Systems and methods are provided for implementing adaptable embedded search engine functionality. In an aspect, a shared SERP system receives a user search query from a first search utility among a plurality of search utilities, which is associated with corresponding apps that are different from each other. A router of the shared SERP system provides the user search query and location information to a first query builder among one or more query builders of the shared SERP system. The first query builder constructs a query request corresponding to the user search query, based on the provided user search query and location information. A first query executor among one or more query executors of the shared SERP system executes the query request to produce search results. A component renderer of the shared SERP system renders one or more UX components within the first SERP, based on the search results.
Polynucleotide sequencing generates multiple reads of a polynucleotide molecule. Many or all of the reads contain errors. Trace reconstruction takes multiple reads generated by a polynucleotide sequencer and uses those multiple reads to reconstruct accurately the nucleotide sequence of the polynucleotide molecule. Some reads may contain errors that cannot be corrected. Thus, there may be reads that can be used throughout their entire length and other reads that have indeterminant errors which cannot be corrected. Rather than discarding the entire read when an indeterminant error is found, the portion of the read with the error is skipped and the sequence of the read following the error is used to reconstruct the trace. The amount of the read skipped is determined by the location of subsequence after the error that matches a consensus sequence of the other reads. Analysis resumes at a location determined by the location of the match.
G16B 40/00 - ICT specially adapted for biostatisticsICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
The described technology provides a method including selecting a physical SFT entry to be victimized, the physical SFT entry being one of a base SFT entry and an extra SFT entry of a logical SFT entry in a snoop filter (SFT) and CPU CPU GPU consolidating the base SFT entry and the extra SFT entry into one physical entry.
G06F 12/0831 - Cache consistency protocols using a bus scheme, e.g. with bus monitoring or watching means
G06F 12/0891 - Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches using clearing, invalidating or resetting means
4.
AGENT-BASED SEARCHING OVER HETEROGENEOUS DATA SOURCES
Searching heterogeneous cybersecurity data sources is described. A natural language search enables searching across available data sources, independent of underlying storage architectures or query languages. This capability leverages multiple task-specific agents, large language models, and data map representation-based approaches, and enables integration of new data sources into the search process with minimal additional computing resources. The searching includes determining a data map representation for available data sources (which might have different storage architectures or query languages), which indicates relationships between the available data sources. Query intent associated with a query is determined. A query intent task is determined by mapping the query intent to a relevant data source according to the data map representation. A search agent parameterized for searching the relevant data source executes the query intent task. The result of this executed query intent task is used to augment a response to the query.
This disclosure describes utilizing a generative document system to create generative search results documents using generative artificial intelligence (AI) models and dynamically determining which one of the generative search results documents to provide in response to a search query. For example, in response to receiving a search query, the generative document system obtains search link results (e.g., website links and corresponding grounding information) for the search query and utilizes this information with multiple generative AI models to generate various types of generative search results documents. Additionally, the generative document system generates and utilizes a generative document arbitration model to determine, based on the search link results, which of the generative search results documents to provide in response to the search query.
Methods, apparatuses, and products for runtime firmware updates using hotpatching, including: storing, in a runtime buffer, a firmware update patch comprising an updated code segment for a firmware module loaded into system memory for execution; adding, to the firmware module and at a location corresponding to a code segment updated by the updated code segment, a redirect command directed to the updated code segment; and wherein the redirect command, when executed, causes the updated code segment to be executed instead of the code segment.
Techniques are described herein that are capable of performing a multi-vector correlation using threat and anomaly analyses to assess a real-time security threat. A supervised AI model is caused to determine a first extent to which relationships between more than two vectors in a multi-vector representation, which indicate telemetry associated with a machine, correspond to first reference relationships associated with a known security threat. An unsupervised AI model is caused to determine a second extent to which the relationships differ from second reference relationships associated with a machine type of the machine. A security score is generated by combining indications of the first and second extents. A security action is performed as a result of the security score satisfying a security threat criterion.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
8.
SYSTEMS AND METHODS FOR TARGET COMMUNICATION ITEMS HAVING CONTEXTUAL TITLES DISTINCT FROM RELATED COMMUNICATION ITEMS
Technology is disclosed to programmatically determine and generate, for a target communication item, a contextual title that is relevant to a user, optimally formatted for ease of indexing and use by certain software applications, and easy for the user to consume. The contextual title is generated based on a comparison of the target communication item and related communication items. In this manner, the contextual title generated for the target communication item is different from existing contextual titles of the related communication items, yet related enough to associate the target communication item to certain related communication items. In this manner, contextual titles are generated without a user having to open or edit metadata associated with the communication item, thereby conserving bandwidth associated with a user engaging with high-bandwidth content from the target communication item and battery associated with consuming and editing the document.
Systems and methods for resolving a performance bottleneck of a query search to improve search results are provided. In particular, a computing device may receive a user search query from a user, generate query alteration candidates based on the user search query using an index-based language model, determine whether the user search query includes a bottleneck term that is likely to cause the performance bottleneck of the query search, wherein the bottleneck term includes one or more words or phrases, optimize, in response to determination that the user search query includes the bottleneck term, the query alteration candidates to resolve the performance bottleneck, update the index-based language model by updating confidence scores associated with the query alteration candidates, generate search results based on the optimized query alteration candidates, and provide the search results to the user.
Tensile stress in a glass substrate of an optical storage medium is reduced by pre-stressing the substrate in compression to counteract thermally- and inertially-induced tensile stresses experienced during write operations using a pulsed laser. In a first embodiment, a uniform compressive stress distribution is realized in the medium by performing write operations in an enclosure that is positively pressurized by a gas. In a second embodiment using a disc-shaped optical storage medium, compressive forces are directed radially inward using circumferentially-located mechanical engagement members. A third embodiment uses a metal tension strip that is heat-treated to induce tensile hoop stress in the strip. The metal tension strip functions as a circumferential compression band around a disc-shaped optical storage medium. Axially-directed forces can be applied to support the center of the disc in the second and third embodiments to mitigate against buckling from the radially-inward directed forces.
G11B 33/14 - Reducing influence of physical parameters, e.g. temperature change, moisture, dust
G11B 7/00 - Recording or reproducing by optical means, e.g. recording using a thermal beam of optical radiation, reproducing using an optical beam at lower powerRecord carriers therefor
G11B 7/0037 - Recording, reproducing or erasing systems characterised by the shape of the carrier with discs
An electronic record input system (ERIS) may detect historical entities in the electronic record, the historical entities corresponding to the context and corresponding to first input fields of the electronic record. The ERIS may identify a next input field of the electronic record based on the historical entities by executing a predictive model on the historical entities, wherein the next input field corresponds to a next entity in the context, the next input field is different from the first input fields. The ERIS may generate one or more suggested actions for guiding the collection of the next entity corresponding to the next input field by executing a generative artificial intelligence model on the next input field and the historical entities. The ERIS may present the one or more suggested actions using the user computing device.
The description relates to enhancing component and device reliability by analyzing stored margin data relating to the component. One example can obtain first margin data relating to a component from a first time and obtain second margin data relating to the component from a subsequent second time. The example can compare the first margin data to the second margin data to identify a change in a condition of the component.
A computerized method detects and mitigates regression errors in software services. Error log data associated with a current version of the service is obtained from a data store. The error log data is transformed into a first group of error log vectors using a model, wherein the first group of error log vectors represents semantic meaning of the error logs. A second group of error log vectors associated with a previous version of the service is obtained. Based on semantic similarity, the first group and the second group of error log vectors are clustered and, based on the clustering, a vector cluster that includes error log vectors from the first group and no error log vectors from the second group is identified as a regression vector cluster. Regression data associated with the regression vector cluster is generated and a regression mitigation action is performed using the generated regression data.
Implementations for capturing user activity as memory for question-answering are provided. One example includes a computing system (100) comprising: processing circuitry (102) and memory (104) storing instructions that, during execution, cause the processing circuitry (102) to: receive a query (130); perform semantic searching on an L2 index (118) comprising a database of event summaries (400) based on the query (130) to retrieve an L2 answer (500) comprising one or more relevant event summaries; generate one or more L1 answers (502) based on the L2 answer (500) using an L1 index (110) comprising a database of screen summaries (300) associated with a plurality of L0 screenshot images (106), wherein each of the one or more L1 answers (502) comprises relevant screen summaries (300) corresponding to L0 screenshot images (106) associated with a respective relevant event summary; pass the query (130) and the one or more L1 answers (502) to a large language model (120) to generate an answer (132) to the query (130); and output the answer (132) to the query (130).
Decoupling of telemetry data production from network transmission during network congestion in a processor-based system is disclosed. The processor-based system includes processor cores (“cores”) that can each execute computer program instructions to perform tasks. To avoid the issue of analyzing telemetry data relating to the cores collected for a given epoch that may include missing and thus incomplete telemetry data, such as due to network congestion, a telemetry data system in the processor-based system is configured to track timing of receipt of telemetry data packets. If any telemetry data packets have not been timely received for an expected epoch, an epoch status for such epoch is recorded as having incomplete telemetry data for such epoch. This ensures complete telemetry data received for a given epoch is analyzed to more accurately control performance in the processor-based system.
Examples of the present disclosure describe systems and methods for non-disruptively hibernating and resuming a guest environment using a network virtual service client. In examples, when a guest environment is hibernated, a network virtual service client provides an instruction to a virtual network interface card to set the device power state of the virtual network interface card to a low power state. The network virtual service client disables the communication channels used by the network virtual service client and saves the operating state of the virtual network interface card. When the guest environment is resumed, the network virtual service client provides an instruction to set the device power state of the virtual network interface card to a full power state. The network virtual service client reenables the communication channels used by the network virtual service client and restores the operating state of the virtual network interface card.
A data processing system implements prompting a first GenAI model to label a dataset into preference pairs based on a task and preference judgement criteria; using a second GenAI model to generate an initial reward model (RM) by modeling a reward score difference for each preference pair as a reward distribution curve that ranks each preference pair; training adapters of the second model to iteratively train the initial RM by: identifying on the curve a first portion including first pairs hard for the first model to correctly label, and a second portion including positive pairs ranked higher than the first pairs, and updating the curve for a subsequent iteration RM based on an improved dataset including the positive pairs and human annotated data generated from the first pairs; and fine-tuning the first model based on either a last iteration RM or an improved dataset associated with the last iteration RM.
Efficiently replacing software breakpoint instructions in processor-based devices is disclosed. In this regard, in one exemplary embodiment, a processor-based device is provided. The processor-based device comprises a system memory and a processor. The processor comprises a breakpoint slip register (BSR) configured to store an instruction of a software process that was replaced in the system memory by a software breakpoint instruction, and further comprises a breakpoint slip enable (BSE) indicator. The processor is configured to, during execution of the software process, execute the software breakpoint instruction. The processor is further configured to, responsive to executing the software breakpoint instruction, transfer program control to a debugger. The processor is also configured to, upon program control returning from the debugger, determine that the BSE indicator is set. The processor is additionally configured to, responsive to determining that the BSE indicator is set, execute the instruction stored in the BSR.
Methods, systems, and computer storage media for providing a modular cybersecurity platform are described. The modular cybersecurity platform is implemented using a modular cybersecurity engine that operates based on an analytical framework for dynamic data analysis and data management in a data intelligence system. In particular, the analytical framework is based on complementary modular components that are designed to interoperate in the modular cybersecurity engine. The modular cybersecurity engine includes a modular distributed system, a credential detection system, and a credential semantic graph system. The modular cybersecurity engine supports cybersecurity and sensitive data management scenarios that can empower investigators in various investigations, and provide automated flows that are highly scalable and support different types of functionality (e.g., priority embedding pipeline, credential scanning, and credential semantic graph analysis). The utility of the modular cybersecurity engine is demonstrated by its wide-ranging application in addressing complex cybersecurity challenges and sensitive data management tasks.
Some embodiments detect infeasible scheduling requests, such as overlapping do-not-move bookings with a given resource required at different locations, bookings with insufficient travel time, or other enumerated examples. Some embodiments utilize retrieval augmented generation or language model function invocation or both to summarize infeasibility patterns, or to explain scheduling decisions, or to do both. Some embodiments utilize virtual bookings to produce a partial schedule instead of declining to produce any schedule which involves conflicts. Some embodiments partition a scheduling problem into smaller problems using an eligibility graph, or using clusters computed from location data and shift assignment exploration, or both.
A computerized method detects and mitigates regression errors in software services. Error log data associated with a current version of the service is obtained from a data store. The error log data is transformed into a first group of error log vectors using a model, wherein the first group of error log vectors represents semantic meaning of the error logs. A second group of error log vectors associated with a previous version of the service is obtained. Based on semantic similarity, the first group and the second group of error log vectors are clustered and, based on the clustering, a vector cluster that includes error log vectors from the first group and no error log vectors from the second group is identified as a regression vector cluster. Regression data associated with the regression vector cluster is generated and a regression mitigation action is performed using the generated regression data.
This invention relates to a method and system for Active Multi-Preference Optimization (AMPO) in training language models. The method involves generating multiple candidate responses for a given query and selecting a subset of responses that are most informative for training. The selection process includes identifying a highest-reward response as a positive example and employing strategies such as clustering and weighted selection to choose negative responses. The selected responses are used to compute a weighted contrastive loss function, which updates the model's parameters to improve alignment with human preferences. This approach enhances training efficiency by reducing computational overhead and improving model performance through targeted data selection and optimization.
The techniques describe dynamic content-aware data sampling that adjusts a sampling rate of data associated with a service based on the content of the data. More specifically, if the data to be logged indicates that the service is operating normally, then the sampling rate is adjusted lower as the logged data has limited purpose provided the service is likely not experiencing an issue. In contrast, if the data indicates that the service is operating abnormally, then the sampling rate is adjusted higher as the logged data has elevated purpose provided the service may be experiencing an issue. The dynamic content-aware data sampling is implemented using program code generated by an artificial intelligence agent (e.g., a generative language model) based on service owner requirements, as well as historical data patterns and/or usage patterns.
Methods, systems, and computer storage media for providing data security posture management using an application discovery engine in a security management system. Application discovery supports identifying and mapping various applications within a computing environment. In particular, application discovery can be provided as part of security management operations to assess security posture of applications, identify vulnerabilities, and ensure compliance with regulations. In operation, application discovery data associated with a plurality computing resources of a computing environment is accessed. An annotated application discovery graph comprising a plurality of entities that represent the plurality of computing resources is generated. The annotated application discovery graph is deployed to support generating security postures for computing environments. A request is received for a security posture of the computing environment. A security posture visualization that includes an application discovery graph annotation is generated. The security posture visualization is communicated to cause display of the security posture visualization.
A method for calibrated touch sensing on an electronic device comprises: (a) scanning driven electrodes of a touch sensor while recording signal from sensory electrodes of the touch sensor; (b) storing the signal in a signal matrix; (c) for each element in the signal matrix that is lower than a predetermined threshold, adjusting a corresponding element in the calibration matrix based at least partly on a value of the element in the signal matrix and on a value of the corresponding element in the calibration matrix; (d) for each element in the signal matrix that is above the predetermined threshold, estimating the corresponding element in the calibration matrix based at least partly on one or more elements neighboring the corresponding element in the calibration matrix; and (e) returning a calibrated signal value based at least partly on corresponding values in the signal and calibration matrices.
A server computing device generates training data based upon an identifier for a device, a timestamp, and a label received from a developer computing device. The server computing device trains a computer-implemented machine learning (ML) model based upon the training data. The server computing device also generates client configuration data for the ML model that specifies transformations that are to be applied to values in order to generate input values for the ML model. The server computing device deploys ML assets to client computing devices, the ML assets comprising the ML model and the client configuration data. The client computing devices execute the ML model using input values derived via transformations of (local) values produced by the client computing devices and transmit telemetry data to the server computing device. The server computing device updates the ML assets based upon the telemetry data.
The description relates to enhancing component and device reliability by analyzing stored margin data relating to the component. One example can obtain first margin data relating to a component from a first time and obtain second margin data relating to the component from a subsequent second time. The example can compare the first margin data to the second margin data to identify a change in a condition of the component.
Methods, computer systems, and computer-storage media are provided for facilitating distributed encoding in a remote desktop environment. In embodiments, a representation of graphical data is provided to a first video encoder associated with a video driver of a remote desktop server. The first video encoder may encode the graphical data to generate base-encoded graphical data. Thereafter, a representation of the base-encoded graphical data is provided to a second video encoder associated with a remote access protocol stack in a terminal service of the remote desktop server. The second video encoder may encode the base-encoded graphical data to generate fully-encoded graphical data. Such fully-encoded graphical data is transmitted to a remote desktop client device.
Systems and methods are provided for sorting cells with distinct cell designs for characterizing a library of the cell designs. The present disclosure uses randomized sorting rules associated with bins and pseudo-random numbers to counts the cells with measured fluorescence values in one of the bins. A mean fluorescence value for a cell design group may be determined based on a ratio of cell counts of the cells associated with the cell design group across the bins. Unlike the traditional histogram-based sorting that use a mean fluorescence value of a bin, the disclosed technology determines mean fluorescence values of cell design groups for characterizing libraries of the cell design group. Use of the mean fluorescence values with unbiased “sort-seq” and a de-multiplexed sequencing using the mean fluorescence values enables characterizing libraries of cell designs with improved accuracy over traditional use of discrete histograms.
Systems and methods discussed herein generate a semantic-domain constraint corpus that detects data errors within columns of any data table, without requiring domain-experts to manually specify constraints on a per-table basis. A large body of semantic-domain constraint candidates is generated from test datasets, after which high-quality constraints within those candidates are identified. The systems and methods further pare the remaining semantic-domain constraints down based on size and false-positive rate constraints. The resulting semantic-domain constraint corpus can be applied to any structured dataset to automatically detect errors within columns of that dataset.
The disclosure herein describes a system for measuring probability of influence in digital communications to determine if communication content originated in a person's own prior knowledge or new information more recently obtained from interaction with communications of others. An estimated probability a new communication by a first user comes from the same distribution as prior communications of the first user are generated using multidimensional statistics on embeddings representing the communications. A second estimated probability that the new communication comes from the same distribution as communication(s) of a second user that were accessible to the first user are generated. If the second probability is greater than the first probability, the new communication is more likely influenced by exposure of the first user to the second user's communications rather than the first user's own historical knowledge. An influence attribution recommendation is generated, including an influence attribution or other recommended action.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
Devices, systems, and methods for post-quantum (PQ) secure (PQS) communications are provided. A method includes authenticating, by a device and with a first server, using a legacy device identity, receiving and installing, by the device, a firmware upgrade that provides the device an ability to communicate in a PQS manner, establishing a PQS communication channel between the device and a second server, mutually authenticating, by the device and with the second server, using a PQ identity (PQI) of the device, the PQI different from the legacy identity, and responsive to successful mutual authentication, communicating between the device and the second server, using the PQS communication channel.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & 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; computer operating system software; hardware; computers; tablets; laptops; tablet computers; laptop computers; mobile computers; mobile phones; smart phones; portable electronic devices for receiving and reading text, images and sound through wireless internet access reader for e-books and other electronic publications; computer peripherals; wireless computer peripherals; mobile communications modules for use with tablet computers; headphones; audio speakers; computer keyboards; electronic musical keyboards; computer mouse; webcams; digital pens; power cords; battery chargers; electrical cables and cord sets; electronic docking stations; computer docking stations; adapters for use with computers and computer peripherals; USB hardware devices; carrying cases and holders for electronic equipment; computer accessories. software; software as a service (SaaS); applications; mobile applications; application service provider (asp) services; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence services; 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.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & 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; computer operating system software; hardware; computers; tablets; laptops; tablet computers; laptop computers; mobile computers; mobile phones; smart phones; portable electronic devices for receiving and reading text, images and sound through wireless internet access reader for e-books and other electronic publications; computer peripherals; wireless computer peripherals; mobile communications modules for use with tablet computers; headphones; audio speakers; computer keyboards; electronic musical keyboards; computer mouse; webcams; digital pens; power cords; battery chargers; electrical cables and cord sets; electronic docking stations; computer docking stations; adapters for use with computers and computer peripherals; USB hardware devices; carrying cases and holders for electronic equipment; computer accessories. software; software as a service (SaaS); applications; mobile applications; application service provider (asp) services; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence services; 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.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & 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; computer operating system software; hardware; computers; tablets; laptops; tablet computers; laptop computers; mobile computers; mobile phones; smart phones; portable electronic devices for receiving and reading text, images and sound through wireless internet access reader for e-books and other electronic publications; computer peripherals; wireless computer peripherals; mobile communications modules for use with tablet computers; headphones; audio speakers; computer keyboards; electronic musical keyboards; computer mouse; webcams; digital pens; power cords; battery chargers; electrical cables and cord sets; electronic docking stations; computer docking stations; adapters for use with computers and computer peripherals; USB hardware devices; carrying cases and holders for electronic equipment; computer accessories. software; software as a service (SaaS); applications; mobile applications; application service provider (asp) services; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence services; 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.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & 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; computer operating system software; hardware; computers; tablets; laptops; tablet computers; laptop computers; mobile computers; mobile phones; smart phones; portable electronic devices for receiving and reading text, images and sound through wireless internet access reader for e-books and other electronic publications; computer peripherals; wireless computer peripherals; mobile communications modules for use with tablet computers; headphones; audio speakers; computer keyboards; electronic musical keyboards; computer mouse; webcams; digital pens; power cords; battery chargers; electrical cables and cord sets; electronic docking stations; computer docking stations; adapters for use with computers and computer peripherals; USB hardware devices; carrying cases and holders for electronic equipment; computer accessories software; software as a service (SaaS); applications; mobile applications; application service provider (asp) services; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence services; 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.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & 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; computer operating system software; hardware; computers; tablets; laptops; tablet computers; laptop computers; mobile computers; mobile phones; smart phones; portable electronic devices for receiving and reading text, images and sound through wireless internet access reader for e-books and other electronic publications; computer peripherals; wireless computer peripherals; mobile communications modules for use with tablet computers; headphones; audio speakers; computer keyboards; electronic musical keyboards; computer mouse; webcams; digital pens; power cords; battery chargers; electrical cables and cord sets; electronic docking stations; computer docking stations; adapters for use with computers and computer peripherals; USB hardware devices; carrying cases and holders for electronic equipment; computer accessories software; software as a service (SaaS); applications; mobile applications; application service provider (asp) services; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence services; 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.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & 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; computer operating system software; hardware; computers; tablets; laptops; tablet computers; laptop computers; mobile computers; mobile phones; smart phones; portable electronic devices for receiving and reading text, images and sound through wireless internet access reader for e-books and other electronic publications; computer peripherals; wireless computer peripherals; mobile communications modules for use with tablet computers; headphones; audio speakers; computer keyboards; electronic musical keyboards; computer mouse; webcams; digital pens; power cords; battery chargers; electrical cables and cord sets; electronic docking stations; computer docking stations; adapters for use with computers and computer peripherals; USB hardware devices; carrying cases and holders for electronic equipment; computer accessories. software; software as a service (SaaS); applications; mobile applications; application service provider (asp) services; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence services; 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; 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; computer operating system software; hardware; computers; tablets; laptops; tablet computers; laptop computers; mobile computers; mobile phones; smart phones; portable electronic devices for receiving and reading text, images and sound through wireless internet access reader for e-books and other electronic publications; computer peripherals; wireless computer peripherals; mobile communications modules for use with tablet computers; headphones; audio speakers; computer keyboards; electronic musical keyboards; computer mouse; webcams; digital pens; power cords; battery chargers; electrical cables and cord sets; electronic docking stations; computer docking stations; adapters for use with computers and computer peripherals; USB hardware devices; carrying cases and holders for electronic equipment; computer accessories. (1) Software; software as a service (SaaS); applications; mobile applications; application service provider (asp) services; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence services; 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; 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; computer operating system software; hardware; computers; tablets; laptops; tablet computers; laptop computers; mobile computers; mobile phones; smart phones; portable electronic devices for receiving and reading text, images and sound through wireless internet access reader for e-books and other electronic publications; computer peripherals; wireless computer peripherals; mobile communications modules for use with tablet computers; headphones; audio speakers; computer keyboards; electronic musical keyboards; computer mouse; webcams; digital pens; power cords; battery chargers; electrical cables and cord sets; electronic docking stations; computer docking stations; adapters for use with computers and computer peripherals; USB hardware devices; carrying cases and holders for electronic equipment; computer accessories. (1) Software; software as a service (SaaS); applications; mobile applications; application service provider (asp) services; artificial intelligence, machine learning, and deep learning software; generative artificial intelligence; generative artificial intelligence software; generative artificial intelligence services; 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.
42.
ROUTING NETWORK TRAFFIC USING TIME ZONE INFORMATION
A DNS request is received from a requesting computing system at a DNS service. The DNS service serves the DNS request by identifying a service endpoint that is closest to the requesting computing system in terms of latency, based on a time zone in which the requesting computing system is located.
H04L 67/63 - Routing a service request depending on the request content or context
H04L 45/121 - Shortest path evaluation by minimising delays
H04L 61/4511 - Network directoriesName-to-address mapping using standardised directoriesNetwork directoriesName-to-address mapping using standardised directory access protocols using domain name system [DNS]
H04L 67/52 - Network services specially adapted for the location of the user terminal
43.
MACHINE LEARNING SYSTEM WITH MODALITY SELECTION MODEL
A computing system including one or more input devices, output devices, and processing devices. The one or more processing devices receive a user input via an input device and receive interaction context metadata associated with the user input. The interaction context metadata includes an input modality of the user input and output modalities of the one or more output devices. At a multimodal machine learning (ML) system, the one or more processing devices select one or more of the output modalities at a modality selection ML model based at least on the user input and the interaction context metadata. At one or more generative ML models, based at least on the user input, the one or more processing devices compute one or more respective model outputs that respectively have the one or more selected output modalities. The one or more processing devices output the one or more model outputs.
A data processing system with a processor and memory is configured to: implement a feature pipeline to receive telemetry data generated in response to activity in a set of applications; analyze the telemetry data using a feature extraction unit of the feature pipeline to extract feature data from the telemetry data; operate a scoring pipeline to classify the user as working onsite or remotely based on the feature data extracted from the telemetry data, the scoring pipeline utilizing a machine-learning model trained to receive feature data as an input and to output a classification indicating that the user is working onsite at a location associated with the enterprise or remotely at a location not associated with the enterprise; and allocate computing and network resources using a resource allocation unit based on the classification.
H04L 47/76 - Admission controlResource allocation using dynamic resource allocation, e.g. in-call renegotiation requested by the user or requested by the network in response to changing network conditions
H04L 43/10 - Active monitoring, e.g. heartbeat, ping or trace-route
H04L 47/2441 - Traffic characterised by specific attributes, e.g. priority or QoS relying on flow classification, e.g. using integrated services [IntServ]
45.
CAPTURING USER ACTIVITY AS MEMORY FOR QUESTION-ANSWERING
Implementations for capturing user activity as memory for question-answering are provided. One example includes a computing system comprising: processing circuitry and memory storing instructions that, during execution, cause the processing circuitry to: receive a query; perform semantic searching on an L2 index comprising a database of event summaries based on the query to retrieve an L2 answer comprising one or more relevant event summaries; generate one or more L1 answers based on the L2 answer using an L1 index comprising a database of screen summaries associated with a plurality of L0 screenshot images, wherein each of the one or more L1 answers comprises relevant screen summaries corresponding to L0 screenshot images associated with a respective relevant event summary; pass the query and the one or more L1 answers to a large language model to generate an answer to the query; and output the answer to the query.
The present disclosure relates to enabling a private connection to a Content Delivery Network (CDN). A data packet encapsulated with a tenant specific VNI is received by a driver, wherein the data packet comprising a user IP address in a source IP field and a subnet IP address in a destination IP field. The driver decapsulates the data packet to retrieve the tenant specific VNI and replaces the destination IP field with an internal IP address. The driver transmits the data packet to an edge server, wherein the data packet is processed by the edge server. The driver receives a returning data packet from the edge server comprising the internal IP address in the source IP field and the user IP address in the destination IP field. The driver replaces the source IP field with the subnet IP address and transmits the returning data packet to the edge router.
H04L 61/4511 - Network directoriesName-to-address mapping using standardised directoriesNetwork directoriesName-to-address mapping using standardised directory access protocols using domain name system [DNS]
47.
CONDITIONAL SIGNALLING OF REFERENCE PICTURE LIST MODIFICATION INFORMATION
Innovations in signaling of reference picture list (“RPL”) modification information. For example, a video encoder evaluates a condition that depends at least in part on a variable indicating a number of total reference pictures. Depending on the results of the evaluation, the encoder signals in a bitstream a flag that indicates whether an RPL is modified according to syntax elements explicitly signaled in the bitstream. A video decoder evaluates the condition and, depending on results of the evaluation, parses from a bitstream a flag that indicates whether an RPL is modified according to syntax elements explicitly signaled in the bitstream. The condition can be evaluated as part of processing for an RPL modification structure that includes the flag, or as part of processing for a slice header. The encoder and decoder can also evaluate other conditions that affect syntax elements for list entries of the RPL modification information.
H04N 19/58 - Motion compensation with long-term prediction, i.e. the reference frame for a current frame not being the temporally closest one
H04N 19/105 - Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction
H04N 19/109 - Selection of coding mode or of prediction mode among a plurality of temporal predictive coding modes
H04N 19/134 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
H04N 19/46 - Embedding additional information in the video signal during the compression process
H04N 19/503 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
H04N 19/573 - Motion compensation with multiple frame prediction using two or more reference frames in a given prediction direction
H04N 19/70 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards
H04N 19/85 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
An AR/VR headset that is configured to be worn on a user’s head. The headset includes a first sprocket, a second sprocket and a ball chain engaging the first and second sprockets. A rotating actuator engages the first sprocket such that the first sprocket rotates and the ball chain translates along the first and second sprockets when torque is applied to the rotating actuator. The ball chain applies torque to the second sprocket as the ball chain translates along the first and second sprockets. A transmission gear engages the second sprocket and rotates with the second sprocket. A first arm includes a first set of internal gear teeth, and a second arm includes a second set of internal gear teeth. The transmission gear engages the first and second sets of gear teeth such that rotation of the transmission gear moves the second arm relative to the first arm.
G06F 1/16 - Constructional details or arrangements
F16M 13/04 - Other supports for positioning apparatus or articlesMeans for steadying hand-held apparatus or articles for supporting on, or holding steady relative to, a person, e.g. by chains
49.
CODE REVIEW COMMENT GENERATION VIA INSTRUCTION PROMPTING WITH INTENT
A code review is automatically generated by a large language model given a prompt that includes code changes made to a source code program, an associated intent, and an extended context. The intent represents an issue with the code changes from a code reviewer's perspective and is predicted from a neural classifier given the code changes in a code diff format. The neural classifier is a neural encoder transformer model pre-trained on various code review datasets and fine-tuned on code diff hunks of code changes labeled with an intent.
There is provided a method that includes (a) obtaining a first voice vector that was derived from a signal of a voice that was sampled at a first sampling frequency, (b) obtaining a second voice vector that was derived from a signal of a voice that was sampled at a second sampling frequency, (c) mapping the second voice vector into a mapped voice vector in accordance with a machine learning model, and (d) comparing the first voice vector to the mapped voice vector to yield a score that indicates a probability that the first voice vector and the second voice vector originated from a same person.
A hardware memory allocator of a compute system is described. The allocator stores batches of free identifiers (IDs) as elements of a linked list in a memory external to the system, each free ID identifying a respective segment of the memory, and transfers batch(es) of free IDs from the head of the linked list to an internal buffer. The allocator then responds to memory requests by allocating free IDs from among the batch(es) of free IDs in the buffer and to memory deallocation requests by deallocating previously-allocated free IDs. The allocator transfers batches of deallocated free IDs from the buffer to the head of the linked list, wherein transferring a batch of deallocated free IDs includes selecting one of the deallocated free IDs in the buffer exclusive of the batch and storing the batch of at the memory segment identified by the selected deallocated free ID.
Techniques and systems are disclosed to perform language model prompt optimization for complex task resolution, such as for natural language prompts used with large language models (LLMs). An example method includes: forming different combinations of subtasks that accomplish some overall task; generating corresponding combinations of subprompts; producing a performance prediction of combinations of subprompts to accomplish the overall task using the language model; evaluating the performance predictions against a threshold performance condition; selecting a combination for performing the overall task that meets the threshold performance condition; executing the subprompts corresponding to the selected combination of subtasks using the language model to accomplish the overall task; and outputting a response based on a result of the executing of the subprompts.
A computing system (10) including one or more processing devices (12) configured to receive a first user input (300) at a user interface (20) of a machine learning (ML) system (30). In response to receiving the first user input, the one or more processing devices initiate a first model call (304) to a first ML model (312). During execution of the first model call, the one or more processing devices receive one or more second user inputs (302) and perform one or more second model calls (306) to a second ML model (314) to compute one or more second model outputs (310). The one or more processing devices output the one or more second model outputs to the user interface. Subsequently to outputting the one or more second model outputs, the one or more processing devices receive and output a first model output (308) computed at the first ML model in response to receiving the first user input.
Techniques and systems are disclosed to perform language model prompt optimization for complex task resolution, such as for natural language prompts used with large language models (LLMs). An example method includes: forming different combinations of subtasks that accomplish some overall task; generating corresponding combinations of subprompts; producing a performance prediction of combinations of subprompts to accomplish the overall task using the language model; evaluating the performance predictions against a threshold performance condition; selecting a combination for performing the overall task that meets the threshold performance condition; executing the subprompts corresponding to the selected combination of subtasks using the language model to accomplish the overall task; and outputting a response based on a result of the executing of the subprompts.
A computing system including one or more processing devices configured to receive a first user input at a user interface of a machine learning (ML) system. In response to receiving the first user input, the one or more processing devices initiate a first model call to a first ML model. During execution of the first model call, the one or more processing devices receive one or more second user inputs and perform one or more second model calls to a second ML model to compute one or more second model outputs. The one or more processing devices output the one or more second model outputs to the user interface. Subsequently to outputting the one or more second model outputs, the one or more processing devices receive and output a first model output computed at the first ML model in response to receiving the first user input.
A method for recommending a mixed-precision data type configuration to accelerate execution of a language model includes identifying a plurality of mixed-precision test configurations that assign mixed-precision data types among components of the language model; measuring saliency metrics for the language model while the language model is executed in a test environment configured in accord with multiple of the plurality of mixed-precision test configurations; generating a saliency ranking that ranks the components based on the saliency metrics; and generating the recommended mixed-precision data type configuration. The recommended mixed-precision data type configuration assigns a first, reduced-precision data type to a least salient subset of the components identified in the saliency ranking while assigning a second, higher-precision data type to a most salient subset of the components identified in the saliency ranking.
Aspects herein pertain to a form of detection rule enrichment, in which a detection rule implemented in a security system is enriched with relevant context to assist actions such as reporting or remediation when the rule is triggered based on pattern matching to telemetry. A two-stage rule classification process is disclosed, where a first classifier assigns a first threat classification label (e.g., tactic) and a second classifier assigns a second threat classification label (e.g., technique). The classification is hierarchical in that second classifier uses the output of the first classifier (the first threat classification label) to determine the second threat classification label.
Methods, apparatuses, and products for database query acceleration. Methods include receiving, by a query execution platform, database query plan data from a database host, the database query plan data comprising a query execution plan and one or more database tables, translating the database query plan data into format associated with a coprocessor of the query execution platform, generating a coprocessor query execution plan for the coprocessor based on the query execution plan of the database query plan data, identifying one or more operators for executing the coprocessor query execution plan, selecting an implementation for each of the one or more operators based on one or more characteristics of data on which the one or more operators are to be applied based on the coprocessor execution plan, and executing the coprocessor query execution plan using the coprocessor.
Devices, systems, and methods for post-quantum (PQ) secure (PQS) communications are provided. A method includes authenticating, by a device and with a first server, using a legacy device identity, receiving and installing, by the device, a firmware upgrade that provides the device an ability to communicate in a PQS manner, establishing a PQS communication channel between the device and a second server, mutually authenticating, by the device and with the second server, using a PQ identity (PQI) of the device, the PQI different from the legacy identity, and responsive to successful mutual authentication, communicating between the device and the second server, using the PQS communication channel.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
Information is received indicating a plurality of files that are determined to be associated with a user's computing activity in the computing system and meet a criterion for being variants of one another. A polymorphic placeholder is generated that corresponds to the plurality of files. The plurality of files are selected based on a threshold relevance to the criterion, and the plurality of files are abstracted from underlying storage locations in the computing system.
A cooling system for a set of solid state drive (SSD) modules includes a thermal mounting frame. The thermal mounting frame includes a thermal transfer plate, and a plurality of parallel fins that project outward from a first side of the thermal transfer plate along a length dimension. The first side of the thermal transfer plate in combination with each neighboring pair of fins of the plurality of parallel fins defines a slot that accommodates a corresponding SSD module of the set of SSD modules. The thermal transfer plate includes a plurality of parallel spines in which each spine projects into a core region of a corresponding fin of the plurality of parallel fins along a base portion of the length dimension of the fin. For each slot, each fin of the neighboring pair of fins that defines the slot includes an exterior thermal transfer layer.
Methods of secure resource authorization for external identities using remote principal objects are performed by systems and devices. An external entity creates a user group and defines entitlements to an owning entity’s secure resource as a set of permissions for the group. An immutable access template with the permissions and an access policy for the secure resource are provided to the owning entity for approval. On approval, a remote principal object is created in the owner directory according to the permissions and access policy. A remote principal that is a group member requests access via an interface to the owner domain using external domain credentials. The identity of the remote principal is verified against the remote principal object by a token service. Verification causes generation and issuance of a token, with the enumerated entitlements, to the remote principal interface affecting a redirect for access to the secure resource.
Techniques are described herein that are capable of generating a content signature of a textual communication using OCR and text processing. The textual communication is rendered. Text is extracted from the rendered textual communication using OCR. Customization is removed from the text to provide a templatized version of the rendered textual communication that includes de-customized text. The de-customized text is parsed into tokens. Each token includes a respective subset of a plurality of characters. The tokens are converted into respective numbers. Each number is processed using fuzzy hash functions to provide respective hash values associated with the respective token. Representative hash values are selected for the respective fuzzy hash functions by selecting each representative hash value from the hash values that are processed using the respective fuzzy hash function. A content signature of the textual communication is generated by bitwise concatenating at least portions of the respective representative hash values.
Examples of the present disclosure describe systems and methods for selecting test combinations of hardware and software features for product validation. In examples, a test scheduler of a system receives metrics associated with a first batch of test combinations for multiple computing entities. The metrics may include data associated with a fleet prevalence and a fleet risk determined for the multiple computing entities. The scheduler provides one or more of the metrics to a machine learning algorithm. The test scheduler determines a second batch of test combinations associated with a subset of the multiple computing entities based on an output of the machine learning algorithm. The second batch of combinations may include a subset of the first batch of test combinations. The system executes the second batch of test combinations for the subset of the multiple computing entities.
A system and method for providing automated event of interest detection and reporting for software testing. The technology described herein uses natural language processing to identify events of interest based on natural language included in log files messages and/or telemetry event items of software under test. Identified events of interest are reported to one or more downstream services. In some examples, events of interest are mapped to action sequences of interest that can be replayed to reproduce events of interest without requiring event of interest criteria to be defined. In some examples, events of interest are reported to a health/status dashboard and/or a listener that responds to reported events of interest.
Some embodiments construct a set of build dependencies for a program without access to a full set of build instructions. When multiple clashing name resolutions are identified for a particular dependency, a union of the alternative versions is formed. Intermediate representations of the union of program versions, such as symbol tables, abstract syntax trees, and other internal compiler data structures, are emitted to persistent non-volatile storage, instead of using a single resolution to create temporary intermediate data to build an executable program. Security analysis and licensing analysis utilize the persisted program representations to analyze the union of multiple overlapping but different versions of the program.
Systems and methods for providing adaptive and conversational chat cards are provided herein. For example, a method may include receiving, from a client device, an indication to start a chat card exercise, determining, by a chat card engine, a source document based on the chat card exercise, and generating chat cards based on the source document. Each of the chat cards may correspond to a subtopic present in the source document. As such, the chat card engine may generate a first prompt based on a first subtopic and provide the first prompt within a first chat card to the client device. The chat card engine may receive a first query from the client device responsive to the first prompt and determine an understanding score. The chat card engine may then generate a second prompt based on the understanding score and provide the second prompt in the first chat card.
G09B 3/02 - Manually- or mechanically-operated teaching appliances working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by the student
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
A cached random access memory (RAM) counter system includes a plurality of linear feedback shift register (LFSR) counters associated with count values that maintain a unique sequence of bits associated with least-significant bits of a respective count value and a respective carry bit, a RAM circuit that stores a plurality of most-significant bits of each respective count value, a multi-bit multiplexer that receives the unique sequence of bits and the respective carry bit from each of the plurality of LFSR counters and selectively provides the unique sequence of bits and the respective carry bit for the respective count value; and an adder circuit that adds the carry bit output for the respective count value from the multi-bit multiplexer to the plurality of most-significant bits of the respective count value and provides updated most-significant bits of the respective count value for storage in the RAM circuit.
A computing system (10) including one or more input devices (16), output devices (18), and processing devices (12). The one or more processing devices receive a user input (22) via an input device and receive interaction context metadata (50) associated with the user input. The interaction context metadata includes an input modality (52) of the user input and output modalities (54) of the one or more output devices. At a multimodal machine learning (ML) system (30), the one or more processing devices select one or more of the output modalities (72) at a modality selection ML model (70) based at least on the user input and the interaction context metadata. At one or more generative ML models (74), based at least on the user input, the one or more processing devices compute one or more respective model outputs (24) that respectively have the one or more selected output modalities. The one or more processing devices output the one or more model outputs.
Aspects herein pertain to a form of detection rule enrichment, in which a detection rule implemented in a security system is enriched with relevant context to assist actions such as reporting or remediation when the rule is triggered based on pattern matching to telemetry. A two-stage rule classification process is disclosed, where a first classifier assigns a first threat classification label (e.g., tactic) and a second classifier assigns a second threat classification label (e.g., technique). The classification is hierarchical in that second classifier uses the output of the first classifier (the first threat classification label) to determine the second threat classification label.
The disclosed techniques provide a method for reducing power consumption in a logic circuit. A design of the logic circuit is provided. The logic circuit includes storage circuits that store state information and receive clock signals. Toggle activity data indicating whether the stored state information changes in response to a respective clock signal is determined. A graph that represents the toggle activity data is constructed. The graph includes nodes and edges. The nodes correspond to the storage circuits. The edges represent statistical relationships among the determined changes in the stored state information. A graph neural network to the graph is applied. The application includes generating an embedding that characterizes patterns in the toggle activity data. Via a reinforcement learning agent, control logic that selectively gates the clock signals provided to storage circuits for which the stored state information is predicted, based on the embedding, to remain unchanged is determined.
G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
A display device includes a plurality of image-forming elements arranged in a grid, including a plurality of rows and columns. A gate integrated circuit (IC) outputs a clock signal. A gate output buffer controls whether the clock signal is received by image-forming elements in a corresponding one or more rows. A source IC outputs data signals to control the plurality of image-forming elements. A block selection component controls, via a block selection signal, whether image-forming elements in a corresponding one or more columns are refreshed based at least in part on the data signals. A timing controller controls the output enable signal and the block selection signal to thereby control refresh rates for the plurality of image-forming elements, such that a first display region is refreshed at a first refresh rate, and a second display region is refreshed at a second refresh rate.
G09G 3/3266 - Details of drivers for scan electrodes
G09G 3/3275 - Details of drivers for data electrodes
G09G 3/36 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix by control of light from an independent source using liquid crystals
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer hardware; computer software; downloadable software; computer firmware; computer chips; semiconductor chips; integrated circuits; cryptographic apparatus and instruments; data security apparatus and instruments; computer hardware, software and firmware for cryptography, data encryption and decryption, authentication, digital signatures, cryptographic key generation, storage, management and lifecycle management, identity and access management, computer security and data security; computer hardware and software for implementing and managing cryptographic and post-quantum cryptographic security protocols; computer hardware and software for managing, configuring, monitoring and operating cryptographic hardware and computer security hardware; computer hardware and software for managing user access, access permissions, access controls, authentication credentials and cryptographic credentials; computer hardware and software for the development, implementation and testing of cryptographic security systems; hardware security modules [HSMs]; integrated hardware security modules [HSMs]; cryptographic appliances; computer hardware, semiconductor chips and integrated circuits incorporating cryptographic security functionality. Software as a service [SaaS]; platform as a service [PaaS]; cloud computing; providing temporary use of online non-downloadable software; software as a service [SaaS] featuring software for cryptography, data encryption and decryption, authentication, digital signatures, cryptographic key generation, storage, management and lifecycle management, identity and access management, computer security and data security; software as a service [SaaS] featuring software for managing, configuring, monitoring and operating hardware security modules [HSMs], integrated hardware security modules [HSMs], cryptographic hardware and computer security hardware; software as a service [SaaS] featuring software for implementing and managing cryptographic and post-quantum cryptographic security protocols; software as a service [SaaS] featuring software for managing user access, access permissions, access controls, authentication credentials and cryptographic credentials; software as a service [SaaS] featuring software for the development, implementation and testing of hardware security modules [HSMs] and cryptographic security systems; providing temporary use of online non-downloadable software for the aforesaid purposes.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for managing, configuring, monitoring and operating hardware security modules (HSMs) and integrated HSMs; downloadable software for cryptographic key generation, storage, management and lifecycle management, data encryption and decryption, authentication, and cryptographic security; downloadable software for managing and monitoring cryptographic hardware, computer security hardware, semiconductor chips and integrated circuits; downloadable software and firmware for implementing and managing cryptographic and post-quantum cryptography security protocols; downloadable software for identity and access management, namely, managing user access, access permissions, access controls, authentication credentials and cryptographic credentials for hardware security modules (HSMs) and cryptographic systems; computer hardware and downloadable software for the development, implementation and testing of hardware security modules and cryptographic security systems; computer hardware; computer chips; semiconductor chips; integrated circuits; computer hardware, semiconductor chips and integrated circuits incorporating cryptographic security functionality; hardware security modules (HSMs); integrated hardware security modules (HSMs); secure cryptographic devices in the nature of hardware security modules (HSMs), cryptographic appliances for encryption, digital signature, authentication and cryptographic key management Software as a service (SaaS) featuring software for managing, configuring, monitoring and operating hardware security modules (HSMs) and integrated HSMs; software as a service (SaaS) featuring software for cryptographic key generation, storage, management and lifecycle management, data encryption and decryption, authentication, and cryptographic security; software as a service (SaaS) featuring software for managing and monitoring cryptographic hardware, computer security hardware, semiconductor chips and integrated circuits; software as a service (SaaS) featuring software for implementing and managing cryptographic and post-quantum cryptography security protocols; software as a service (SaaS) featuring software for identity and access management, namely, managing user access, access permissions, access controls, authentication credentials and cryptographic credentials for hardware security modules (HSMs) and cryptographic systems; software as a service (SaaS) featuring software for the development, implementation and testing of hardware security modules and cryptographic security systems.
75.
REFERENCE FREE ALIGNMENT FOR MULTI-PREFERENCE OPTIMIZATION
The disclosed relates to a method and system for training language models using a reference-free multi-preference alignment approach. It addresses the challenge of aligning model outputs with human preferences by optimizing a contrastive loss function over selected responses. The method involves identifying candidate responses, calculating reward scores, and selecting a subset of responses for optimization. Deviations from mean reward scores are used to assign weights, and a weighted contrastive loss function is generated to update model parameters. This approach enhances model alignment by considering multiple preferences and mitigating biases toward brevity, resulting in richer and more detailed outputs.
An early stopping checking and verification process includes deriving a workload lower bound and a workload upper bound on what-if cost for an index tuning curve for a workload as what-if calls are being made. The index tuning curve represents a function that maps a number of what-if calls allocated to a percentage improvement of a best index configuration found so far. Early stopping checks are performed to identify a predetermined characteristic of the index tuning curve to determine if early stopping verification should be performed. A difference between the workload lower bound and the workload upper bound is compared to a threshold when the predetermined characteristic is detected. What-if calls for the workload are terminated based at least in part on the comparison between the difference between the workload lower bound and the workload upper bound and the predefined threshold.
Provided herein are systems, methods, machine-readable media, and the like, for bug mitigation in a software application. A method includes receiving a bug report associated with a bug, the bug report including a title, reproduction steps, and a description, generating, by a transformer model, respective embeddings of the title and the description resulting in a title embedding and a description embedding, generating a functional intent signature (FIS) of the bug based on the reproduction steps, clustering the bug based on the FIS, the title embedding and the description embedding, determining the bug belongs to a highest priority cluster, and mitigating the bug responsive to determining the bug belongs to a highest priority cluster resulting in an updated software application.
Techniques and related implementations for analyzing semantic sessions are provided. One implementation includes a computing system comprising: processing circuitry and memory storing instructions that, during execution, cause the processing circuitry to perform the steps of: receiving a plurality of screenshot images; for each of the plurality of screenshot images: identifying one or more image regions and one or more text regions on the screenshot image; and generating features for the screenshot image based on the one or more image regions and the one or more text regions using an artificial intelligence module; generating a user activity graph comprising nodes and edges, wherein the nodes correspond to the plurality of screenshot images, and wherein the edges correspond to commonalities between node pairs based on the generated features of the plurality of screenshot images; and identifying one or more node clusters from the user activity graph based on semantic relationships.
G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
G06V 10/40 - Extraction of image or video features
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A computing system generates a trained super-resolution model using correlated high-resolution and low-resolution image pairs. A first image generator produces high-resolution images, which are processed by a downscaler network to create corresponding low-resolution images. The downscaler network is trained using an initial set of image pairs. Additional high-resolution images are generated and processed by the downscaler network to produce additional low-resolution images, forming a second set of image pairs. The super-resolution model is trained using the second set of image pairs. The trained super-resolution model processes low-resolution images to generate enhanced images with improved detail and reduced artifacts. The model can be used to increase resolution of input images or refine details without changing resolution. The trained model may be deployed on different devices and applied across various rendering environments.
A63F 13/52 - Controlling the output signals based on the game progress involving aspects of the displayed game scene
G06T 3/4046 - Scaling of whole images or parts thereof, e.g. expanding or contracting using neural networks
G06T 3/4053 - Scaling of whole images or parts thereof, e.g. expanding or contracting based on super-resolution, i.e. the output image resolution being higher than the sensor resolution
G06T 5/60 - Image enhancement or restoration using machine learning, e.g. neural networks
80.
PIXEL-BASED AUTOMATED TESTING OF A NAVIGABLE SIMULATED ENVIRONMENT
A computing system for pixel-based automated testing of a navigable simulated environment includes one or more processors configured to execute, in a run-time inference phase, an application testing program. The application testing program includes a machine learning model trained to detect errors in the application under test. A screen image of the simulated environment is processed by an object detection module to determine if a key object is present in the screen image. If a key object is present in the screen image, the application testing program executes an object investigation module to generate investigation inputs to investigate the key object. If a key object is not present in the screen image, the application testing program executes an environment exploration module to generate an environment exploration action to be provided to the application under test as simulated user input.
G06F 3/04815 - Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 19/00 - Manipulating 3D models or images for computer graphics
81.
CONTEXTUAL LONG-TERM SURVIVAL OPTIMIZATION FOR CONTENT MANAGEMENT SYSTEM CONTENT SELECTION
A method involves first receiving a set of data on rewards associated with previously chosen content variant choices, selected based on an initial content variant choice model. This initial model is informed by a prior set of data. A second, updated content variant choice model is then determined based on this first set of reward data. When a request for selecting a content variant choice is received, it comes with contextual features. The method involves estimating the expected rewards for a range of content variant choices, considering these contextual features. Subsequently, a specific content variant choice is chosen based on both the updated model and the anticipated rewards. Finally, the chosen content variant is displayed on a device, responding to the initial request.
Embodiments of the present disclosure include a multipurpose multiply-accumulator (MAC) array circuit comprising one or more input memories for receiving operands and a plurality of multiply-accumulator circuits each selectively coupled to the one or more input memories to receive at least a pair of operands and generate a result. Each of the plurality of multiply-accumulator circuits receives operands from the one or more input memories independently. Additionally, selection of operands from the one or more input memories is controlled based on at least an operation and/or data types, where different operation and/or data types configure the plurality of multiply-accumulator circuits to receive different pairs of operands from the one or more input memories to execute particular operation types.
G06F 7/544 - Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state deviceMethods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using unspecified devices for evaluating functions by calculation
G06F 5/06 - Methods or arrangements for data conversion without changing the order or content of the data handled for changing the speed of data flow, i.e. speed regularising
83.
SYSTEM AND METHOD FOR MULTI-CHANNEL SPEECH PRIVACY PROCESSING
A method, computer program product, and computing system for receiving a speech signal from a single microphone. A sensitive speech component is identified from the speech signal. In response to identifying the sensitive speech component, a filtered speech signal is generated by removing the sensitive speech component from the speech signal. A voice style transfer of the speech signal is generated. Speech processing is performed on the filtered speech signal and the voice style transfer of the speech signal.
Methods, computer systems, and computer-storage media are provided for facilitating implementation of high dynamic range display technology in a remote desktop environment. In embodiments, graphical data is obtained, at a video driver of a remote desktop server, for presenting in association with a remote desktop client device. The graphical data is provided to a high dynamic range (HDR) video encoder, logically separated from the video driver, based on an indication to use the HDR video encoder to encode. Thereafter, the graphical data is encoded via the HDR video encoder, and such encoded graphical data is provided to a remote access protocol stack in a terminal service of the remote desktop server for transmitting the encoded graphical data to the remote desktop client device associated with the HDR monitor.
G06F 9/451 - Execution arrangements for user interfaces
H04N 19/186 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a colour or a chrominance component
Systems and methods for dynamically modifying a cache associated with a neural network model of a natural language generator are described. In examples, a neural network model employs a beam search algorithm at a decoder when decoding output and generating predicted output candidates. The decoder utilizes caching techniques to improve a speed at which the neural network operations. When an amount of memory utilized by one or more caches of the neural network model is determined to exceed a threshold memory size, a layer-specific portion of a cache associated with a layer of the neural network model is identified. The identified layer-specific portion of the cache can be deleted when the amount of memory utilized by the cache of the neural network model exceeds the threshold memory size. In examples, data in the cache is deduplicated and/or deleted.
Methods and systems for processing digital audio are disclosed. A digital audio file is received and linear predictive coding (LPC) analysis is performed to decompose the digital audio file into a spectral envelope signal and an excitation signal. A spread spectrum watermark is generated using a first watermark key and the spectral envelope signal, and a self-correlated watermark is generated using a second watermark key and the excitation signal. The spread spectrum watermark and the self-correlated watermark are embedded into the digital audio file. LPC synthesis is performed to combine the spectral envelope signal with the embedded spread spectrum watermark and the excitation signal with the embedded self-correlated watermark to produce a watermarked digital audio file.
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
87.
LATENT-CONTEXT ALERT CORRELATION ENGINE IN A SECURITY MANAGEMENT SYSTEM
Methods, systems, and computer storage media for providing security incident management using a latent-context alert correlation engine in a security management system. Security incident management is provided using the latent-context alert correlation engine that is operationally integrated into the security management system. In operation, first security data of a first alert and second security data of a second alert are accessed. The first alert and the second alert do not share a common entity identifiable in a security graph. Using the first security data and the second security data, a determination is made that the first alert is connected to the second alert based on a latent-context connection. The latent-context connection is a known attack path connection that indirectly connects alerts. Based on determining that the first alert is connected to the second alert, a security incident is generated for the alert. A notification comprising the security incident is communicated.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
A multi-user virtual machine (VM) system is disclosed herein. Upon receiving a user login, first persistent storage and a first network interface card (NIC) are attached to a VM, where the VM operates as a personal computing device of a first user. Upon receiving a logout request for the user, the first persistent storage and the first NIC are detached from the VM. Thereafter, a second login is received, and second persistent storage and a second NIC are attached to the VM, where the VM operates as a personal computing device of a second user.
Aspects of the present disclosure relate to computing device headset input. In examples, sensor data from one or more sensors of a headset device are processed to identify implicit and/or explicit user input. A context may be determined for the user input, which may be used to process the identified input and generate an action that affects the behavior of a computing device accordingly. As a result, the headset device is usable to control one or more computing devices. As compared to other wearable devices, headset devices may be more prevalent and may therefore enable more convenient and more intuitive user input beyond merely providing audio output.
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
H04Q 9/00 - Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
In a UDP firewall, a flow of packets is received from a public communications network, the flow of packets being sent into a private communications network. The firewall forwards a threshold amount of the flow of packets into the private communications network and validates the flow of packets in response to receiving a packet from the private communications network. In response to the validation failing the firewall blocks the flow of packets. In response to the validation succeeding the firewall allows the flow of packets to continue to be forwarded into the private communications network.
Systems and methods herein provide a disruptor validation engine and its related functions. In an aspect, a disruptor validation engine may determine disruption alerts issued by one or more disruptors, where a disruption alert indicates potential malicious activity within a tenant environment. Responsive to receiving the disruption alerts, the disruptor validation engine may generate a probability grade for a respective disruption alert. The probability grade may indicate a likelihood that the potential malicious activity triggering the disruption alert is actually malicious. The disruptor validation engine may then determine a disruption classification for the disruption alert based on a respective probability grade. Based on the disruption classification, the disruptor validation engine may generate a quality grade for the one or more disruptors indicating the validity and quality of the respective disruptor.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
A generative artificial intelligence (AI) model application programming interface (API) receives a generative AI request and routes the generative AI request to a generative AI model. The generative AI model API identifies whether the generative AI request is an asynchronous or a synchronous request and identifies a likely length of generation requested by the generative AI request. The generative AI model API evaluates the available capacity of generative AI models in a shared pool of computing system resources based upon the generative AI model type requested by the generative AI request and based upon the length of the requested generation. The generative AI model API routes the generative AI request to a generative AI model based upon the available capacity, whether the generative AI request is synchronous or asynchronous, the generative AI model type, and the length of the requested generation.
An apparatus and method for mitigating gas line absorption of a signal transmitted via a hollow core fiber by a transmitter are described. The method comprises computing an adjustment to be made to a property of the signal, the adjustment being an adjustment to change one or more of a frequency, an amplitude, and a modulation format of the signal to reduce an impact of gas line absorption on the signal. The method further comprises configuring one or more of: the transmitter to cause the adjustment to be applied to the signal during transmission of the signal, via the hollow core fiber, by the transmitter; and a receiver configured to receive the signal transmitted via the hollow core fiber, to cause the adjustment to be applied to the signal after the receiver receives the signal.
According to implementations of the disclosure, a solution for performing network simulation with an FPGA device is provided. In this solution, at least one FPGA device is configured to configure a simulation network corresponding to a computing network based on configuration information of the computing network, the simulation network including a plurality of simulation endpoints and a plurality of simulation switches. The at least one FPGA device is configured to include a plurality of endpoint modules implementing the plurality of simulation endpoints in a multiplexing mode and a switch module implementing the plurality of simulation switches in a multiplexing mode. An endpoint module of the plurality of endpoint modules is configured to: execute an application configured in the endpoint module to process a first data packet. The switch module is configured to: transmit at least a second data packet to a further endpoint module of the plurality of endpoint modules.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
95.
COORDINATING INTERACTIONS WITH HETEROGENOUS MACHINE LEARNING AGENTS
This document relates to facilitating interactions between a user and multiple agents, such as agents that provide different generative machine learning capabilities. In certain disclosed implementations, user input is received and two or more agents are selected to perform a particular task for the user. Then, interactions with the agents are coordinated on behalf of the user based on agent definitions of the selected agents. A result of the particular task is received and provided to the user. For instance, the user input can be received via a chat interface that allows the user to conduct a single chat session that involves the particular task being performed by multiple agents, thus giving the user the appearance of interacting with a single agent.
The present invention relates to a method for differential quantization of neural networks, such as large language models (LLMs), to improve operational efficiency without significant performance degradation. The method involves decomposing a neural network layer's matrix into multiple matrices using decomposition to identify significant components and insignificant components. The significant components undergo minimal or no quantization, while the less significant components undergo higher degrees of quantization. This differential quantization allows large neural networks to operate efficiently on edge devices with limited computing resources. The differential quantization technique enhances the deployment of neural networks in various hardware environments by reducing computational and memory bandwidth demands.
This disclosure describes a location-based response system that utilizes multimodal embedding and generative artificial intelligence (AI) models to generate location-based responses for user queries. For example, the location-based response system receives a real-time image, real-time location data, and a user query from a client device and determines a multimodal embedding in a multimodal vector embedding space based on the real-time image and the real-time location data. The multimodal embedding is then provided to a generative AI model, together with the data received from the client device, with instructions to generate a user query response. Upon receiving the user query response from the generative AI model, the system may provide it to the client device. Indeed, the location-based response system generates location-based responses for user queries by utilizing identified multimodal embedding and by instructing a generative AI model to respond to the user query based on the identified multimodal embedding.
The technology described herein automatically tunes large language model (LLM) prompts for improved performance. The system receives an LLM prompt as input, optimizes it, and outputs a more effective prompt. The optimization process involves converting the prompt into a hierarchical prompt tree, which organizes the prompt into distinct sections and subsections. This structured format allows for systematic refinements targeting specific components without altering the entire prompt. The system uses an actor/critic learning model, where the critic evaluates the prompts generated by the actor and provides feedback to guide future prompt generation decisions. The actor executes actions based on the feedback, continuously improving its performance. The iterative process generates replacement prompts, assigns quality scores, and selects high-quality prompts for further optimization.
Techniques and related implementations for analyzing semantic sessions are provided. One implementation includes a computing system (100) comprising: processing circuitry (102) and memory (104) storing instructions that, during execution, cause the processing circuitry (102) to perform the steps of: receiving a plurality of screenshot images (106); for each of the plurality of screenshot images (106): identifying one or more image regions (302) and one or more text regions (304) on the screenshot image (106); and generating features (110) for the screenshot image (106) based on the one or more image regions (302) and the one or more text regions (304) using an artificial intelligence module (112); generating a user activity graph (116) comprising nodes and edges, wherein the nodes correspond to the plurality of screenshot images (106), and wherein the edges correspond to commonalities between node pairs based on the generated features (110) of the plurality of screenshot images (106); and identifying one or more node clusters from the user activity graph (116) based on semantic relationships.
Disclosed are techniques for disabling security exploits. Some live code patches redirect execution from a vulnerable version of a function to a secure version of the function. However, the vulnerable version of the function may remain in memory, creating an opportunity for exploitation. Disclosed are techniques for determining when the vulnerable version of the function is no longer in use, and when this determination is made, rendering at least a vulnerable portion of the vulnerable version of the function inoperable. Reference counting, call stack inspection, and process lifecycle tracking may be used to determine when the vulnerable version of the function is no longer in use. Some implementations may employ compiler-assisted instrumentation, run-time generated instrumentation, or hardware support. The vulnerable version of the function may be rendered inoperable by overwriting it with illegal instructions, marking a page of memory that contains the vulnerable version of the function non-executing, etc.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
