPONENT INTERCONNECT EXPRESS (PCIe) interface requirements).

Classes IPC  ?

• G06F 13/40 - Structure du bus
• G06F 13/42 - Protocole de transfert pour bus, p. ex. liaisonSynchronisation

Abrégé

A natural language query is received from an operator of a telecommunications network. A metadata request is computed from the natural language query. The metadata request is sent to a repository of metadata, the metadata describing telemetry data of the telecommunications network, the telemetry data stored in a relational database. Metadata is received from the metadata repository in response to the metadata request. Using the received metadata and a language model a relational database query is computed and the relational database is queried. A response is received from the relational database, triggering an action.

Classes IPC  ?

• G06F 16/33 - Requêtes
• G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
• G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
• G06F 40/40 - Traitement ou traduction du langage naturel

Abrégé

According to examples, an apparatus may include a processor and a memory on which is stored machine-readable instructions that when executed by the processor, may cause the processor to cause a graphical user interface to be displayed, the graphical user interface including graphical icons of a plurality of authentication types available for assignment to users and a graphical icon of a first user. The instructions may also cause the processor to detect a movement of a graphical icon of a first authentication type from a first location to a second location in the graphical user interface, the second location corresponding to the graphical icon of the first user and based on the detected movement, assign the first authentication type to the first user.

Classes IPC  ?

• G06F 21/36 - Authentification de l’utilisateur par représentation graphique ou iconique

Abrégé

Implementations of the subject matter described herein provide a solution for rate control based on reinforcement learning. In this solution, an encoding state of a video encoder is determined, the encoding state being associated with encoding of a first video unit by the video encoder. An encoding parameter associated with rate control in the video encoder is determining by a reinforcement learning model and based on the encoding state of the video encoder. A second video unit different from the first video unit is encoded based on the encoding parameter. In this way, it is possible to achieve a better quality of experience (QOE) for real time communication with computation overhead being reduced.

Classes IPC  ?

• H04N 19/196 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par le procédé d’adaptation, l’outil d’adaptation ou le type d’adaptation utilisés pour le codage adaptatif étant spécialement adaptés au calcul de paramètres de codage, p. ex. en faisant la moyenne de paramètres de codage calculés antérieurement

Abrégé

Example implementations include a method, apparatus, and computer-readable medium configured for implementing a workflow using a large language model (LLM). A workflow automation application sends a first prompt to a large language model (LLM) to transform a first input data source in a first format to a second format. The workflow automation application sends a second prompt to the LLM to define multiple steps of a workflow starting on the data source in the second format. The workflow automation application sends a third prompt to the LLM to define execution of business logic for each step of the workflow. The workflow automation application receives, from the LLM, output data indicating that each step of the workflow has been executed.

Classes IPC  ?

• G06Q 10/0633 - Analyse du flux de travail

Abrégé

A large language model has multiple different layers, each layer generating a set of hidden state values that are passed on to a subsequent layer, during generation. A probe accesses the hidden state values and generates a probe output indicative of how likely a next token to be generated will be an undesirable token (such as a hallucination). An action signal is generated based upon the probe output. The action signal can be used to terminate generation, to generate an alert, or to perform other actions.

Classes IPC  ?

• G06N 3/0455 - Réseaux auto-encodeursRéseaux encodeurs-décodeurs

Abrégé

Example solutions enhance security of bootable media images during bare metal restores. A boot image generation request and original image integrity data is received from a first computing device. An original image timestamp associated with the boot image generation request is stored. A message is received from a second computing device that includes current image integrity data generated by the second computing device using a current boot image. The original image integrity data is verified to match the current image integrity data. The message is determined to have been received within a length of time from the original image timestamp. A registration of the second computing device is performed within the device management system based on the verification and the determination.

Classes IPC  ?

• G06F 21/64 - Protection de l’intégrité des données, p. ex. par sommes de contrôle, certificats ou signatures
• G06F 8/61 - Installation
• G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
• H04L 9/40 - Protocoles réseaux de sécurité

Abrégé

A system, method, and computer-readable media for executing applications for radio interface controller (RIC) management are disclosed. The system includes far-edge datacenters configured to execute a radio access network (RAN) function and a real-time RIC; near-edge datacenters configured to execute a core network function and a near-real-time RIC or a non-real-time RIC; and a central controller. The central controller is configured to: receive inputs of application requirements, hardware constraints, and a capacity of first and second computing resources at the far-edge datacenters and near-edge datacenters; enumerate a plurality of feasible combinations of application locations and configurations that satisfy the application requirements and hardware constraints; incrementally allocate a quant of the first or second computing resources to a feasible combination that would produce a greatest utility from the quant based on a utility function; and deploy each of the plurality of applications.

Classes IPC  ?

• G06N 3/092 - Apprentissage par renforcement
• H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle

Abrégé

This document relates to providing adaptive teleconferencing experiences using generative image models. For example, the disclosed implementations can employ inpainting and/or image-to-image restyling modes of a generative image model to generate images for a teleconference. The images can be generated based on prompts relating to the teleconference. Users can be superimposed on the generated images, thus giving the appearance that the users are present in an environment generated by the generative image model.

Classes IPC  ?

• H04N 7/15 - Systèmes pour conférences

Abrégé

A method for user intent evaluation includes receiving recorded speech (306) of a human user (104). One or more attention indicators (406) are detected in an image (400) of the human user (104). Using a trained command recognition model (504), a command confidence (506) is estimated indicating a confidence that the recorded human speech (306) includes a command for a smart assistant computing system (100). Based at least in part on detecting the one or more attention indicators (406), and the command confidence (506) exceeding a command confidence threshold, the human user (104) is classified as intending to interact with the smart assistant computing system (100).

Classes IPC  ?

• G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
• G06F 3/16 - Entrée acoustiqueSortie acoustique

Abrégé

Large language models (LLMs) and visual-language models (VLMs) are able to provide robust results based on specified formatting and organization. Although LLMs and VLMs are designed to receive natural language input, users often lack the skill, knowledge, or patience to utilize LLMs and VLMs to their full potential. By leveraging screen understanding, AI prompts (or "pills") may automatically be generated for artificial-intelligence (AI) assistance and query resolution in a VLM/LLM environment. Using an image encoder, a current screenshot is processed into an image embedding and compared to text embeddings representing screenshot activities. By identifying the text embedding having the closest similarity to the image embedding, a screen activity being performed by the user may be determined. Suggested AI prompts (or "pills") may then be generated in real-time to assist the user in performing the screen activity.

Classes IPC  ?

• G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
• G06F 40/30 - Analyse sémantique
• G06N 20/00 - Apprentissage automatique
• G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p. ex. des interruptions ou des opérations d'entrée–sortie
• G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos
• G06F 16/3329 - Formulation de requêtes en langage naturel
• G06F 3/048 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI]

Abrégé

A signal conditioning connector assembly (50) is provided, including an enclosure (52), and a plurality of signal conditioner layers (68) mounted within the enclosure (52). Each signal conditioner layer (68) includes a substrate (66), signal conditioner circuitry (60) mounted to the substrate (66), first electrodes (64) forming a first connector on a first side of the signal conditioner circuitry (60), second electrodes (65) forming a second connector on a second side of the signal conditioner circuitry (60), a heat spreader (62) in thermal communication with a side of the signal conditioner circuitry (60) opposite the substrate (66), and a liquid cooling pipe (54) positioned adjacent and in thermal communication with the heat spreader (62). The liquid cooling pipe (54) is configured to draw heat away from the heat spreader (62) for thermal management. The signal conditioning connector assembly (50) can be positioned adjacent an interface between the vertical cable shuffle (20) and the horizontal cable backplane (14) within the rack (10) of the computing device assembly (100) of the first and second aspects.

Classes IPC  ?

• G06F 1/20 - Moyens de refroidissement
• H05K 7/14 - Montage de la structure de support dans l'enveloppe, sur cadre ou sur bâti
• H05K 7/20 - Modifications en vue de faciliter la réfrigération, l'aération ou le chauffage

Abrégé

Systems and techniques for facilitating unified multichannel communication are provided. The described systems and techniques improve communication technology through an encompassing, channel-agnostic approach which unifies disparate communication modes into a singular coherent thread. A unified multichannel communication ("UMC") service of a UMC platform can initialize a UMC thread for a UMC session, where the UMC thread can be used to facilitate unified multichannel communication.

Classes IPC  ?

• H04L 51/066 - Adaptation de format, p. ex. conversion de format ou compression
• H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
• H04L 51/56 - Messagerie unifiée, p. ex. interactions entre courriel, messagerie instantanée ou messagerie IP convergente [CPM]

Abrégé

Embodiments of the disclosed technologies include parsing a query into a first query portion and at least one second query portion, matching an embedding of the at least one second query portion with an embedding that corresponds to a portion of a document of a document set, mapping the portion of the document to a first node of a graph; by a generative artificial intelligence model, constructing a graph query based on at least the first node, executing the graph query on the graph to identify a second node of the graph, extracting a path from the graph, and configuring the path for output at a device.

Classes IPC  ?

• G06F 16/2453 - Optimisation des requêtes
• G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage

Abrégé

Clickable trackpad designs generally aim to achieve a thin form factor with a minimized footprint that provides consistent user perception of click feel at scale within cost constraints. The clickable trackpad designs found herein adopt a mechanical depression mechanism that allows a user to register a click at any point on the trackpad surface with little variance in the depression force required to register the click. This provides a consistent click feel for the user. Further consistency of the click feel is achieved by establishing simultaneous travel of the entire trackpad surface, no matter where the click force is applied. This motion is a downward translation of the trackpad surface. An end user may press at any location of the trackpad surface to achieve a push button input (or click).

Classes IPC  ?

• G06F 3/041 - Numériseurs, p. ex. pour des écrans ou des pavés tactiles, caractérisés par les moyens de transduction
• G06F 3/0354 - Dispositifs de pointage déplacés ou positionnés par l'utilisateurLeurs accessoires avec détection des mouvements relatifs en deux dimensions [2D] entre le dispositif de pointage ou une partie agissante dudit dispositif, et un plan ou une surface, p. ex. souris 2D, boules traçantes, crayons ou palets

Produits et services

Bath mitts hair pins cosmetic cotton wool for personal use, namely, cotton swabs, cotton balls, cotton pads; pre-moistened cosmetic wipes; dry shampoos; hair styling preparations, namely, hair styling sprays, gels, foams, clays, and waxes; hair masks; hair detangling preparations; eyebrow pencils, eyebrow gels, eyebrow powders, foundations, concealers, eye liner pencils, eye liner gels, powder eyeshadows, liquid eyeshadows, lip liner pencils, lipsticks, powder bronzer, powder blush, powder highlighter, cream bronzer, priming serums, mascara, make-up and eyeshadow palettes, make-up powder, artificial eyelashes, eyelash tints; non-medicated eyelash growth serums; non-medicated eyebrow growth serums; self-adhesive false eyebrows; adhesives for affixing false eyebrows; adhesives for attaching false eyelashes; nail polish removing preparations; adhesives for affixing false nails; false nails; nail art stickers; nail polish; nail polish base coat; nail polish top coat; perfume; musk being perfumery; eau de cologne; eau de toilette; deodorants for personal use; non-medicated bath salts; mouth wash; flower essences for cosmetic purposes facial oils and lotions for cosmetic purposes; skin and body lotions for cosmetic purposes; skin and body moisturizers for cosmetic purposes; non-medicated skin toners; make-up removing preparations; cotton wool impregnated with make-up removing preparations; gift baskets containing non-medicated bath preparations and cosmetic preparations; non-medicated aftershave gels and lotions; shaving foam; non-medicated beard care preparations, namely, balms and cleansers; cosmetic sunscreen preparations; scented water for use as perfumery; scented linen water; skin moisture masks; gel eye masks; facial beauty masks; mask pack for cosmetic purposes; facial sheet masks for cosmetic use; cosmetic facial masks; toiletry bags sold filled with non-medicated toiletry preparations, namely, shampoo, conditioner, facial cleanser, body washes, bath soaps hand-sanitizing preparations; wipes impregnated with sanitizing preparations; anti-cavity dental coating preparations containing fluoride; nail fungus treatment preparations; dietary supplements Nail clippers; electric shavers; non-electric shavers; electric hair trimmers; non-electric hair trimmers; manicure kits comprised of nail clippers, nail files, cuticle pushers, nail buffers; electric hair straightening irons; electric hair curling irons Therapeutic cold therapy packs Electric hair dryers Cosmetic bags and make-up totes, sold empty cosmetic brushes; bath products, namely, loofah sponges and body sponges; exfoliating mitts; floss for dental purposes

Produits et services

software; applications; mobile applications; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence applications; software featuring generative artificial intelligence; applications featuring generative artificial intelligence; software, namely, artificial intelligence, machine learning, and deep learning applications; software, namely, applications featuring generative artificial intelligence; software using artificial intelligence for machine learning; software using artificial intelligence and artificial intelligence techniques to generate content; software that enables users to create user-generated content; software using artificial intelligence to generate content; software for synthesizing human speech and text; software for processing, generating, understanding, and analyzing natural language; software for machine learning based speech and speech processing; chatbot software; software for creating and generating text; software for generating artificial intelligence and machine learning algorithms; software for enabling artificial intelligence, machine learning, and deep learning in applications; software for enabling generative artificial intelligence in applications; software for development of skills and knowledge using artificial intelligence; software enabling human collaboration with artificial intelligence, machine learning, and deep learning to generate content; software using artificial intelligence for generating content; software enabling human collaboration with artificial intelligence to generate content; software using artificial intelligence for computers, computer software, and computer systems; software using artificial intelligence for the creation, conversion, manipulation, translation, storage, management, recognition, and/or transfer of documents, images, text, video, sounds, speech and/or data; software using artificial intelligence for video and computers games; software using artificial intelligence for search engines; software using artificial intelligence for online digital advertising; software using artificial intelligence for providing news and information online; software using artificial intelligence for privacy management; software using artificial intelligence for business, business management, marketing, e-commerce applications, customer relationship management, enterprise business management, financial management, and accounting; software using artificial intelligence for data governance and management; software using artificial intelligence for cloud computing; software using artificial intelligence for communication and data exchange on computer networks and global computer networks; software using artificial intelligence for communication and telecommunication services; software using artificial intelligence for accessing computer networks and global communications networks; software using artificial intelligence for computer programming, cyber security, computer security, application security, hardware security, network security, infrastructure security, operational security, cloud and hybrid environment security, internet of things security, database security, endpoint security, security for internet-connected devices, information security, internet security, information technology, computer science and technology, privacy, data security and management, cyber security strategies and countering security threats, security risk management and response, security architecture, computer and network threat detection and remediation, security management and solutions, identity and access management, security attacks and responses, security disaster recovery, and exploit analysis; software using artificial intelligence for creating web applications, data syncing, data storage, archiving, and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data visualization, data processing, data analysis, data security, access, administration and management of computer applications and computer hardware, computer application distribution, and for transmission of voice, data, images, audio, video, and information, and for content management, online project management, predictive digital marketing, online conferences, meetings, demonstrations, tours, presentations and interactive discussions; software using artificial intelligence for operating system programs and utilities, virtual desktop platform and server applications, computer maintenance, document and database management, data transmission, computer network security, and malware protection; software using artificial intelligence for providing information in the field of computers, computer software, and computer systems. Software as a service (SAAS) services in the nature of artificial intelligence, machine learning, and deep learning software; software as a service (SAAS) services featuring software for generative artificial intelligence; software as a service (SAAS) services in the nature of generative artificial intelligence software; software as a service (SAAS) services featuring software for generative artificial intelligence services; providing temporary use of on-line non-downloadable applications using generative artificial intelligence; software as a service (SAAS) services in the nature of providing software featuring generative artificial intelligence; providing temporary use of on-line non-downloadable applications featuring generative artificial intelligence; providing temporary use of on-line non-downloadable software and applications, namely, artificial intelligence, machine learning, and deep learning applications; providing temporary use of on-line non-downloadable software, namely, applications featuring generative artificial intelligence; software as a service (SAAS) services featuring software using artificial intelligence for machine learning; software as a service (SAAS) services featuring software using artificial intelligence and artificial intelligence techniques to generate content; software as a service (SAAS) services featuring software that enables users to create user-generated content; software as a service (SAAS) services featuring software using artificial intelligence to generate content; software as a service (SAAS) services featuring software for synthesizing human speech and text; software as a service (SAAS) services featuring software for processing, generating, understanding, and analyzing natural language; software as a service (SAAS) services featuring software for machine learning based speech and speech processing; software as a service (SAAS) services in the nature of chatbot software; software as a service (SAAS) services featuring software for creating and generating text; software as a service (SAAS) services featuring software for generating artificial intelligence and machine learning algorithms; software as a service (SAAS) services featuring software for enabling artificial intelligence, machine learning, and deep learning in applications; software as a service (SAAS) services featuring software for enabling generative artificial intelligence in applications; software as a service (SAAS) services featuring software for development of skills and knowledge using artificial intelligence; software as a service (SAAS) services featuring software enabling human collaboration with artificial intelligence, machine learning, and deep learning to generate content; software as a service (SAAS) services featuring software using artificial intelligence for generating content; software as a service (SAAS) services featuring software enabling human collaboration with artificial intelligence to generate content; software as a service (SAAS) services featuring software using artificial intelligence for computers, computer software, and computer systems; software as a service (SAAS) services featuring software using artificial intelligence for the creation, conversion, manipulation, translation, storage, management, recognition, and/or transfer of documents, images, text, video, sounds, speech and/or data; software as a service (SAAS) services featuring software using artificial intelligence for video and computers games; software as a service (SAAS) services featuring software using artificial intelligence for search engines; software as a service (SAAS) services featuring software using artificial intelligence for online digital advertising; software as a service (SAAS) services featuring software using artificial intelligence for providing news and information online; software as a service (SAAS) services featuring software using artificial intelligence for privacy management; software as a service (SAAS) services featuring software using artificial intelligence for business, business management, marketing, e-commerce applications, customer relationship management, enterprise business management, financial management, and accounting; software as a service (SAAS) services featuring software using artificial intelligence for data governance and management; software as a service (SAAS) services featuring software using artificial intelligence for cloud computing; software as a service (SAAS) services featuring software using artificial intelligence for communication and data exchange on computer networks and global computer networks; software as a service (SAAS) services featuring software using artificial intelligence for communication and telecommunication services; software as a service (SAAS) services featuring software using artificial intelligence for accessing computer networks and global communications networks; software as a service (SAAS) services featuring software using artificial intelligence for computer programming, cyber security, computer security, application security, hardware security, network security, infrastructure security, operational security, cloud and hybrid environment security, internet of things security, database security, endpoint security, security for internet-connected devices, information security, internet security, information technology, computer science and technology, privacy, data security and management, cyber security strategies and countering security threats, security risk management and response, security architecture, computer and network threat detection and remediation, security management and solutions, identity and access management, security attacks and responses, security disaster recovery, and exploit analysis; software as a service (SAAS) services featuring software using artificial intelligence for creating web applications, data syncing, data storage, archiving, and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data visualization, data processing, data analysis, data security, access, administration and management of computer applications and computer hardware, computer application distribution, and for transmission of voice, data, images, audio, video, and information, and for content management, online project management, predictive digital marketing, online conferences, meetings, demonstrations, tours, presentations and interactive discussions; software as a service (SAAS) services featuring software using artificial intelligence for operating system programs and utilities, virtual desktop platform and server applications, computer maintenance, document and database management, data transmission, computer network security, and malware protection; software as a service (SAAS) services featuring software using artificial intelligence for providing information in the field of computers, computer software, and computer systems; application service provider (asp) services namely hosting computer application software of others.

Produits et services

(1) Software; applications; mobile applications; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence applications; software featuring generative artificial intelligence; applications featuring generative artificial intelligence; software, namely, artificial intelligence, machine learning, and deep learning applications; software, namely, applications featuring generative artificial intelligence; software using artificial intelligence for machine learning; software using artificial intelligence and artificial intelligence techniques to generate content; software that enables users to create user-generated content; software using artificial intelligence to generate content; software for synthesizing human speech and text; software for processing, generating, understanding, and analyzing natural language; software for machine learning based speech and speech processing; chatbot software; software for creating and generating text; software for generating artificial intelligence and machine learning algorithms; software for enabling artificial intelligence, machine learning, and deep learning in applications; software for enabling generative artificial intelligence in applications; software for development of skills and knowledge using artificial intelligence; software enabling human collaboration with artificial intelligence, machine learning, and deep learning to generate content; software using artificial intelligence for generating content; software enabling human collaboration with artificial intelligence to generate content; software using artificial intelligence for computers, computer software, and computer systems; software using artificial intelligence for the creation, conversion, manipulation, translation, storage, management, recognition, and/or transfer of documents, images, text, video, sounds, speech and/or data; software using artificial intelligence for video and computers games; software using artificial intelligence for search engines; software using artificial intelligence for online digital advertising; software using artificial intelligence for providing news and information online; software using artificial intelligence for privacy management; software using artificial intelligence for business, business management, marketing, e-commerce applications, customer relationship management, enterprise business management, financial management, and accounting; software using artificial intelligence for data governance and management; software using artificial intelligence for cloud computing; software using artificial intelligence for communication and data exchange on computer networks and global computer networks; software using artificial intelligence for communication and telecommunication services; software using artificial intelligence for accessing computer networks and global communications networks; software using artificial intelligence for computer programming, cyber security, computer security, application security, hardware security, network security, infrastructure security, operational security, cloud and hybrid environment security, internet of things security, database security, endpoint security, security for internet-connected devices, information security, internet security, information technology, computer science and technology, privacy, data security and management, cyber security strategies and countering security threats, security risk management and response, security architecture, computer and network threat detection and remediation, security management and solutions, identity and access management, security attacks and responses, security disaster recovery, and exploit analysis; software using artificial intelligence for creating web applications, data syncing, data storage, archiving, and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data visualization, data processing, data analysis, data security, access, administration and management of computer applications and computer hardware, computer application distribution, and for transmission of voice, data, images, audio, video, and information, and for content management, online project management, predictive digital marketing, online conferences, meetings, demonstrations, tours, presentations and interactive discussions; software using artificial intelligence for operating system programs and utilities, virtual desktop platform and server applications, computer maintenance, document and database management, data transmission, computer network security, and malware protection; software using artificial intelligence for providing information in the field of computers, computer software, and computer systems (1) Software as a service (SAAS) services in the nature of artificial intelligence, machine learning, and deep learning software; software as a service (SAAS) services featuring software for generative artificial intelligence; software as a service (SAAS) services in the nature of generative artificial intelligence software; software as a service (SAAS) services featuring software for generative artificial intelligence services; providing temporary use of on-line non-downloadable applications using generative artificial intelligence; software as a service (SAAS) services in the nature of providing software featuring generative artificial intelligence; providing temporary use of on-line non-downloadable applications featuring generative artificial intelligence; providing temporary use of on-line non-downloadable software and applications, namely, artificial intelligence, machine learning, and deep learning applications; providing temporary use of on-line non-downloadable software, namely, applications featuring generative artificial intelligence; software as a service (SAAS) services featuring software using artificial intelligence for machine learning; software as a service (SAAS) services featuring software using artificial intelligence and artificial intelligence techniques to generate content; software as a service (SAAS) services featuring software that enables users to create user-generated content; software as a service (SAAS) services featuring software using artificial intelligence to generate content; software as a service (SAAS) services featuring software for synthesizing human speech and text; software as a service (SAAS) services featuring software for processing, generating, understanding, and analyzing natural language; software as a service (SAAS) services featuring software for machine learning based speech and speech processing; software as a service (SAAS) services in the nature of chatbot software; software as a service (SAAS) services featuring software for creating and generating text; software as a service (SAAS) services featuring software for generating artificial intelligence and machine learning algorithms; software as a service (SAAS) services featuring software for enabling artificial intelligence, machine learning, and deep learning in applications; software as a service (SAAS) services featuring software for enabling generative artificial intelligence in applications; software as a service (SAAS) services featuring software for development of skills and knowledge using artificial intelligence; software as a service (SAAS) services featuring software enabling human collaboration with artificial intelligence, machine learning, and deep learning to generate content; software as a service (SAAS) services featuring software using artificial intelligence for generating content; software as a service (SAAS) services featuring software enabling human collaboration with artificial intelligence to generate content; software as a service (SAAS) services featuring software using artificial intelligence for computers, computer software, and computer systems; software as a service (SAAS) services featuring software using artificial intelligence for the creation, conversion, manipulation, translation, storage, management, recognition, and/or transfer of documents, images, text, video, sounds, speech and/or data; software as a service (SAAS) services featuring software using artificial intelligence for video and computers games; software as a service (SAAS) services featuring software using artificial intelligence for search engines; software as a service (SAAS) services featuring software using artificial intelligence for online digital advertising; software as a service (SAAS) services featuring software using artificial intelligence for providing news and information online; software as a service (SAAS) services featuring software using artificial intelligence for privacy management; software as a service (SAAS) services featuring software using artificial intelligence for business, business management, marketing, e-commerce applications, customer relationship management, enterprise business management, financial management, and accounting; software as a service (SAAS) services featuring software using artificial intelligence for data governance and management; software as a service (SAAS) services featuring software using artificial intelligence for cloud computing; software as a service (SAAS) services featuring software using artificial intelligence for communication and data exchange on computer networks and global computer networks; software as a service (SAAS) services featuring software using artificial intelligence for communication and telecommunication services; software as a service (SAAS) services featuring software using artificial intelligence for accessing computer networks and global communications networks; software as a service (SAAS) services featuring software using artificial intelligence for computer programming, cyber security, computer security, application security, hardware security, network security, infrastructure security, operational security, cloud and hybrid environment security, internet of things security, database security, endpoint security, security for internet-connected devices, information security, internet security, information technology, computer science and technology, privacy, data security and management, cyber security strategies and countering security threats, security risk management and response, security architecture, computer and network threat detection and remediation, security management and solutions, identity and access management, security attacks and responses, security disaster recovery, and exploit analysis; software as a service (SAAS) services featuring software using artificial intelligence for creating web applications, data syncing, data storage, archiving, and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data visualization, data processing, data analysis, data security, access, administration and management of computer applications and computer hardware, computer application distribution, and for transmission of voice, data, images, audio, video, and information, and for content management, online project management, predictive digital marketing, online conferences, meetings, demonstrations, tours, presentations and interactive discussions; software as a service (SAAS) services featuring software using artificial intelligence for operating system programs and utilities, virtual desktop platform and server applications, computer maintenance, document and database management, data transmission, computer network security, and malware protection; software as a service (SAAS) services featuring software using artificial intelligence for providing information in the field of computers, computer software, and computer systems; application service provider (asp) services namely hosting computer application software of others

Produits et services

(1) Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Downloadable computer software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Downloadable computer software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Downloadable computer software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Downloadable computer software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Downloadable computer software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Downloadable computer software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare (1) Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Providing on-line non-downloadable software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Providing on-line non-downloadable software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Providing on-line non-downloadable software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Providing on-line non-downloadable software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare

Produits et services

Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Downloadable computer software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Downloadable computer software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Downloadable computer software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Downloadable computer software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Downloadable computer software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Downloadable computer software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare. Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Providing on-line non-downloadable software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Providing on-line non-downloadable software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Providing on-line non-downloadable software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Providing on-line non-downloadable software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare.

Produits et services

Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Downloadable computer software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Downloadable computer software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Downloadable computer software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Downloadable computer software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Downloadable computer software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Downloadable computer software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare. Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Providing on-line non-downloadable software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Providing on-line non-downloadable software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Providing on-line non-downloadable software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Providing on-line non-downloadable software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare.

Produits et services

Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Downloadable computer software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Downloadable computer software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Downloadable computer software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Downloadable computer software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Downloadable computer software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Downloadable computer software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Providing on-line non-downloadable software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Providing on-line non-downloadable software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Providing on-line non-downloadable software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Providing on-line non-downloadable software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare

Abrégé

Phishing protection utilizes a security identifier displayed in association with secure content. The identifier may be displayed separately for comparison. A security identifier may be generated by a user interface, local source, or remote source. Users may visually and/or physically confirm identifiers. An identifier may be a character string or QR code. Phishing attempts may be monitored, detected, and alerted during and outside a secure session. A device may modify images from a first computing device to a display monitor. A device interface may receive a first image from the first computing device. A detector may monitor the first image for counterfeit information. An alert generator may generate a security alert for counterfeit information. A combiner may combine with the first image, in response to a secure session, a secure image associated with a secure identifier and, in response to the detector detecting counterfeit secure information, the security alert.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité

Abrégé

System, methods, apparatuses, and computer program products are disclosed for injecting custom information for a server while establishing end-to-end secure communications with a client via a tunneling service. A reverse proxy receives, from a client over a first transport-layer connection, a request that includes an identifier associated with an on-premises resource. The reverse proxy determines, based on the identifier, that an error prevents forwarding of the client request to the on-premises resource. In response, the reverse proxy transmits, to an error handling service (EHS) over a second transport-layer connection, a new application-layer request comprising error handling information to enable the EHS to establish, via the reverse proxy, a secure communications channel with the client using the existing first transport-layer connection and the second transport-layer connection. The reverse proxy proxies, from the EHS and to the client, an encrypted response containing an error message.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité
• H04L 41/0631 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant l’analyse des causes profondesGestion des fautes, des événements, des alarmes ou des notifications en utilisant l’analyse de la corrélation entre les notifications, les alarmes ou les événements en fonction de critères de décision, p. ex. la hiérarchie ou l’analyse temporelle ou arborescente
• H04L 67/2895 - Traitement intermédiaire fonctionnellement situé à proximité de l'application fournisseur de données, p. ex. intermédiaire de mandataires inverses

Abrégé

A system and method for providing access control to one or more resources based on roster scoped roles includes generating, via a group management system, a group instance for a group for use in an application, the group including a plurality of group members, and receiving selection of roles for one or more of the plurality of group members. Access rights for the selected roles are retrieved from an application manifest associated with the application and an access rights list instance is generated for the group for storing a list of group members, the group member's selected roles and access rights associated with the selected roles. The access rights list instance is then stored to an access management data structure, and access to the group instance or group connected resources associated with the group is provided based on the access rights list.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité

Abrégé

The techniques disclosed herein enable systems to leverage publisher profile and reputation to detect malware and block malicious actors. This is accomplished by obtaining a description of a software application that is pending release from the publisher. The description defines the nominal functionality of the software application such as expected program behaviors and device driver accesses. The system then catalogues the actual functionality of the software application by analyzing the program code implementing the software application. Accordingly, the generative model can detect inconsistencies between the actual functionality and the nominal functionality. In response, the generative model can initiate an interaction with the publisher to resolve the inconsistency. The publisher can respond with a justification of the inconsistency which is evaluated by the generative model in accordance with a reputation score associated with the publisher. The generative model optionally approves or blocks the software application based on the reputation score.

Classes IPC  ?

• G06F 21/56 - Détection ou gestion de programmes malveillants, p. ex. dispositions anti-virus
• G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité

Abrégé

This document relates to distance-based estimation of energy propagation variation in synthetic three-dimensional scenes. For example, the disclosed implementations can detect geometric features, such as outside corners or portals, based on a distance field that identifies distances from points in a scene to the nearest geometry in the scene. Then, energy propagation variation within the scene can be estimated based on the locations of the geometric features. Energy propagation variation can be employed for a range of applications, such as deploying sampling probes within a given scene and simulating energy propagation to/from the probes within the scene.

Classes IPC  ?

• G06F 30/13 - Conception architecturale, p. ex. conception architecturale assistée par ordinateur [CAAO] relative à la conception de bâtiments, de ponts, de paysages, d’usines ou de routes

Abrégé

The present disclosure relates to methods and systems that perform probabilistic reasoning on knowledge graphs. The systems and methods use path-based simulations over a knowledge graph to convert the knowledge graph into a probabilistic graphical model that supports probabilistic reasoning on the knowledge graph. The systems and methods use the probabilistic graphical model to discover paths of the knowledge graph in response to a query.

Classes IPC  ?

• G06N 5/02 - Représentation de la connaissanceReprésentation symbolique

Abrégé

A method, computer program product, and computing system for secure speech feature extraction. A speech signal comprising content information and speaker information is received and a component of the speaker information is altered to generate an augmented voice signal. In a first neural network, first embeddings of the received voice signal are generated. In a second neural network, second embeddings of the received voice signal having minimized speaker information based on the augmented voice signal are generated. The second neural network is trained to generate the second embeddings to be similar to the first embeddings generated by the first neural network.

Classes IPC  ?

• G10L 21/013 - Adaptation à la hauteur tonale ciblée
• G10L 17/02 - Opérations de prétraitement, p. ex. sélection de segmentReprésentation ou modélisation de motifs, p. ex. fondée sur l’analyse linéaire discriminante [LDA] ou les composantes principalesSélection ou extraction des caractéristiques
• G10L 17/04 - Entraînement, enrôlement ou construction de modèle
• G10L 17/18 - Réseaux neuronaux artificielsApproches connexionnistes

Abrégé

A method, computer program product, and computing system for securely transmitting voice signals. A speech signal including a content component and a speaker component of a first voice is received at an encoder. The speaker component of the speech signal is processed, using machine learning, to generate a speaker embedding. The content component of the voice signal is processed, using machine learning and based at least on the speaker embedding, to generate a content embedding having minimized speaker information. The content embedding is transmitted to a decoder for restoring the received speech signal.

Classes IPC  ?

• G10L 19/24 - Codecs à débit variable, p. ex. pour générer différentes qualités en utilisant une représentation évolutive comme le codage hiérarchique ou le codage par couches

Abrégé

Systems for dynamically synthesizing widgets for chart modification are provided. A method can include receiving data indicating a dataset of structured data. The data can be provided by a user through a user interface (UI). The UI can display the data on a chart. A request can be received by the UI. The request can be provided by the user. The request can indicate an alteration to a representation of the data on the chart. A widget can be dynamically synthesized based on the request. The widget can be operable to alter the representation of the data on the chart based on user interaction with the widget. The UI can present the widget on the UI alongside the chart. The chart can be altered based on user interaction with the widget.

Classes IPC  ?

• G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
• G06F 8/30 - Création ou génération de code source
• G06F 40/40 - Traitement ou traduction du langage naturel

Abrégé

A data processing system implements receiving a first request to collaboratively author a mixed reality experience with a vision-language model planner, the mixed reality experience comprising an interactive guide for performing a task involving a complex multipart object; obtaining 3D object geometry information for the complex multipart object; obtaining a description of the task to be performed including a plurality of subtasks each associated with a user action to be performed on a respective part of the complex multipart object; constructing a prompt to the model using a prompt construction unit, the prompt instructing the model to generate a task list based on the geometry information and the description of the task to be performed; providing the prompt as an input to the model to obtain the task list; and generating content for the mixed reality experience using the task list in response to a second request to execute the mixed reality experience.

Classes IPC  ?

• G06T 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie
• G10L 15/26 - Systèmes de synthèse de texte à partir de la parole

Abrégé

A method for user intent evaluation includes receiving recorded speech of a human user. One or more attention indicators are detected in an image of the human user. Using a trained command recognition model, a command confidence is estimated indicating a confidence that the recorded human speech includes a command for a smart assistant computing system. Based at least in part on detecting the one or more attention indicators, and the command confidence exceeding a command confidence threshold, the human user is classified as intending to interact with the smart assistant computing system.

Classes IPC  ?

• G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
• G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains
• G06V 40/20 - Mouvements ou comportement, p. ex. reconnaissance des gestes
• G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
• G10L 15/25 - Reconnaissance de la parole utilisant des caractéristiques non acoustiques utilisant la position des lèvres, le mouvement des lèvres ou l’analyse du visage

Abrégé

Aspects of the disclosure include methods and systems for optimizing content service through state-machine based goal programming. An exemplary method can include receiving, from a client, a card request for structured data cards and determining a state of the client. The method can include, based on the state of the client, selecting for inferencing, via a finite state machine, one of a first model and a second model, determining, from the respective model selected for inferencing, a ranking of a plurality of candidate structured data cards, and providing, to the client, a card response including one or more structured data cards of the plurality of candidate structured data cards according to the ranking.

Classes IPC  ?

• G06F 16/906 - GroupementClassement

Abrégé

A data processing system implements receiving, via a user interface of a client device of a user, a first prompt requesting an image to be generated for the user by a generative model, the first prompt including textual content. The system further implements constructing a second prompt by a prompt construction unit as an input to the generative model, the prompt construction unit constructing the second prompt by extracting an artifact and a theme from the textual content and appending the artifact and the theme to an instruction string, the instruction string comprising instructions to the generative model to determine a design template matching the artifact, and to generate the image by replacing visual element(s) of the design template based on the theme while preserving a graphic layout of the design template; providing the image to the client device; and causing the user interface to present the image.

Classes IPC  ?

• G06T 11/60 - Édition de figures et de texteCombinaison de figures ou de texte
• G06F 40/40 - Traitement ou traduction du langage naturel
• G06T 7/12 - Découpage basé sur les bords
• G06T 11/00 - Génération d'images bidimensionnelles [2D]

Abrégé

User sensing dynamic camera resolution control is implemented by adapting camera settings and/or image processing based on sensed conditions, such as detected changes in an environment indicating user presence while approaching or retreating from a computing device. Dynamic adaptation of camera settings and/or image processing can conserve power and/or reduce user wait time by preparing to resume operation and greet a user as the user arrives at a computing device. An image processor uses sensed conditions to increment and decrement camera power consumption and/or image processing power consumption by dynamically switching between modes, such as powering and/or processing a single subpixel, multiple subpixels, a single pixel, multiple pixels, multiple pixels in a heatmap mode, low, medium, and high/full resolution, at one or fields of view, based on a series of events detected using the camera sensor alone or combined with other sensors, such as a sound sensor (e.g., microphone).

Classes IPC  ?

• H04N 23/611 - Commande des caméras ou des modules de caméras en fonction des objets reconnus les objets reconnus comprenant des parties du corps humain
• G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains
• H04N 23/65 - Commande du fonctionnement de la caméra en fonction de l'alimentation électrique
• H04N 23/667 - Changement de mode de fonctionnement de la caméra, p. ex. entre les modes photo et vidéo, sport et normal ou haute et basse résolutions
• H04N 23/80 - Chaînes de traitement de la caméraLeurs composants

Abrégé

Systems and techniques for facilitating unified multichannel communication are provided. The described systems and techniques improve communication technology through an encompassing, channel-agnostic approach which unifies disparate communication modes into a singular coherent thread. A unified multichannel communication (“UMC”) service of a UMC platform can initialize a UMC thread for a UMC session, where the UMC thread can be used to facilitate unified multichannel communication.

Classes IPC  ?

• H04L 51/56 - Messagerie unifiée, p. ex. interactions entre courriel, messagerie instantanée ou messagerie IP convergente [CPM]
• H04L 51/046 - Interopérabilité avec d'autres applications ou services réseau
• H04L 51/06 - Adaptation des messages aux exigences du terminal ou du réseau
• H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation

Abrégé

This disclosure describes utilizing a generative document system to dynamically build and provide generative search result documents. The generative document system utilizes an aggregated framework that leverages one or more large generative models (LGMs). For example, the aggregated framework includes three stages where local processes are applied to generative outputs from LGMs, with each stage building upon the generative inputs from previous stages. The generative document system uses the aggregated framework to create generative search result documents based on search queries and their corresponding search result links. These generative search result documents provide interactive, intuitive, comprehensive, and flexible curation of answers that address the respective search queries.

Classes IPC  ?

• G06F 16/9538 - Présentation des résultats des requêtes
• G06F 16/93 - Systèmes de gestion de documents

Abrégé

A system includes a stored counter value and a stored boot manifest including a manifest type flag. A manifest type of the boot manifest is determined based on the manifest type flag, a tenancy mode is determined based on a parity of the counter value, a first boot is executed if the manifest type is a first manifest type and the tenancy mode is a first tenancy mode, a second boot flow is executed if the manifest type is the first manifest type and the tenancy mode is a second tenancy mode, a third boot flow is executed if the manifest type is a second manifest type and the tenancy mode is the first tenancy mode, and a fourth boot flow is executed if the manifest type is the second manifest type and the tenancy mode is the second tenancy mode.

Classes IPC  ?

• G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
• H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
• H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système

Abrégé

A computing device includes a flexible display supported by first and second display-supporting frames that are rotatably coupled via a spine. Each display-supporting frame comprises a backplate opposite the flexible display. Each display-supporting frame is coupled to a respective translation mechanism, and each translation mechanism is configured to translate the respective display-supporting frame relative to the spine as the display-supporting frame is rotated relative to the spine. A respective moveable slider plate for each display-supporting frame is biased into contact with the spine to cover at least a portion of an aperture at least partially defined by a leading edge of the respective backplate of the display-supporting frame and the spine.

Classes IPC  ?

• G06F 1/16 - Détails ou dispositions de structure

Abrégé

A foldable computing device comprises a first frame comprising a first magnet assembly and a second frame rotatably coupled to the first frame via a hinge. The second frame comprises a second magnet assembly operatively configured for rotation with respect to the second frame. The second magnet assembly attracts the first magnet assembly of the first frame when the first frame and the second frame are in a closed configuration. The second frame further comprises an actuator operatively configured to rotate the second magnet assembly to thereby reduce a magnetic force between the first magnet assembly and the second magnet assembly and allow the foldable computing device to open.

Classes IPC  ?

• G06F 1/16 - Détails ou dispositions de structure

Abrégé

Systems and methods are provided for interactively highlighting a region as pixel data on a screen and automatically retrieving context data associated with content of the highlighted region for contextual notetaking. The highlighted region includes at least a part of one or more windows and one or more applications associated with the one or more windows. The disclosed technology determines a context associated with content of the highlighted region and automatically retrieves context data that are contextually relevant to the content. Notes data are generated based on an aggregate of the highlighted content, window-specific context data, application-specific context data, and user-specific context data. A notetaking application retrieves stored the notes data from a notes database and displays the notes data for recall and for use. The contextual notetaking enables the user reducing a burden of performing manual operations for notetaking and utilizing notes that are enriched relevant data by context.

Classes IPC  ?

• G06F 3/0354 - Dispositifs de pointage déplacés ou positionnés par l'utilisateurLeurs accessoires avec détection des mouvements relatifs en deux dimensions [2D] entre le dispositif de pointage ou une partie agissante dudit dispositif, et un plan ou une surface, p. ex. souris 2D, boules traçantes, crayons ou palets
• G06F 3/038 - Dispositions de commande et d'interface à cet effet, p. ex. circuits d'attaque ou circuits de contrôle incorporés dans le dispositif
• G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
• G06V 30/14 - Acquisition d’images
• G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux

Abrégé

In implementations of the subject matter as described herein, there is provided a method for forgery detection of a face image. Subsequent to inputting a face image, it is detected whether a blending boundary due to the blend of different images exists in the face image, and then a corresponding grayscale image is generated based on a result of the detection, where the generated grayscale image can reveal whether the input face image is formed by blending different images. If a visible boundary corresponding to the blending boundary exists in the generated grayscale image, it indicates that the face image is a forged image; on the contrary, if the visible boundary does not exist in the generated grayscale image, it indicates that the face image is a real image.

Classes IPC  ?

• G06V 40/16 - Visages humains, p. ex. parties du visage, croquis ou expressions
• G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
• G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 40/40 - Détection d’usurpation, p. ex. détection d’activité

Abrégé

Various example user interface (UI) mechanisms are described herein, each of which enables a user to efficiently and intuitively manipulate a trained generative model at runtime. Among other things, the described techniques have applications in the field of game design or application design more generally, enabling a game or application developer to easily generate extended application (e.g., gameplay) sequences. Other applications include guided image or audio synthesis, or other forms of guided output generation (e.g., synthesized code, simulated or actual industrial outputs, engineering data, cybersecurity data etc.).

Classes IPC  ?

• G06N 3/0475 - Réseaux génératifs
• A63F 13/60 - Création ou modification du contenu du jeu avant ou pendant l’exécution du programme de jeu, p. ex. au moyen d’outils spécialement adaptés au développement du jeu ou d’un éditeur de niveau intégré au jeu
• G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs

Abrégé

A method for verifying an application structured to execute on a client device. A challenge request is sent to the application. A candidate challenge answer is received from the application in response to the challenge request, which is then provided as input to a verification computation with a challenge input. Based on an output of the verification computation, it is determined that the candidate challenge answer is generated by providing the challenge input to a challenge computation. Based on the determination that the candidate challenge answer is generated by providing the challenge input to the challenge computation, the application is verified.

Classes IPC  ?

• G06F 21/44 - Authentification de programme ou de dispositif

Abrégé

Techniques are described herein that are capable of performing AI-based conversion of a natural language prompt (“prompt”) to a system-specific segment definition using entity reduction and renaming. The prompt requests data that satisfies a search criterion from a database that stores entities having entity names. Each entity name not satisfying a relevance criterion is changed based on content of the respective entity. An AI model is caused to determine a first subset of the entity names that is relevant to the prompt by providing a first AI prompt, the prompt, and the entity names as first inputs to the AI model. The AI model is caused to convert the prompt to the system-specific segment definition, which conforms to a particular format, by providing a second AI prompt, the prompt, information regarding the particular format, and the first subset of the entity names as second inputs to the AI model.

Classes IPC  ?

• G06F 16/21 - Conception, administration ou maintenance des bases de données
• G06F 40/295 - Reconnaissance de noms propres
• G06F 40/40 - Traitement ou traduction du langage naturel

Abrégé

Technologies described herein relate to a computer-implemented environment that includes multiple bots with which a user can interact. At least one generative model is employed to identify which bot of the multiple bots is to respond to a user communication set forth by the user in the computer-implemented environment.

Classes IPC  ?

• G06F 16/3329 - Formulation de requêtes en langage naturel

Abrégé

The present disclosure proposes a method, apparatus and computer-readable medium for action decision based on self-tune mechanism. A set of previous states associated with a target application and a set of previous rewards corresponding to the set of previous states may be obtained. An action in natural language for the target application may be generated based on the set of previous states and the set of previous rewards. It may be verified with a set of predefined rules whether the action is reasonable. Action code in computer language corresponding to the action may be generated in response to verifying that the action is reasonable. The target application may be caused to execute the action code.

Classes IPC  ?

• G06F 9/445 - Chargement ou démarrage de programme
• G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
• G06N 20/00 - Apprentissage automatique

Abrégé

Techniques are described herein that are capable of performing AI-based conversion of a natural language prompt ("prompt") to a system-specific segment definition using entity reduction and renaming. The prompt requests data that satisfies a search criterion from a database that stores entities having entity names. Each entity name not satisfying a relevance criterion is changed based on content of the respective entity. An AI model is caused to determine a first subset of the entity names that is relevant to the prompt by providing a first AI prompt, the prompt, and the entity names as first inputs to the AI model. The AI model is caused to convert the prompt to the system-specific segment definition, which conforms to a particular format, by providing a second AI prompt, the prompt, information regarding the particular format, and the first subset of the entity names as second inputs to the AI model.

Classes IPC  ?

• G06F 16/2452 - Traduction des requêtes
• G06F 16/334 - Exécution de requêtes

Abrégé

The disclosed concepts relate to leveraging a generative language model for interactive constraint solving. For instance, a generative language model can be prompted to generate a constraint data structure that represents a user preference expressed in natural language. The constraint data structure can be parsed to extract constraint parameters that can be programmatically solved by a constraint solver. The generative language model can also be prompted to generate constraint-checking code that can be invoked by the constraint solver.

Classes IPC  ?

• G06F 40/30 - Analyse sémantique
• G06F 17/11 - Opérations mathématiques complexes pour la résolution d'équations
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"

Abrégé

A method for verifying an application structured to execute on a client device. A challenge request is sent to the application. A candidate challenge answer is received from the application in response to the challenge request, which is then provided as input to a verification computation with a challenge input. Based on an output of the verification computation, it is determined that the candidate challenge answer is generated by providing the challenge input to a challenge computation. Based on the determination that the candidate challenge answer is generated by providing the challenge input to the challenge computation, the application is verified.

Classes IPC  ?

• G06F 21/44 - Authentification de programme ou de dispositif
• H04L 9/40 - Protocoles réseaux de sécurité

Abrégé

A data processing system implements receiving a first request to collaboratively author a mixed reality experience with a vision-language model planner, the mixed reality experience comprising an interactive guide for performing a task involving a complex multipart object; obtaining 3D object geometry information for the complex multipart object; obtaining a description of the task to be performed including a plurality of subtasks each associated with a user action to be performed on a respective part of the complex multipart object; constructing a prompt to the model, the prompt instructing the model to generate a task list based on the geometry information and the description of the task to be performed; providing the prompt as an input to the model to obtain the task list; and generating content for the mixed reality experience using the task list in response to a second request to execute the mixed reality experience.

Classes IPC  ?

• G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
• G06F 3/03 - Dispositions pour convertir sous forme codée la position ou le déplacement d'un élément
• G06F 3/16 - Entrée acoustiqueSortie acoustique
• G06F 9/44 - Dispositions pour exécuter des programmes spécifiques
• G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
• G06F 16/9032 - Formulation de requêtes
• G06F 40/20 - Analyse du langage naturel
• G06T 19/20 - Édition d'images tridimensionnelles [3D], p. ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
• G06V 20/20 - ScènesÉléments spécifiques à la scène dans les scènes de réalité augmentée
• G09B 23/00 - Modèles à usage scientifique, médical ou mathématique, p. ex. dispositif en vraie grandeur pour la démonstration

Produits et services

(1) Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Downloadable computer software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Downloadable computer software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Downloadable computer software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Downloadable computer software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Downloadable computer software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Downloadable computer software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare (1) Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Providing on-line non-downloadable software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Providing on-line non-downloadable software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Providing on-line non-downloadable software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Providing on-line non-downloadable software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare

Produits et services

Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Downloadable computer software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Downloadable computer software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Downloadable computer software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Downloadable computer software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Downloadable computer software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Downloadable computer software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Downloadable computer software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for speech recognition, speech dictation, natural language processing, and ambient speech processing in the healthcare field; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for locating, analyzing, processing, accessing, summarizing, creating, editing, managing, securing, and transmitting data, documents, and medical information; Providing on-line non-downloadable software for using artificial intelligence (AI) for analyzing medical records, electronic health records, and point of care data to improve clinical productivity; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for summarizing and drafting medical communications, transcribing notes, automating notetaking, generating text, producing medical documentation, automating workflows and tasks, summarizing evidence, summarizing medical consultations, preparing and processing medical orders, and drafting referrals; Providing on-line non-downloadable software for using generative artificial intelligence (GenAI) for providing assessments and actionable medical insights to assist with the evaluation of patient information; Providing on-line non-downloadable software for providing a virtual assistant featuring generative artificial intelligence (GenAI) for automatically and accurately documenting patient encounters, communicating clinical information, and completing clinical tasks in the field of healthcare; Providing on-line non-downloadable software for integrating artificial intelligence (AI) processing capabilities with computer software applications to analyze medical data and improve workflow efficiency for medical professionals; Providing on-line non-downloadable software for providing conversational user interfaces (CUIs) featuring large language models (LLMs) and generative artificial intelligence (GenAI) to assist medical professionals in tasks, decision-making processes, communication, and analyzing data across multiple applications and the internet; Providing on-line non-downloadable software for enhancing user productivity by connecting users with information, data, content, projects, files, and documents from software applications in the field of healthcare

Produits et services

software; applications; mobile applications; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence applications; software featuring generative artificial intelligence; applications featuring generative artificial intelligence; software, namely, artificial intelligence, machine learning, and deep learning applications; software, namely, applications featuring generative artificial intelligence; software using artificial intelligence for machine learning; software using artificial intelligence and artificial intelligence techniques to generate content; software that enables users to create user-generated content; software using artificial intelligence to generate content; software for synthesizing human speech and text; software for processing, generating, understanding, and analyzing natural language; software for machine learning based speech and speech processing; chatbot software; software for creating and generating text; software for generating artificial intelligence and machine learning algorithms; software for enabling artificial intelligence, machine learning, and deep learning in applications; software for enabling generative artificial intelligence in applications; software for development of skills and knowledge using artificial intelligence; software enabling human collaboration with artificial intelligence, machine learning, and deep learning to generate content; software using artificial intelligence for generating content; software enabling human collaboration with artificial intelligence to generate content; software using artificial intelligence for computers, computer software, and computer systems; software using artificial intelligence for the creation, conversion, manipulation, translation, storage, management, recognition, and/or transfer of documents, images, text, video, sounds, speech and/or data; software using artificial intelligence for video and computers games; software using artificial intelligence for search engines; software using artificial intelligence for online digital advertising; software using artificial intelligence for providing news and information online; software using artificial intelligence for privacy management; software using artificial intelligence for business, business management, marketing, e-commerce applications, customer relationship management, enterprise business management, financial management, and accounting; software using artificial intelligence for data governance and management; software using artificial intelligence for cloud computing; software using artificial intelligence for communication and data exchange on computer networks and global computer networks; software using artificial intelligence for communication and telecommunication services; software using artificial intelligence for accessing computer networks and global communications networks; software using artificial intelligence for computer programming, cyber security, computer security, application security, hardware security, network security, infrastructure security, operational security, cloud and hybrid environment security, internet of things security, database security, endpoint security, security for internet-connected devices, information security, internet security, information technology, computer science and technology, privacy, data security and management, cyber security strategies and countering security threats, security risk management and response, security architecture, computer and network threat detection and remediation, security management and solutions, identity and access management, security attacks and responses, security disaster recovery, and exploit analysis; software using artificial intelligence for creating web applications, data syncing, data storage, archiving, and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data visualization, data processing, data analysis, data security, access, administration and management of computer applications and computer hardware, computer application distribution, and for transmission of voice, data, images, audio, video, and information, and for content management, online project management, predictive digital marketing, online conferences, meetings, demonstrations, tours, presentations and interactive discussions; software using artificial intelligence for operating system programs and utilities, virtual desktop platform and server applications, computer maintenance, document and database management, data transmission, computer network security, and malware protection; software using artificial intelligence for providing information in the field of computers, computer software, and computer systems. Software as a service (SAAS) services in the nature of artificial intelligence, machine learning, and deep learning software; software as a service (SAAS) services featuring software for generative artificial intelligence; software as a service (SAAS) services in the nature of generative artificial intelligence software; software as a service (SAAS) services featuring software for generative artificial intelligence services; providing temporary use of on-line non-downloadable applications using generative artificial intelligence; software as a service (SAAS) services in the nature of providing software featuring generative artificial intelligence; providing temporary use of on-line non-downloadable applications featuring generative artificial intelligence; providing temporary use of on-line non-downloadable software and applications, namely, artificial intelligence, machine learning, and deep learning applications; providing temporary use of on-line non-downloadable software, namely, applications featuring generative artificial intelligence; software as a service (SAAS) services featuring software using artificial intelligence for machine learning; software as a service (SAAS) services featuring software using artificial intelligence and artificial intelligence techniques to generate content; software as a service (SAAS) services featuring software that enables users to create user-generated content; software as a service (SAAS) services featuring software using artificial intelligence to generate content; software as a service (SAAS) services featuring software for synthesizing human speech and text; software as a service (SAAS) services featuring software for processing, generating, understanding, and analyzing natural language; software as a service (SAAS) services featuring software for machine learning based speech and speech processing; software as a service (SAAS) services in the nature of chatbot software; software as a service (SAAS) services featuring software for creating and generating text; software as a service (SAAS) services featuring software for generating artificial intelligence and machine learning algorithms; software as a service (SAAS) services featuring software for enabling artificial intelligence, machine learning, and deep learning in applications; software as a service (SAAS) services featuring software for enabling generative artificial intelligence in applications; software as a service (SAAS) services featuring software for development of skills and knowledge using artificial intelligence; software as a service (SAAS) services featuring software enabling human collaboration with artificial intelligence, machine learning, and deep learning to generate content; software as a service (SAAS) services featuring software using artificial intelligence for generating content; software as a service (SAAS) services featuring software enabling human collaboration with artificial intelligence to generate content; software as a service (SAAS) services featuring software using artificial intelligence for computers, computer software, and computer systems; software as a service (SAAS) services featuring software using artificial intelligence for the creation, conversion, manipulation, translation, storage, management, recognition, and/or transfer of documents, images, text, video, sounds, speech and/or data; software as a service (SAAS) services featuring software using artificial intelligence for video and computers games; software as a service (SAAS) services featuring software using artificial intelligence for search engines; software as a service (SAAS) services featuring software using artificial intelligence for online digital advertising; software as a service (SAAS) services featuring software using artificial intelligence for providing news and information online; software as a service (SAAS) services featuring software using artificial intelligence for privacy management; software as a service (SAAS) services featuring software using artificial intelligence for business, business management, marketing, e-commerce applications, customer relationship management, enterprise business management, financial management, and accounting; software as a service (SAAS) services featuring software using artificial intelligence for data governance and management; software as a service (SAAS) services featuring software using artificial intelligence for cloud computing; software as a service (SAAS) services featuring software using artificial intelligence for communication and data exchange on computer networks and global computer networks; software as a service (SAAS) services featuring software using artificial intelligence for communication and telecommunication services; software as a service (SAAS) services featuring software using artificial intelligence for accessing computer networks and global communications networks; software as a service (SAAS) services featuring software using artificial intelligence for computer programming, cyber security, computer security, application security, hardware security, network security, infrastructure security, operational security, cloud and hybrid environment security, internet of things security, database security, endpoint security, security for internet-connected devices, information security, internet security, information technology, computer science and technology, privacy, data security and management, cyber security strategies and countering security threats, security risk management and response, security architecture, computer and network threat detection and remediation, security management and solutions, identity and access management, security attacks and responses, security disaster recovery, and exploit analysis; software as a service (SAAS) services featuring software using artificial intelligence for creating web applications, data syncing, data storage, archiving, and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data visualization, data processing, data analysis, data security, access, administration and management of computer applications and computer hardware, computer application distribution, and for transmission of voice, data, images, audio, video, and information, and for content management, online project management, predictive digital marketing, online conferences, meetings, demonstrations, tours, presentations and interactive discussions; software as a service (SAAS) services featuring software using artificial intelligence for operating system programs and utilities, virtual desktop platform and server applications, computer maintenance, document and database management, data transmission, computer network security, and malware protection; software as a service (SAAS) services featuring software using artificial intelligence for providing information in the field of computers, computer software, and computer systems; application service provider (asp) services namely hosting computer application software of others

Abrégé

A system, method, and computer-readable media for executing applications for radio interface controller (RIC) management are disclosed. The system includes far-edge datacenters configured to execute a radio access network (RAN) function and a real-time RIC; near-edge datacenters configured to execute a core network function and a near-real-time RIC or a non-real-time RIC; and a central controller. The central controller is configured to: receive inputs of application requirements, hardware constraints, and a capacity of first and second computing resources at the far-edge datacenters and near-edge datacenters; enumerate a plurality of feasible combinations of application locations and configurations that satisfy the application requirements and hardware constraints; incrementally allocate a quant of the first or second computing resources to a feasible combination that would produce a greatest utility from the quant based on a utility function; and deploy each of the plurality of applications.

Classes IPC  ?

• G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]

Abrégé

The description relates to adaptive sampling of three-dimensional virtual scenes. For instance, sampling assignments can be determined based on an energy propagation variation field having energy propagation variation values indicating rates at which energy propagation changes as a function of location within a three-dimensional synthetic scene. Sampling probes can be deployed according to the sampling assignments, and then each sampling probe can be employed to simulate energy propagation within the three-dimensional synthetic scene. The simulations can produce parameters suitable for subsequent rendering of energy signals for applications such as video games.

Classes IPC  ?

• G06T 15/50 - Effets de lumière
• H04N 13/351 - Affichage simultané

Abrégé

The disclosed concepts relate to leveraging a generative language model for interactive constraint solving. For instance, a generative language model can be prompted to generate a constraint data structure that represents a user preference expressed in natural language. The constraint data structure can be parsed to extract constraint parameters that can be programmatically solved by a constraint solver. The generative language model can also be prompted to generate constraint-checking code that can be invoked by the constraint solver.

Classes IPC  ?

• G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence

Abrégé

The present disclosure relates to a socket apparatus that includes a socket cavity sized and configured to receive a chip package. The socket apparatus further includes a plurality of base contacts on a bottom surface of the socket apparatus, the plurality of base contacts being mountable on a circuit board. The socket apparatus further includes a plurality of pins positioned across a top surface of the socket apparatus opposite the bottom surface, each pin of the plurality of pins having a location that is referenced relative to a datum reference. The datum reference is positioned in a first corner of the socket apparatus to improve alignment accuracy between socket pins and package pads.

Classes IPC  ?

• G01R 1/04 - BoîtiersOrganes de supportAgencements des bornes
• G01R 31/28 - Test de circuits électroniques, p. ex. à l'aide d'un traceur de signaux
• H05K 1/18 - Circuits imprimés associés structurellement à des composants électriques non imprimés

Abrégé

When a content modification is detected, a set of properties corresponding to that content modification is identified, and a timestamp is generated indicating when the content modification was made. An index request including the properties and timestamp are provided to an index ingestion pipeline. Each component in the index ingestion pipeline generates a separate timestamp indicating when the index request was received at the corresponding component. The timestamps generated by each of the components in the index ingestion pipeline are sent through the index ingestion pipeline, along with the properties, to an output component which outputs an index entry that can be stored in a search index. The output component also generates an index latency output that can be provided to a latency processing system. The index latency output indicates the latency introduced by each of the components in the index ingestion pipeline, and also identifies the properties of the content modification. An action signal is generated based upon the index latency output.

Classes IPC  ?

• G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
• G06F 9/54 - Communication interprogramme
• G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p. ex. des interruptions ou des opérations d'entrée–sortie

Abrégé

A generative artificial intelligence (AI) system has a plurality of different AI models. A prompt is provided to each of the different AI models and each of the different AI models generates an output. The outputs from the AI models are provided to an orchestrator. The orchestrator selects from among the different model outputs to generate a response. A cache system generates a cache entry, corresponding to the query, for each of the model outputs. When a subsequent query is received, the cache is searched based upon the subsequent query to determine whether any matching cache entries are found. The individual model outputs corresponding to a matching cache entry are output to the individual AI models for validation.

Classes IPC  ?

• G06F 12/0877 - Modes d’accès à la mémoire cache
• G06F 16/2455 - Exécution des requêtes

Abrégé

Methods and systems for detecting anomalous software behavior by monitoring frequency spectrums emanating from an electronic device are provided. A method includes storing frequency spectrum profiles for software applications and operational modes on the device. During execution of a software application, the real-time emanating frequency spectrum is measured and compared to the stored spectrum profile for that application and operational mode. Deviations between the real-time and reference spectrums indicate anomalous behavior from unknown software executing. The device determines a deviation exists and performs remedial actions like alerting the user, disconnecting from the network, shutting down, or switching application execution to another device. Frequency profiles are measured for new applications installed and stored to keep the data updated. Monitoring real-time frequency spectrums emanating from a device provides a computationally lightweight technique for detecting malicious software behavior without requiring complex analysis of application code.

Classes IPC  ?

• G06F 21/56 - Détection ou gestion de programmes malveillants, p. ex. dispositions anti-virus
• H04L 27/36 - Circuits de modulationCircuits émetteurs

Abrégé

A combined hyperparameter and proxy model tuning method is described. The method involves multiple search iterations. In each search iteration, candidate hyperparameters are considered. An initial (‘seed’) hyperparameter is determined, and used to train one or more first proxy models on a target dataset. From the first proxy model(s), one or more first synthetic datasets are sampled. A first evaluation model is fitted to each first synthetic dataset, for each candidate hyperparameter, enabling each candidate hyperparameter to be scored. Based on the respective scores assigned to the candidate hyperparameters, a candidate hyperparameter is selected and used to train one or more second proxy models on the target dataset

Classes IPC  ?

• G06N 20/00 - Apprentissage automatique

Abrégé

A data processing system includes: a processor; and a memory comprising programming instructions for execution by the processor alone or in combination with other processors, to implement a service to generate a work as specified by a user. The service includes: a service-side component of a User Interface (UI) to receive user input about the work from the user, the user input including an initial prospective description of the work that the user intends to generate using the system and a set of parameters for the work; a prompt generator to generate prompts for a Large Language Model (LLM) based on the user input to generate both an outline for the work and a proposed version of the work, the prompt generator further to generate additional prompts to the LLM to update either the outline or the proposed version of the work based a user editing of the other of the outline or the proposed version of the work; and an Application Programming Interface to deliver prompts to the LLM and receive responses from the LLM for presentation in the UI.

Classes IPC  ?

• G06N 3/0475 - Réseaux génératifs

Abrégé

A computing system including one or more processing devices configured to receive a stabilizer channel sequence of three or more stabilizer channels and respective fault sets. The one or more processing devices compute a lower-bound channel distance of the stabilizer channel sequence at least in part by computing lower-bound channel distances of compositions of adjacent pairs of stabilizer channels. For a stabilizer channel and a plurality of partition timestep counts, computing the lower-bound channel distance further includes receiving an indication of whether there exists a partition of the fault set of that stabilizer channel that has that partition timestep count and for which the stabilizer channel is time-local. Computing the lower-bound channel distance further includes selecting a lowest value among the lower-bound channel distances of the compositions and each of the partition timestep counts that has a time-locality-satisfying partition. The one or more processing devices output the lower-bound channel distance.

Classes IPC  ?

• G06N 10/70 - Correction, détection ou prévention d’erreur quantique, p. ex. codes de surface ou distillation d’état magique

Abrégé

A computing system including one or more processing devices configured to identify one or more severe hook faults in a stabilizer channel. Identifying the severe hook faults includes receiving a circuit channel check matrix, the columns of which indicate values of checks associated with elementary faults of the stabilizer channel. Identifying the severe hook faults further includes receiving a phenomenological channel check matrix as a sub-matrix of the circuit channel check matrix, receiving a logical effect matrix, and receiving a weight vector that indicates probability weights of the elementary faults. Based at least in part on the circuit channel check matrix, the logical effect matrix, the phenomenological channel check matrix, and the weight vector, identifying the severe hook faults further includes computing column indices of columns of the circuit channel check matrix that correspond to the severe hook faults. The processing devices output an indication of the severe hook faults.

Classes IPC  ?

• G06N 10/70 - Correction, détection ou prévention d’erreur quantique, p. ex. codes de surface ou distillation d’état magique
• G06N 10/20 - Modèles d’informatique quantique, p. ex. circuits quantiques ou ordinateurs quantiques universels
• G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit

Abrégé

In some embodiments, a collaboration feature overlays a web application by receiving a network communication that was redirected from the web application by a suffix proxy. The collaboration feature supplements or replaces activity of the web application by maintaining per-user-account activity states, deriving a shared collaboration state from the activity states, and supplying the shared collaboration state to multiple user accounts. The collaboration feature is installed without modifying the web application. The collaboration feature provides user accounts with a collaboration capability, such as shared document editing, chat rooms, shared calendars, or shared private workspaces. Some collaboration features overlay multiple web applications, even from different vendors, and some collaboration features support posting collaboratively created content to a website even when some contributors to the content are not registered users of the website. Some collaboration features impose stricter or different cybersecurity than an underlying website.

Classes IPC  ?

• H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
• G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p. ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
• H04L 9/40 - Protocoles réseaux de sécurité
• H04L 67/56 - Approvisionnement des services mandataires

Abrégé

Systems and methods for providing a guidance function for use of large language models within educational environments are provided herein. In an example, a system includes instructions to receive, from a first client device, a request to generate content within an application and initiate, by the application, a guidance function. The guidance function observes interactions between the first client device and a content generator and determines a first interaction between the first client device and the content generator. The guidance function also determines a first text portion generated based on the first interaction between the first client device and the content generator and generates a relationship between the first text portion and the first interaction between the first client device and the content generator. The guidance function may also store the relationship between the first text portion and the first interaction.

Classes IPC  ?

• G09B 5/02 - Matériel à but éducatif à commande électrique avec présentation visuelle du sujet à étudier, p. ex. en utilisant une bande filmée
• G06F 40/279 - Reconnaissance d’entités textuelles