An apparatus is provided including storage encoded computer executable code for a consolidated enterprise application configured to provide, to a select set of users with credentialed private access to the consolidated enterprise application, web-based access in a form of a given user experience. In select embodiments, the given user experience involves providing access to user interface static content. The consolidated enterprise application comprises plural frontend web-based independent user interface (UI) unit applications. More specifically, the UI unit applications are individual uncontainerized micro frontends. One or more content publishing interfaces may be provided, that are configured to publish content including the code to a web service storage. The one or more content publishing interfaces are configured to use application programming interface requests to publish the content to the web service storage.
In some aspects, the techniques described herein relate to a method including: receiving, by a collaboration service, location data of a user, wherein the location data includes a timestamp; verifying, by the collaboration service and based on a digital itinerary associated with the user, a location of the user; processing data from a data profile associated with the user as input data to a machine learning model; receiving, by the collaboration service and as output of the machine learning model, a plurality of predicted travel objective classifications; determining, by the collaboration service, a plurality of travel objectives, wherein each of the plurality of travel objectives is associated with one of the plurality of predicted travel objective classifications; determining, by the collaboration service, a travel objective within a predefined proximity of the location of the user; and displaying the travel objective to the user via a planning interface.
G01C 21/34 - Recherche d'itinéraireGuidage en matière d'itinéraire
G01C 21/28 - NavigationInstruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier avec corrélation de données de plusieurs instruments de navigation
G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
3.
SYSTEMS AND METHODS FOR GENERATING JOINTLY CERTIFIABLE RANDOMNESS AND PROVIDING JOINTLY CERTIFIABLE RANDOMNESS VIA PUBLICLY-CERTIFIABLE RANDOMNESS BEACONS
A method may include: selecting, by a plurality of classical parties, each of the classical parties using a classical party computer program, a distributed randomness protocol; generating, by the plurality of classical parties, a random string using the selected distributed randomness protocol; providing, by one of the classical parties, the random string to a quantum party, wherein the quantum party executes a quantum party computer program in communication with a quantum randomness source; executing, by the quantum party, a certified randomness protocol with the quantum randomness source using the random string as an input; receiving, by the quantum party, quantum randomness comprising a sequence of random bits from the quantum randomness source; and verifying, by the classical parties, that the random string was randomly selected, and that the quantum randomness is a valid output of the certified randomness protocol using the random string as input.
A method and a system for improving a quality of software code generated by using a large language model (LLM) via code guardrails are provided. The method includes: receiving a request for performing a task; providing the request as an input to the LLM; receiving, from the LLM, a first set of executable code that is intended to be usable for performing the task; automatically executing the first set of executable code in an environment that includes at least one guardrail component that is configured to detect errors; detecting at least one error, such as a hallucination error, based on a result of the execution; determining at least one feedback item based on the at least one error; and prompting the LLM to generate a second set of executable code based on the request, the first set of executable code, and the at least one feedback item.
A method for computing regional counterfactual rules to summarize recourse options is disclosed. The method includes receiving model data via an input, the model data including information that relates to a target model and a corresponding data set; training a surrogate model for the target model based on the model data; identifying, by using the surrogate model, rules for an output of the target model based on a predetermined threshold, the rules including a counterfactual rule; enumerating, by using the surrogate model, boundaries for the identified rules to partition an input space into a grid with cells, each of the cells including a hyperrectangular cell; labeling, by using the surrogate model, each of the cells with one of the identified rules based on predetermined optimality criteria; and merging, by using the surrogate model, each of the labeled cells based on a matching of the rules to generate regions of optimality.
A method may include: generating, by a plurality of auditor computer programs and a data curator computer program, a first random string using a first distributed randomness protocol; sending the first random string to a quantum party computer program; executing, by the quantum party computer program, a certified randomness protocol with a quantum randomness source using the first random string; receiving, from the quantum randomness source, a first quantum randomness; generating, by the auditor computer programs and the data curator computer program, a second random string using a second distributed randomness protocol; extracting, by the data curator computer program and using a randomness extractor, a second quantum randomness from the first quantum randomness using the second random string, wherein the second quantum randomness comprises a near-uniformly random string; and executing, by the data curator computer program, a differential privacy protocol using the second quantum randomness as additive noise.
In some embodiments, techniques described herein relate to a method including: receiving a user instruction at an application executed by an electronic device; generating, at a framework executed by a server, one or more feature groups based on the profile data; generating, at the framework, a data configuration file; generating, at the framework, a model configuration file; specifying, at the framework, a sequence of functionality steps for execution; generating, at the framework, a prediction score based on the sequence of functionality steps; saving and/or executing, at the framework, the sequence of functionality steps; and generating, at the electronic device, one or more outputs including, for example, a prediction based on the sequence of functionality steps.
A method may receive a text string of an utterance. A method may tokenize the utterance into a plurality of tokens. A method may transform the plurality of tokens into a plurality of feature vectors. A method may assign an entity label to each of the plurality of feature vectors. A method may resolve each feature vector of the plurality of feature vectors to a corresponding standardized value of a database query language.
Payment cards with activated information displays are disclosed. In one embodiment, a payment card may include: a first layer; a second layer comprising an elastic material; an actuator; and an information layer between the first layer and the second layer, comprising: a plurality of information voids; and a microfluidic channel that communicates the plurality of information voids with the actuator. A fluid may be provided in the microfluidic channel such that when the actuator is depressed, fluid flows into the information voids making the information voids visible through the second layer, and when the actuator is released, the fluid flows out of the information voids making the information voids substantially invisible through the second layer.
A method and a system for automatically migrating projects of a computing product in phases for a version upgrade are provided. The method includes: receiving at least one input relating to projects of the computing product; identifying, based on the at least one input, at least one project of the first version of the computing product to be migrated; deploying a first intermediate instance for the first version of the computing product; copying at least one first data file of the identified at least one project from a source instance to the first intermediate instance; importing the identified at least one project from the at least one first data file into the first intermediate instance; modifying the first intermediate instance to a second intermediate instance for the second version; copying at least one second data file; and importing the at least one identified project of the second version.
Systems and methods for federated model validation and data verification are disclosed. A method may include: (1) receiving, by a local computer program executed by client system, a federated machine learning model from a federated model server; (2) testing, by the local computer program and using a policy service, the federated machine learning model for vulnerabilities to attacks; (3) accepting, by the local computer program, the federated machine learning model in response to the federated machine learning model passing the testing; (4) training, by the local computer program, the federated machine learning model using input data comprising local data and outputting training parameters; (5) identifying, by the local computer program using the policy service, accidental leakage and/or contamination by comparing the training parameters to the input data; and (6) providing, by the local computer program, the training parameters to the federated model server.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
A system and method for assessing a quality of a data fabric are disclosed. The method includes: receiving a plurality of input data products from at least one data source into the data fabric; and transmitting the plurality of input data products to a quality scoring engine for assessing the quality of the data fabric based on an analysis of each of the plurality of input data products. The analysis includes receiving a plurality of scoring parameters, rule definitions, and a metadata for each of the plurality of input data products; calculating a respective data offering quality score against each of the plurality of scoring parameters during the lifecycle of the plurality of input data products; generating a data fabric quality scoreboard based on an aggregation of the respective data offering quality scores calculated for each of the input data product; and displaying the data fabric quality scoreboard.
A method may include: receiving a plurality of log-text examples from network devices and labels indicating if the log-text example is anomalous or not anomalous; identifying, from the log-text examples and labels, rules for weak annotation, and validation labels for a validation dataset and test labels for a test dataset; organizing log-text examples in the validation dataset into a plurality of time windows; concatenating log-text examples in each time window; providing the concatenated log-text examples and the rules for weak annotation to a weak annotation framework, to a LLM training dataset; training a LLM with the LLM training dataset; collecting runtime log-texts from the network devices for a period of time; concatenating the runtime log-texts for the period of time; and prompting the LLM for analysis with the concatenated log-texts, wherein the LLM outputs a response of anomaly or no anomaly and a confidence in the response.
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p. ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
14.
SYSTEMS AND METHODS FOR MOBILE DEVICE PAYMENT USING TAP
Systems and methods for mobile device payment using tap are disclosed. In one embodiment, a method may include: reading, by a mobile application executed by a mobile electronic device, a machine-readable code comprising an embedded link to a provider website at a uniform resource locator (URL) provided by a provider of a good or service for a transaction involving the good or service; accessing, by the mobile application, the URL; receiving, by the mobile application and from the provider website, a payment by tap option; wirelessly receiving, by the mobile application, payment information from a physical financial instrument; providing, by the mobile application, the payment information to the provider website; and receiving, by the mobile application and from the provider website, confirmation of payment for the transaction.
A laser level target post for leveling a server cabinet. The laser level target post includes an elongated body section extending in a longitudinal direction, the elongated body section having an external surface that extends in the longitudinal direction, a reflective surface at a top end of the external surface of the elongated body section, wherein the top end reflective surface is operable to reflect a received light beam for leveling a top surface of the server cabinet, and a magnetic base at a bottom end of the elongated body section, wherein the magnetic base is operable to attach the laser level target post to a corner of the top surface of the server cabinet such that the longitudinal direction extends vertically.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
36 - Services financiers, assurances et affaires immobilières
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
Charge cards, credit cards, chip cards, electronic data carrier cards, and payment cards; magnetic encoded cards and cards containing an integrated circuit chip in the nature of smart cards all containing programming used to process payments; cards encoded with security features for authentication purposes Promoting the use of credit cards through the administration of incentive benefits, privileges, consumer loyalty programs, and the offering of exclusive programs and promotions to cardmembers Issuance of credit cards; credit card services, namely, credit card verification, financial administration of credit card accounts, and processing of credit card annual fees, transactions, payments, and merchant refunds Personal concierge services for others comprising making requested personal arrangements and reservations and providing customer-specific information to meet individual needs rendered to cardmembers
17.
SYSTEMS AND METHODS FOR INTEGRATED DIGITAL WALLET PAYMENTS
Systems and methods for integrated digital wallet payments are disclosed. Embodiments may store and manage the lifecycle of assets in a digital wallet and may provide artificial intelligence and/or machine learning based recommendations to provide the optimal frictionless and rewarding consumer authentication and payment experience. Embodiments may leverage blockchain technology that provides a single consumer solution with decentralized wallet ownership and a data-driven network orchestration for optimal payments. Embodiments securely store the payment instruments and may provide personal usage recommendations for the optimal outcome based on, for example, consumer preferences.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
A system and method are provided for image-based login and authentication. The system displaying a plurality of random images to a user; receiving from the user a selection of at least one target image from the plurality of random images; generating a hash number for the at least one target image; generating an encrypted identification token; and associating the encrypted identification token with the user. The hash number identifies the at least one target image. The encrypted identification token includes the hash number.
G06F 21/36 - Authentification de l’utilisateur par représentation graphique ou iconique
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
19.
SYSTEMS AND METHODS FOR DETECTION OF HALLUCINATION IN LARGE LANGUAGE MODELS
Systems and methods for detection of hallucination in large language models are disclosed. According to an embodiment, a method may include: (1) receiving, by a computer program, a plurality of input texts, wherein each input text is a prompt for a large language model (LLM) and may include a slight perturbation from an initial input text; (2) generating, by the computer program and for each of the plurality of input texts, an input embedding vector; (3) providing, by the computer program, each input text to a large language model (LLM); (4) receiving, by the computer program and for each input text from the LLM, an output text; (5) generating, by the computer program and for each of the plurality of output texts, an output embedding vector; and (6) generating, by the computer program, a hallucination metric based on the input embedding vectors and the output embedding vectors.
Various methods and processes, apparatuses or systems, and media for deterministically deriving underlying graph structure and associated text information in a document are disclosed. A processor implements a vision-based algorithm and a network-based algorithm that may extract and structure a diagram from an image obtained from the document. The processor deterministically derives underlying graph structure and associated text information in the document by applying the vision-based algorithm and the network-based algorithm, thereby allowing encoding of graph content and reasoning into downstream applications including LLM inputs, graphical question-answering, and information extraction tasks. The processor also implements OCR algorithm for text fields, and then isolates which piece of text belongs to which node by examining the spatial coordinates of the text against bounding box of the node and executes cross-page resolution.
G06V 10/46 - Descripteurs pour la forme, descripteurs liés au contour ou aux points, p. ex. transformation de caractéristiques visuelles invariante à l’échelle [SIFT] ou sacs de mots [BoW]Caractéristiques régionales saillantes
G06V 20/70 - Étiquetage du contenu de scène, p. ex. en tirant des représentations syntaxiques ou sémantiques
21.
METHOD AND SYSTEM FOR DETECTION AND MITIGATION OF ARTIFICIAL INTELLIGENCE HALLUCINATIONS
Methods and systems for detecting and mitigating hallucinations in artificial intelligence (AI) summarizations of user-generated content are provided. The method includes: receiving an AI-generated content item; retrieving historical content items that have been generated by human beings; comparing the AI-generated content item with the historical content items in order to determine whether text string matches are present; when a determination is made that no match exists, performing a semantic matching operation to identify text strings included in the historical content items that are semantically similar to text strings in the AI-generated content item; and determining, based on the comparison and the semantic matching operation, whether the AI-generated content item is a hallucination. When a hallucination is detected, the hallucination may be mitigated by removing a textual perturbation and/or replacing the textual perturbation with text that accurately reflects the original content item.
Systems and methods for generating synthetic training data are disclosed. A method may include: (1) receiving user speech from a user; (2) generating an input file comprising text of the user speech; (3) extracting entities from the text in the input file; (4) creating an input data structure for a data structure for the entities, wherein the input data structure comprises a plurality of columns, a column name for each column, a data attribute for each column, and a data type for each column, and a number of records based on a volume parameter; (5) converting the data type for each column to an ANSI SQL-standard data type; (6) generating a database agnostic data structure having the column names and the ANSI SQL-standard data type; (7) generating synthetic data for the database agnostic data structure; and (8) outputting an output file comprising the synthetic data.
Systems and methods for verification by tap are disclosed. In one embodiment, a method may include: receiving, by a computer program executed by an electronic device and from a mobile application executed by a mobile electronic device, an action selected by a user; determining, by the computer program, that the action is a sensitive action; causing, by the computer program, the mobile application to display an instruction to present a wireless-enabled device to the mobile electronic device; receiving, by the computer program and from the mobile application, device information that was received wirelessly from the wireless-enabled device; validating, by the computer program, the device information; and executing, by the computer program, the sensitive action in response to the device information being validated.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
24.
SYSTEMS AND METHODS FOR IN-PERSON INTERACTIVE SHOPPING
Systems and methods for in-person interactive shopping are disclosed. In one embodiment, a method may include: (1) identifying, by a computer program, a customer that is present in an area; (2) monitoring, by the computer program, a location of the customer in the area; (3) receiving, by the computer program and from a sensor near the location of the customer, a customer movement associated with removing an item from a shelf; (4) identifying, by the computer program, the item; (5) predicting, by the computer program, that the customer has removed the item from the shelf; (6) adding, by the computer program, the item to a virtual shopping cart for the customer; (7) decreasing, by the computer program, a stored inventory of the item; and (8) charging, by the computer program, the customer for the item.
Systems and methods for configuration driven integration of services in business process models agnostic of a workflow system are disclosed. An exemplary method includes receiving, at a service executor, a generic service call from a business process management notation (BPMN), wherein the generic service call includes a service name parameter, wherein the service name parameter is associated with a service task of the BPMN, and wherein the service name parameter is associated with a service. The service executor can construct a call to the service including required data from a transient data store. The service executor can then receive return data from the service, store the data in the transient data store and respond to the BPMN that the service task has been completed.
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06F 9/30 - Dispositions pour exécuter des instructions machines, p. ex. décodage d'instructions
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p. ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
26.
SYSTEM AND METHOD FOR GENERATING COMPETING MODELS IN RASHOMON SETS FOR GRADIENT BOOSTING
A method may include: receiving a dataset comprising a plurality of samples and a loss function; training a first number first machine learning models using the dataset comprising, wherein each of the first machine learning models has a similar performance; selecting one of the first machine learning models with a smallest loss; computing a residual for each of the plurality of samples using the one first machine learning model; defining a new dataset comprising the plurality of samples and the residual for each samples; training the first machine learning model with the new dataset; generating a second plurality of machine learning models by repeating the selecting, the computing, the defining, and training for a number of boosting iterations; selecting a subset of the second plurality of machine learning model models having a specified property; and deploying the subset of second machine learning models to a downstream task.
Systems and methods for protecting vulnerable persons from fraudulent activity are disclosed. A method may include: (1) receiving, by a computer program executed by an electronic device, a transaction involving a person having a registered guardian; (2) determining, by the computer program, that the transaction requires guardian consent from the registered guardian; (3) communicating, by the computer program, a notification comprising a code to a registered guardian electronic device associated with the registered guardian; (4) receiving, by the computer program and from the person, the code; and (5) executing, by the computer program, the transaction in response to receiving the code.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
28.
SYSTEMS AND METHODS FOR DECENTRALIZED RECOVERY OF IDENTITY ATTRIBUTES
Systems and methods for decentralized recovery of identity attributes are disclosed. In one embodiment, a method for decentralized storage of identity data may include: (1) receiving, at an identity management computer program executed by a computer processor, identity data from a user electronic device; (2) parsing, by the identity management computer program, the identity data into a plurality of portions; (3) mapping, by the identity management computer program, each portion to one of a plurality of storage locations; and (4) storing, by the identity management computer program, the plurality of portions to the plurality of storage locations based on the mapping.
Systems and methods for conducting composable quantum oblivious transfer over noisy quantum channels are disclosed. Embodiments provide a method for constructing a quantum oblivious transfer (QOT) protocol using noisy quantum channels and devices through the use of a quantum-hard one-way function. This construction allows the construction of QOT protocols that achieve simulator security, allowing them to be used in a black-box fashion as part of other cryptographic constructions, including arbitrary secure multiparty computations.
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Providing temporary use of online, non-downloadable software for facilitating the issuance, management, transfer, and settlement of deposit tokens and other digital or virtual blockchain-based payment instruments representing funds held with a financial institution; Software as a service (SaaS) featuring technology for enabling payments, settlements, and programmable transactions using deposit tokens and other digital assets on public and private blockchains; Providing online non-downloadable software for integrating deposit tokens with traditional bank accounts and financial systems; Providing online non-downloadable software for account-to-account transfers of deposit tokens representing funds held with a financial institution; Software as a service (SAAS) services featuring software for transferring, managing and processing deposit tokens, digital currency, virtual currency, and cryptocurrency based on blockchain technology; Platform as a service (PAAS) featuring computer software platforms for transferring, managing and processing deposit tokens, digital currency, virtual currency, and cryptocurrency based on blockchain technology; Software as a service (SAAS) services featuring software for recording and exchanging financial and non-financial data and information via a cryptographic ledger; Providing temporary use of non-downloadable software for facilitating peer-to-peer and institutional payments, cash management, and liquidity optimization using digital or virtual blockchain-based payment solutions; Providing temporary use of online non-downloadable software for accessing, reading, and tracking information in the field of financial transactions on a blockchain; Providing temporary use of online non-downloadable software for financial transactions on a blockchain; Providing temporary use of online non-downloadable software for processing electronic payments; Providing online non-downloadable software for data storage and certification using blockchain technology; Providing online non-downloadable software for managing smart contracts using blockchain technology; Electronic storage of deposit tokens and other digital or virtual blockchain-based payment instruments for others; Electronic storage of data related to financial transactions using blockchain technology for others; Providing online non-downloadable software for enabling secure access to, and transactions from, digital wallets associated with blockchain-based payment solutions; Providing online non-downloadable computer software for use as a digital wallet or electronic wallet; Design and development of computer software relating to deposit tokens, digital currency, virtual currency; Providing authentication, security, and trust services for blockchain-based payment solutions; Data encryption services, namely, electronic monitoring of personally identifying information to detect identity theft via the internet
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Providing temporary use of online, non-downloadable software for facilitating the issuance, management, transfer, and settlement of deposit tokens and other digital or virtual blockchain-based payment instruments representing funds held with a financial institution; Software as a service (SaaS) featuring technology for enabling payments, settlements, and programmable transactions using deposit tokens and other digital assets on public and private blockchains; Providing online non-downloadable software for integrating deposit tokens with traditional bank accounts and financial systems; Providing online non-downloadable software for account-to-account transfers of deposit tokens representing funds held with a financial institution; Software as a service (SAAS) services featuring software for transferring, managing and processing deposit tokens, digital currency, virtual currency, and cryptocurrency based on blockchain technology; Platform as a service (PAAS) featuring computer software platforms for transferring, managing and processing deposit tokens, digital currency, virtual currency, and cryptocurrency based on blockchain technology; Software as a service (SAAS) services featuring software for recording and exchanging financial and non-financial data and information via a cryptographic ledger; Providing temporary use of non-downloadable software for facilitating peer-to-peer and institutional payments, cash management, and liquidity optimization using digital or virtual blockchain-based payment solutions; Providing temporary use of online non-downloadable software for accessing, reading, and tracking information in the field of financial transactions on a blockchain; Providing temporary use of online non-downloadable software for financial transactions on a blockchain; Providing temporary use of online non-downloadable software for processing electronic payments; Providing online non-downloadable software for data storage and certification using blockchain technology; Providing online non-downloadable software for managing smart contracts using blockchain technology; Electronic storage of deposit tokens and other digital or virtual blockchain-based payment instruments for others; Electronic storage of data related to financial transactions using blockchain technology for others; Providing online non-downloadable software for enabling secure access to, and transactions from, digital wallets associated with blockchain-based payment solutions; Providing online non-downloadable computer software for use as a digital wallet or electronic wallet; Design and development of computer software relating to deposit tokens, digital currency, virtual currency; Providing authentication, security, and trust services for blockchain-based payment solutions; Data encryption services, namely, electronic monitoring of personally identifying information to detect identity theft via the internet.
32.
METHODS AND SYSTEMS FOR GENERATING SHORT AND READABLE TRANSACTION REFERENCE NUMBERS USING PROOF-OF-WORK
Aspects of the subject disclosure may include, for example, receiving, from a transaction terminal, a request for reference IDs, based on the receiving, providing, to the transaction terminal, a proof-of-work problem for the transaction terminal to solve, after the providing, receiving, from the transaction terminal, a solution to the proof-of-work problem, performing one or more actions to verify the solution, based on successful verification of the solution, transmitting a range of reference IDs to the transaction terminal, thereby enabling the transaction terminal to utilize the range of reference IDs in relation to transaction processing. Other embodiments are disclosed.
Methods and systems for computing input attributions to accurately explain predictions of decoder-only sequence classification models are provided. The method includes: receiving a set of inputs to the decoder-only sequence classification model; generating, based on the first set of inputs, a perturbed version of the set of inputs; sampling a binary mask from a predetermined masking distribution; generating a group of masked versions of the perturbed set of inputs by applying the binary mask to the perturbed set of inputs; generating, based on the group of masked versions of the perturbed set of inputs, corresponding sets of intermediate predictions that correspond to the decoder-only sequence classification model; computing, based on the sets of intermediate predictions, a set of input attributions; and determining, based on the set of input attributions, an explanation that relates to a prediction of the decoder-only sequence classification model.
Various methods and processes, apparatuses or systems, and media for evaluating LLMs on time series feature understanding are disclosed. A processor implements a pre-trained LLM; generates a comprehensive taxonomy for evaluating analytical capabilities of the LLM in a context of time series data, the comprehensive taxonomy including a feature and a corresponding sub-category of the feature. In evaluating analytical capabilities of the LLM in the context of time series data, the processor determines whether the LLM can detect the feature; and when it is determined that the LLM can detect the feature, determines whether the LLM can identify the sub-category of the feature; automatically generates a feature detection and classification score for the LLM indicating performance time series information retrieval and arithmetic reasoning performance measured by accuracy for different time series; and displays the score onto a graphical user interface.
Systems and methods for providing governance as finite state machines are disclosed. A method may include: a computer program in a compute environment: (1) receiving state machine definitions for a plurality of state machines; (2) saving the state machine definitions in a graph database; (3) receiving an event from one of a plurality of governed systems or a peer computer program in a peer compute environment, an event; (4) querying the graph database for one of the state machine definitions for the event; (5) instantiating a state machine instance using the state machine definitions; (6) executing a transition based on a current state; (7) receiving an instruction from the state machine; and (8) sending the instruction to one or more of the governed systems; wherein the one or more governed systems implement the instruction.
There are provided methods and systems for cloud access control. For example, a method is provided as instructions on a non-transitory computer-readable medium. The instructions may be configured to cause a processor to perform certain operations. The operations can include receiving information about a connecting entity, and the connecting entity seeking to establish a connection to a cloud environment. The operations can further include determining, based on a policy, one or more attributes associated with the connecting entity. The operations may also include partitioning the cloud environment, according to one or more attributes.
A system and method for providing an automated ticket resolution are disclosed. The method includes registering at least one queue owner upon successful completion of an onboarding of the at least one queue owner. The method includes receiving a ticket data from the at least one queue owner, the ticket data comprises data associated with a plurality of tickets and corresponding resolution of the plurality of tickets. The method further includes loading the ticket data into a data repository to train a model for the automated ticket resolution. The method includes receiving at least one ticket via a ticket management platform. The method further includes identifying a resolution for the at least one ticket using the model trained from the ticket data. The method includes executing the identified resolution to resolve the at least one ticket.
In some aspects, the techniques described herein relate to a method including: receiving, at a change request service, a request to update contact information data; receiving, at the change request service, from a verification service provider, a raw ownership score; normalizing, by the change request service, the raw ownership score; sending, by the change request service, the contact information data, the customer identifier, and the normalized ownership score to a risk engine; receiving, by the change request service from the risk engine, a confidence score; providing, by the change request service, the confidence score, the normalized ownership score, and historical data associated with the stored customer profile, to a consolidation function; receiving, by the change request service and from the consolidation function, a consolidated trust score; and updating a datastore record associated with a customer represented by the customer identifier with the contact information data.
A method and a system for using a large language model (LLM) to automatically translate textual instructions into executable software code via skill distillation and composition are provided. The method includes: receiving a request for performing a task and a prompt; providing, as an input to an LLM, the first request and a response to the prompt; receiving, from the LLM, a set of code that implements a function that corresponds to a skill that is usable for performing the task; generating a test that relates to the task; performing the test by executing the set of code and checking whether the task has been successfully completed; and when the task has been successfully completed, storing the set of code in a skills library. Sets of code stored in the skills library may then be accessed and combined in order to perform larger tasks.
Various methods and processes, apparatuses or systems, and media for data processing are disclosed. A processor implements an AI powered bot system; receives, via a user interface within the bot, user input as text data wherein the text data indicates a RFQ for a derivative instrument; transmits the text data to an AIML NLP service; extracts, by a parsing module, parameters associated with the RFQ by utilizing an entity extraction model provided by the AIML NLP service; normalizes the extracted parameters and transmits the normalized parameters to an automated pricing module; receives pricing details data by a response generation component embedded within the parsing module from the automated pricing module; and transmits the pricing details data to the bot for receiving user input via the user interface to conduct a transaction with respect to the derivative instrument.
A method may include: an access management service receiving a client credential from a client; the access management service generating a bearer token for the client electronic device and communicating the bearer token to the client electronic device; a blockchain integration service receiving a remote procedure call with the bearer token from the client electronic device; the blockchain integration service validating the bearer token with the access management service; the blockchain integration service receiving, from the access management service, a client profile comprising the client credential; the blockchain integration service determining that the remote procedure call is a contract create call; the blockchain integration service submitting the contract create call to a blockchain network; and the blockchain integration service adding the client and/or the contract to an allow list, wherein the allow list identifies clients that are allowed to access the contract on the blockchain network.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
42.
SYSTEMS AND METHODS FOR TIME AND/OR LOCATION BASED DISABLING OF MOBILE APPLICATION FUNCTIONALITY
A method may include: (1) receiving, at a computer program, such as a mobile banking application, executed by an electronic device, a request to disable a feature of the computer program, such as a payment feature, for a time period; (2) disabling, by the computer program, the feature; (3) determining, by the computer program, that the time period has passed; and (4) enabling, by the computer program, the feature. The feature may be disabled by removing an icon to access the feature, and may be enabled by adding the icon to access the feature. The method may also include: monitoring, by the computer program, a location of the electronic device; determining, by the computer program, that the electronic device is in a registered location; and enabling, by the computer program, the feature even if the time period has not passed.
H04M 1/72463 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques pour limiter la fonctionnalité du dispositif
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
H04M 1/72403 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens de soutien local des applications accroissant la fonctionnalité
H04M 1/72457 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques en s’appuyant sur la localisation géographique
H04M 1/72469 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles pour faire fonctionner le dispositif en sélectionnant des fonctions à partir de plusieurs éléments affichés, p. ex. des menus ou des icônes
Various methods, apparatuses, systems, and media for implementing endpoint detection and response and data protection correlation are disclosed. A correlation engine receives a data stream from multiple sources and one or more patterns. A processor analyzes the data to relate an event to the one or more patterns and executes a policy when the event matches the one or more patterns to identify suspected encrypted data files. The processor transfers the suspected encrypted data files and an encryption key to a controlled testing environment to use the encryption key to safely decrypt the suspected encrypted data files and to test the suspected encrypted data files to determine a potential network impact of executing each of the suspected encrypted files on the network. The processor detonates, from the controlled testing environment, the suspected data files confirmed during the testing to have a negative impact on the network.
A method for providing a tool for individualized financial planning and navigation that is tailored to user preferences and offers flexibility with respect to modifications in financial goals is provided. The method includes: receiving information that includes a financial goal of a user; applying an optimization algorithm that is designed to analyze the information with respect to the financial goal; and using a result thereof to determine an achievable percentage of the financial goal of the user and recommendation(s) for modifying the information in order to increase the achievable percentage of the financial goal. The information further includes a number of time steps for achieving the goal, a first amount of money that the user contributes per time step towards the goal, and a second amount of money that the user expects to save by the end of the time steps.
A method may include: an access control computer program receiving a third-party registration comprising a biometric from a third party; the access control computer program receiving an asset owner registration comprising an identification of a physical asset, an identification of a physical asset access control device that controls access to the physical asset, and an identification of the third party to access the physical asset; the access control computer program receiving, from the physical asset access control device, a biometric from the third party; the access control computer program comparing the biometric received from the physical asset access control device to the biometric in the third-party registration; and the access control computer program instructing the physical asset access control device to grant access to the physical asset in response to the biometric received from the physical asset access control device matching the biometric in the third-party registration.
A method and a system for using a skipping mechanism to automatically detect out-of-distribution (OOD) inputs to neural networks in an efficient and accurate manner are provided. The method includes: receiving a proposed input to a neural network at a first gate of the neural network; estimating, based on an output generated by the first gate, a first probability that the proposed input is classifiable as being OOD; forwarding the first proposed input to at least one additional gate of the neural network, including skipping at least one layer of the neural network; estimating, based on a respective output generated by each respective additional gate, a corresponding probability that the proposed input is classifiable as being OOD; and determining, based on the estimated probabilities, whether the proposed input is classifiable as being OOD by determining whether at least a minimum number of the estimated probabilities exceed a predetermined threshold.
Aspects of the subject disclosure may include, for example, receiving information regarding a plurality of jobs, assigning the plurality of jobs to a plurality of workers in accordance with a base schedule, wherein the base schedule is derived by solving an initial scheduling model that is configured to facilitate job assignments based on worker availability, capabilities, skills, experience, or a combination thereof, while reducing or minimizing job completion time and maintaining a determined balanced load, detecting one or more disruptions or events after the assigning, and causing the base schedule to be repaired based on the detecting, wherein the causing involves solving a scheduling repairing model that is configured to repair an existing schedule based on detected disruptions or events, while reducing or minimizing an impact of the detected disruptions or events on the existing schedule. Other embodiments are disclosed.
Various methods and processes, apparatuses or systems, and media for automating development, testing, and productionizing a pipeline for users are disclosed. A processor receives a request from a user to access an application, the request including user's credentials data; grants access to the application based on verifying the user's credentials data with prestored credentials data received by calling an authentication server; identifies the user's role within a computing environment; automatically presents a template that corresponds to the user's role allowing the user to write code to source data either by bringing the user's own data into the computing environment or by connecting to data that resides in a database; automatically integrates the written code with a continuous integration continuous delivery pipeline for production of a model; and deploys the model after training and testing the model while managing and maintaining all necessary guardrails from a control standpoint within the computing environment.
Systems and methods for automatically optimizing computer infrastructure by implementing multiple lines of defense in software development lifecycles. A method may include: (1) receiving information for on-premises infrastructure and costs associated with the on-premises infrastructure; (2) mapping the on-premises infrastructure to a proposed cloud infrastructure; (3) generating, using an artificial intelligence engine, an architecture diagram of the cloud infrastructure; (4) validating the proposed cloud infrastructure against organizational standards; (5) generating infrastructure as code for the proposed cloud infrastructure; (6) performing a code scan on the infrastructure as code; (7) identifying deviations from the infrastructure as code from the code scan; (8) generating a pull request for code from a source code repository based on the deviations; (9) identifying services and components to be deployed in the infrastructure as code; and (10) deploying the services and components to a cloud environment.
A method and system for using AI techniques to monitor the performance of an AI model and automatically perform an appropriate corrective action when necessary are provided. The method includes: receiving first data that relates to an AI model; generating, based on the received first data, at least one key performance indicator (KPI) that relates to the AI model; comparing each of the at least one KPI to at least one configurable threshold; assigning, based on a result of the comparing, a model health rating; and when the model health rating is less than a predetermined minimum acceptable health rating, performing, by the at least one processor, at least one corrective action that causes an increase in the model health rating.
A method for performing a determination of voter eligibility and facilitation of secure electronic voting is provided. The method includes authenticating a voter according to security setting and displaying a voting page for a jurisdiction corresponding to the voter's residence. The method then transmits to an adjudicating entity, voter information for determination of voter eligibility, and stores the voter information in a non-public blockchain. The method further includes determining whether the voter is eligible to vote based on the voter information stored in the non-public blockchain, generating a unique voter specific ballot for the voter in response to a determination that the voter is eligible to vote, and transmitting, to the adjudicating entity, a ballot selection received from the voter. The ballot selection is then stored on a public blockchain, and made available for release.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
52.
SYSTEMS AND METHOD FOR NETWORK-BASED DELIVERY OF DYNAMIC CONTENT
Systems and methods for network-based delivery of dynamic content are disclosed. A method may include: receiving, by a network computer program, a location for a customer electronic device associated with a customer; determining, by the network computer program and from the location, that the customer is within a predetermined distance of a merchant; requesting, by the network computer program, content for one or more payment card issued by an issuer to the customer from an issuer backend for the issuer; receiving, by the network computer program, the content; and communicating, by the network computer program, the content to a merchant backend for the merchant. The merchant backend receives, from a merchant point of sale device, payment card information for one of the payment cards, retrieves the content for the payment card, and causes the merchant point of sale device to display the content on a display.
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
53.
METHODS, SYSTEMS, AND DEVICES FOR SCALABLE MACHINE LEARNING MODEL INFRASTRUCTURE
Aspects of the subject disclosure may include, for example, obtaining a processing capacity associated with a machine learning model and obtaining a memory capacity associated with the machine learning model, and obtaining a processing capacity threshold and obtaining a memory capacity threshold. Further embodiments include provisioning a head node and a first group of worker nodes based on the processing capacity, the memory capacity, the processing capacity threshold, and the memory capacity threshold, provisioning a first portion of data engineering pipeline on each of the first group of worker nodes, and provisioning a first portion of the machine learning model on each of the first group of worker nodes. Other embodiments are disclosed.
A system for implementing a transmission log bucketing tool that provides an optimized transmission log storage and retrieval scheme. The system may comprise a processor and memory storing instructions that cause the processor to perform operations. The operations may comprise generating a manifest that comprises a transmission log table, obtaining a first set of transmission logs, evaluating the first set of transmission logs against the manifest to determine a first set of respectively corresponding shard keys, and utilizing the first set of respectively corresponding shard keys to at least one from among store the first set of transmission logs and retrieve the first set of transmission logs.
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
55.
ARTIFICIAL INTELLIGENCE POWERED HOLISTIC DIGITAL BANKING
Provided is a method for implementation of an application running on a computer having a processor and a memory or a cloud infrastructure, receiving a request from a user, via a gateway manager, to initiate a future payment transaction in accordance with a selected one of a plurality of payment transaction types. The method also includes comparing, via an allocation engine, the requested future payment transaction with patterns derived from an analysis of stored previous payment transactions associated with the user, wherein the patterns represent an association of each of the payment transaction types with one of a plurality of different types of vendors from the stored previous payment transactions. A payment transaction type is automatically selected for the future payment transactions based on the comparison.
A method and system for verifying a structured query language (SQL) query are provided. The method includes: receiving a first request to retrieve first data that is accessible via a database; identifying an intention of the first request; generating, based on the first request, a first SQL query to retrieve the first data from the database; predicting, based on the generated first SQL query, an output of the generated first SQL query; determining whether the predicted output matches the identified intention of the first request; generating, based on the determining of whether the predicted output matches the identified intention of the first request, a second SQL query to retrieve the first data that is accessible via the database, when the predicted output of the first SQL query does not match the identified intention of the first request.
A method and system for generating a dynamic graph network for a plurality of documents in a corpus are disclosed. The method includes analyzing a first document among the plurality of documents included in the corpus; generating a first node for the first document in the dynamic graph network; extracting one or more values included in the first document; assigning a key for each of the one or more values included in the first document; identifying at least one entity for the one or more values extracted from the first document; generating a second node for the at least one entity in the dynamic graph network; setting a status identifier for each of the first node and the second node generated; generating a first edge for the first node and the second node; and establishing a connection between the first node and the second node via the first edge.
A method may include: (1) generating, by a classical computer program executed by a client electronic device, a pseudorandom graph having a depth, a number of nodes based on a number of qubits in a quantum computer, and edges between the nodes; (2) creating, by the classical computer program, a coloring of the graph such that no two edges that share a node have the same color; (3) creating, by the classical computer program, a graph coloring layer for each color that includes edges with that color; (4) generating, by the classical computer, a quantum circuit from the graph coloring layers; (5) estimating, by the classical computer program, a cost of validating the quantum circuit; (6) determining, by the classical computer program, that the cost is acceptable; and (7) saving, by the classical computer program, the quantum circuit in response to the cost being acceptable.
A method may include: (1) querying, by a randomness computer program executed by a randomness electronic device, a quantum randomness source for a plurality of sequences of random bits; (2) receiving, by the randomness computer program, the plurality of sequences of random bits; (3) saving, by the randomness computer program, the plurality of sequences of random bits in a randomness pool; (4) receiving, by the randomness computer program, a request for randomness from a client randomness computer program executed by a client electronic device; (5) drawing, by the randomness computer program, a subset of the plurality of sequences of random bits from the randomness pool; (6) marking, by the randomness computer program, the subset of the plurality of sequences of random bits as used; and (7) communicating, by the randomness computer program, the subset of the plurality of sequences of random bits to the client randomness computer program.
A system for implementing a resource transmission management tool that processes resource transmissions, the system comprising a processor that is configured to: obtain a first set of requests that comprises a first resource transmission request; transform the first resource transmission request into a first corresponding encoded resource request; generate, by organizing an arrangement of at least the first corresponding encoded resource request, a pre-processed set of requests that comprises the first corresponding encoded resource request; assign, based on a topology of the pre-processed set of requests, a respectively corresponding weight to each transmission request field; analyze the first corresponding encoded resource request according to associated instructions; and generate a response to the associated instructions based on the analysis.
H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises
61.
SYSTEM AND METHOD FOR PROVIDING END-TO-END OBSERVABILITY FOR DISTRIBUTED EVENT-DRIVEN APPLICATIONS
A method and system for providing end-to-end observability for distributed event-driven applications are disclosed. The method includes generating a trace for an executed transaction and decomposing the generated trace into multiple synthetic traces or sub-traces. Each of the synthetic traces or sub-traces represents an operation performed for a discrete application function contained within that transaction. For each sub-trace a synthetic root span is generated, the root span representing an end-to-end time to process the respective application function.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p. ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
H04L 69/22 - Analyse syntaxique ou évaluation d’en-têtes
62.
SYSTEM AND METHOD FOR IMPLEMENTING A MODEL THAT PREDICTS THE PROBABILITY OF HALLUCINATION FOR ANY QUERY IMPOSED TO AN LLM
Various methods and processes, apparatuses or systems, and media for predicting probability of hallucination before generation for a query imposed to a Large Language Model (LLM) are disclosed. A processor causes a trained generative model to receive a query from a user via a user interface operatively connected to the generative model; perturbs the received query n times into unique variations that retain the original semantic meaning of the received query yet significantly diverge lexically; implements n+1 independent agents to sample an output from each query including the original received query; applies the simulation algorithm on the sampled outputs; derives an empirical estimate into an expected rate of hallucination for the original received query as a ground truth for the encoder; and outputs a probability of hallucination value for the query received by the generative model before the LLM generates an output.
G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p. ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
63.
METHOD AND SYSTEM FOR SECURING LARGE LANGUAGE MODEL SERVICES AGAINST PRIVACY ATTACKS
A system for securing a large language model (LLM) service against LLM privacy attacks. The system may comprise a processor that executes instructions that cause the processor to: interface with each output of the LLM service and each client network of the LLM service; monitor each output of the LLM to detect at least one client query textual response; detect and redact the at least one client query textual response according to an evaluation of that response and at least one current client privilege level that is assigned to at least one target client network account to which the at least one client query textual response is directed; and transmit a result of the redacting to a client device of the at least one target client network account.
Various methods and processes, apparatuses or systems, and media for generating a grounded answer to a query using a corresponding table are disclosed. The present disclosure provides decomposing a complex query into natural-language sub-queries or steps, which are then translated into database manipulation commands to sequentially transform input table into intermediate or simplified tables, until the input table is simplified for performing a final decision query. Each of the sub-queries may be associated with corresponding intermediate or simplified tables to ground the sub-queries.
There is provided a method residing as instructions on a non-transitory computer-readable medium, the instructions being configured to cause a processor to perform operations comprising receiving a request, the request being associated with a batch process for manipulating a dataset. The method also includes receiving a deadline by which the request must be executed, evaluating a set of requirements for executing the request by the deadline, entering the request into a queue, the queue being associated with a hardware location physically hosting the dataset, and determining an optimum time within the deadline for executing the request.
A foam-water fire sprinkler includes a nozzle, a shroud body, an agitator, and a deflector. The nozzle defines a nozzle passage that receives a foam-water solution therein. The shroud body defines a shroud passage that receives the foam-water solution from the nozzle passage. The agitator is positioned within the shroud passage, and has a rounded agitator portion and a straight agitator portion that extends from the rounded agitator portion. The foam-water solution impinges on the agitator at the rounded agitator portion to aspirate the foam-water solution with air to generate foam. A portion of the foam-water solution separates from the agitator at the straight agitator portion. The deflector deflects the foam-water solution and the foam to generate a spray pattern of the foam-water solution and the foam at a coverage area.
A system and method for detecting driver of variance are disclosed. The method includes receiving dependent variable(s) (y) and a set of independent variables (Xn). Next, the method includes computing a correlation (Rxx) between at least two of the independent variables and then calculating a partial effect (β) of each of the independent variables on the dependent variable(s) (y). The method includes estimating a row relative weight as a percentage of coefficient of determination R2 based on a sum of squared values of the calculated partial effect of the independent variables. The method includes determining a distance from median of x-coordinate (DFM x) and y-coordinate (DFM y) of the set of independent variables. The method includes detecting and displaying at least one driver of variance calculated via a weighted Euclidean distance calculated based on the DFM x and DFM y, and the estimated row relative weight.
Systems and methods for immersive data management in spatial computing are disclosed. A method may include: (1) requesting from an identity and access management service executed in a cloud environment, an access token; (2) receiving, from an identity and access management service, the access token comprising user entitlements to access a plurality of elements in a plurality of scenes; (3) requesting one of the plurality of scenes from a scene filtering service, the request comprising the access token; (4) identifying the user entitlements from the access token; (5) retrieving the requested scene comprising a subset of the elements; (6) adding the elements that the user is entitled to based on the user entitlements to a scene to be displayed; (7) returning the scene to be displayed to the computer program; and (8) displaying the scene to be displayed.
There are provided systems and methods for minimizing total emissions during distributed processing. For example, there is provided a method residing as instructions on a non-transitory computer-readable medium. The instructions are configured to cause a processor to perform certain operations. The operations can include receiving a request for access to a resource, and determining, based on the request, a usage profile. The operations may further include executing, based on the usage profile, a search for an available resource corresponding to one or more attributes of the usage profile. Furthermore, the operations may include, in response to finding the available resource, providing access to the available resource, tracking a plurality of parameters associated with the available resource upon the available resource being used after the providing.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software in the nature of a mobile application for brokerage and trading of investments, securities, stocks, bonds, capital investments, and equities; downloadable software in the nature of a mobile application for providing information in the field of finance, securities trading, investments, securities brokerage; downloadable podcasts in the field of financial news and information. Electronic financial securities and trading services for others; margin lending, namely, money lending that allows the borrower to invest the money; financial services, namely, investment brokerage and electronic trading services for securities, stocks, bonds, capital investments, and equities; financial investment brokerage services; providing financial information in the fields of investment and finance over computer networks and global communication networks; financial information provided by electronic means in the field of finance, securities trading, investments, securities brokerage; electronic financial trading services; electronic financial trading services for others via a global computer network; cash management services; issuing of debit cards; debit card transaction processing services; providing financial information in the fields of real time financial market data, securities, stocks, bonds, capital investments, and equities; cryptocurrency trading services; providing access to financial information, namely stock research reports; providing financial news and information; investment banking services; investment fund management services; investment advisory services; capital investment services; financial analysis; financial advice; financial asset management; Providing a website featuring non-downloadable publications in the nature of articles in the field of financial news and information; providing a website featuring on-line electronic newsletters in the field of financial news and information via e-mail; providing a website featuring non-downloadable videos in the field of financial news and information; providing online blogs in the field of financial news and information. Providing on-line electronic newsletters by e-mail in the field of financial news and information; educational services, namely, providing educational podcasts in the field of financial news and information. Providing temporary use of non-downloadable computer software via an online platform for brokerage and trading of investments, securities, stocks, bonds, capital investments, and equities; providing temporary use of non-downloadable computer software via an online platform for providing information in the field of finance, securities trading, investments, securities brokerage.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software in the nature of a mobile application for brokerage and trading of investments, securities, stocks, bonds, capital investments, and equities; downloadable software in the nature of a mobile application for providing information in the field of finance, securities trading, investments, securities brokerage; downloadable podcasts in the field of financial news and information. Electronic financial securities and trading services for others; margin lending, namely, money lending that allows the borrower to invest the money; financial services, namely, investment brokerage and electronic trading services for securities, stocks, bonds, capital investments, and equities; financial investment brokerage services; providing financial information in the fields of investment and finance over computer networks and global communication networks; financial information provided by electronic means in the field of finance, securities trading, investments, securities brokerage; electronic financial trading services; electronic financial trading services for others via a global computer network; cash management services; issuing of debit cards; debit card transaction processing services; providing financial information in the fields of real time financial market data, securities, stocks, bonds, capital investments, and equities; cryptocurrency trading services; providing access to financial information, namely stock research reports; providing financial news and information; investment banking services; investment fund management services; investment advisory services; capital investment services; financial analysis; financial advice; financial asset management; Providing a website featuring non-downloadable publications in the nature of articles in the field of financial news and information; providing a website featuring on-line electronic newsletters in the field of financial news and information via e-mail; providing a website featuring non-downloadable videos in the field of financial news and information; providing online blogs in the field of financial news and information. Providing on-line electronic newsletters by e-mail in the field of financial news and information; educational services, namely, providing educational podcasts in the field of financial news and information. Providing temporary use of non-downloadable computer software via an online platform for brokerage and trading of investments, securities, stocks, bonds, capital investments, and equities; providing temporary use of non-downloadable computer software via an online platform for providing information in the field of finance, securities trading, investments, securities brokerage.
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Financial services, namely, electronic funds transfer; clearing and reconciling financial transactions via a global computer network and wireless networks; providing a wide variety of payment and financial services; digitized financial assets and fund vehicles, namely investment fund vehicles and digital representations of equities, fixed income, cash, and derivatives; payment processing services, namely, providing virtual currency transaction processing services for others; financial services, namely, providing financial exchange services for stablecoin currency, virtual currency, digital currency, digital financial tokens, and cryptocurrency for use by others; financial services, namely, virtual currency, digital currency, stablecoin, and cryptocurrency transfer, trading, exchange, and payment processing services; electronic transfer of cryptocurrency, digital currency, stablecoins, digital and blockchain financial assets, digitized financial assets, digital financial tokens, crypto tokens and utility financial tokens; electronic wallet services for trading, storing, sending, receiving, validating, verifying, accepting, tracking, transferring, and transmitting virtual currency, and managing virtual currency payment and exchange transactions, financial transaction services, namely, providing secure commercial transaction options, secure commercial payment options, secure personal payment options, and secure electronic funds transfer options and permitting account holders to make payment requests, financial services, namely, electronic payment services involving electronic processing of payroll payments; merchant services, namely, payment transaction processing services, none of the aforementioned services are intended to be used in relation to any crypto, digital, or tokenized currency that is based solely upon gold and/or silver Providing temporary use of online non-downloadable software for processing electronic payments; providing temporary use of online non-downloadable software for creating, preparing, managing, sending, processing, tracking, and reconciling investor and transactional information; providing temporary use of online non-downloadable software for electronic funds transfer; providing temporary use of online non-downloadable software for sending, receiving, accepting, buying, selling, storing, transmitting, validating, verifying, tracking, transferring, trading and exchanging digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing temporary use of online non-downloadable software for digital currency payment and exchange transactions; providing temporary use of online non-downloadable software for use in issuing digital currency, virtual currency, cryptocurrency, stablecoins, digital and blockchain assets, digitized assets, digital tokens, crypto tokens and utility tokens; providing temporary use of online non-downloadable software for managing digital currency, virtual currency, cryptocurrency, stablecoin, digital and blockchain asset, digitized asset, digital token, crypto token and utility token payments, money transfers, and commodity transfers; providing temporary use of online non-downloadable software for use with digital currency wallet and storage services; providing temporary use of online non-downloadable software for use as an electronic wallet; providing temporary use of online non-downloadable software for facilitating electronic commerce transactions, none of the aforementioned services are intended to be used in relation to any crypto, digital, or tokenized currency that is based solely upon gold and/or silver
74.
METHOD AND SYSTEM FOR EVALUATION OF CODE GENERATION BY LARGE LANGUAGE MODEL
A method and a system for obtaining an evaluation of a quality of software code that is generated by using a large language model (LLM) are provided. The method includes: receiving a set of instructions for performing a task and generating an output; providing, as an input to an LLM, a list of available application programming interfaces (APIs) and the instructions, together with a submission of a request to the LLM to select one API and to generate a set of executable code based on the instructions; receiving, from the LLM, a selection of one API and the set of executable code; executing the set of executable code in order to perform the first task and generate the output; and evaluating an accuracy, a robustness, and/or a consistency of the set of executable code.
A method for generating customized model explanations via a model is disclosed. The method includes generating, via the model, a prompt in a natural language format based on a received request for an explanation of model outputs, the request including feature attributions and corresponding subject information; modifying, via the model, the prompt based on predetermined guidelines to generate a test response; validating, via the model, the test response by determining whether errors are detected in the test response; performing, via the model when the errors are detected, corrective actions that resolve each of the detected errors by altering the prompt; tuning, via the model, the altered prompt based on response attributes; and generating, via the model, a model explanation in the natural language format based on the tuned prompt.
A method may include a tokenization service: receiving, from a token management system, a namespace and a plurality of token parameters for the namespace; receiving a one-time load of a plurality of primary account numbers from the token management system; generating a token corresponding to each of the plurality of primary account numbers using the token parameters; storing a mapping of the plurality of tokens to the primary account numbers in the namespace; providing the plurality of tokens to the token management system; receiving, in response to a token refresh event, a new namespace and new token parameters from the token management system; generating a new token corresponding to each of the primary account numbers using the new token parameters; storing a mapping of the plurality of new tokens to the primary account numbers; and providing the plurality of new tokens to the token management system.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
77.
METHOD AND SYSTEM FOR EXPANDING CLIENT NETWORKS WHILE IMPROVING AND PROTECTING ROBUSTNESS OF THE CLIENT NETWORKS
A client network expansion system that: converts at least one from among a first rule and a first trend into a first set of code; stores the first set of code within a first repository of strategies; receives a first request that is associated with a new set of client details; based on the first repository of strategies, transforms a new set of client details into at least one new quantification of a first set of client attributes; determines whether the at least one new quantification meets a first set of criteria for a first client network; and adds a new client to the first client network when the determination is made that the at least one new quantification meets the first set of criteria.
H04L 41/0823 - Réglages de configuration caractérisés par les objectifs d’un changement de paramètres, p. ex. l’optimisation de la configuration pour améliorer la fiabilité
H04L 41/0816 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres la condition étant une adaptation, p. ex. en réponse aux événements dans le réseau
H04L 41/12 - Découverte ou gestion des topologies de réseau
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
78.
System and method for watermarking tabular data while obscuring underlying data for improving data integrity and security
A method and system for watermarking a dataset generated by a source system are disclosed. The method includes acquiring the dataset, distributing data elements included in the dataset over a range, and dividing the range into multiple bins according to a scheme. The method further includes designating each of the bins as a first or second type, tagging each data element according to according to a bin type of a bin the respective data element falls into. For each data element included in a bin of the second type, selecting a new value by sampling within a nearest bin of the first type and replacing the respective data element with a replacement data element including the new value, and watermarking each of the data elements originally included in the bins of the first type and replacement data elements for generating a watermarked dataset.
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Providing digital music from the Internet, not downloadable; Providing online music, not downloadable; Entertainment services, namely, providing non-downloadable playback of music via global communications networks
80.
Method and system for dynamic data partitioning and efficient polling in distributed microservices architecture
A method and a system for utilizing dynamic data partitioning to ensure consistency of event publications with associated business transactions in a distributed microservices architecture in order to optimize efficiency in polling data are provided. The method includes: defining a hash space that includes a range of assignable hash values; deploying a respective instance of each microservice to form a cluster of microservices within the distributed microservices architecture; allocating a respective subset of the hash space to each microservice; and facilitating a data polling capability with respect to a data table based on the allocated respective subset of the hash space and the deployed respective instance for each microservice.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
Systems and methods for anomaly detection in network devices are disclosed. A method may include: receiving a plurality of log messages from a data source; creating an offline anomaly detection model by: performing statistical modelling on the log messages from each network device; creating a log template for each log message based on static and variables parts of the log message; creating a template dictionary of log templates for each network device; creating a log template distribution; and creating template variables; receiving streaming data comprising log files from a plurality of network devices; aggregating the streaming data for each network device for a period of time; identifying an anomaly in the aggregated streaming data using the offline anomaly detection model; classifying the anomaly as a rate anomaly, a time anomaly, or a variable anomaly; and executing a self-healing action based on the classification.
Provided is a system and method for identifying anomaly patterns for card transactions within a consumer banking environment that includes retrieving, card transaction data, filtering and storing the debit card transaction data as raw data, processing the raw data in real-time, by detecting card transaction declines within the raw data, identifying, in real-time via a machine learning model, anomaly patterns associated with the card transaction declines detected; and generating at least one graphical illustration associated with the anomaly patterns identified, to be accessible via a user interface.
Multi-material cards with antennas are disclosed. A transaction card may include a card substrate having an antenna recess; an antenna received in the antenna recess; a chip opening in the antenna recess; a chip received in the chip opening, wherein the antenna is in electrical communication with the chip; and a non-blocking material positioned over the chip and the antenna in the antenna recess; wherein the non-blocking material allows radio frequency waves to pass to the antenna.
G06K 19/077 - Détails de structure, p. ex. montage de circuits dans le support
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Providing a website featuring non-downloadable software using artificial intelligence (AI) for searching and making reservations and bookings for temporary lodging and accommodations, restaurants and meals, hotels, and tours and visits to local attractions; Providing temporary use of online non-downloadable chatbot software using artificial intelligence (AI) for engaging in conversations for purposes of providing assistance and advice regarding travel planning, and for providing servicing support for existing booked travel components, namely, making, changing, or updating travel itineraries; Providing temporary use of on-line non-downloadable software for performing agentic tasks; Providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for analyzing and taking actions in response to content in the form of text, audio, or images, accessible via a website, mobile application, and social media platforms; Providing temporary use of on-line non-downloadable software for facilitating multi-modal natural language, speech, text, image, video, and sound input; Providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for simulating conversations, analyzing images, summarizing text, creating content, suggesting trip itineraries, and managing travel plans, reservations, and bookings; Providing a website featuring non-downloadable software using artificial intelligence (AI) for multi-modal communication, including interactive forms, chatbots, conversational agents, voice assistants, and other automated technologies designed to assist users in searching, planning, and making travel arrangements; Providing temporary use of on-line non-downloadable software for for use in providing a virtual assistant which enables natural language understanding, machine learning, and artificial intelligence capable of multi-modal interaction with a user; Providing on-line non-downloadable software using artificial intelligence (AI) for travel agency services, namely, searching and making reservations and bookings for temporary lodging and accommodations, restaurants and meals, hotels, and tours and visits to local attractions
85.
SYSTEMS AND METHODS FOR VERIFIED COMMUNICATION BETWEEN MOBILE APPLICATIONS
Systems and methods for using device data to validate a mobile user are disclosed. In accordance with aspects, a method may include receiving, at a backend processing infrastructure of a third party and from a backend processing infrastructure of a mobile application provider, a first copy of location information and an IP address, wherein the location information and the IP address are associated with a mobile device; receiving, at the backend processing infrastructure of the third party and from a mobile application provided by the third party, a second copy of the location information and the IP address, wherein the mobile application provided by the third party is executed on the mobile device; and verifying, by the backend processing infrastructure of the third party, that the first copy of the location information and the IP address matches the second copy of the location information and the IP address.
INTELLIGENT ANNOTATION ASSISTANT SYSTEMS AND METHODS USING PROMPT-FREE FEW-SHOT LEARNER FOR ANNOTATION AND CONFIDENT LEARNING BASED LABEL NOISE DETECTOR FOR POST-ANNOTATION
Aspects of the subject disclosure may include, for example, a method including training a first machine learning model to recognize a predetermined named entity in a sentence and a corresponding label, receiving input sentences including a target named entity, receiving a plurality of few-shot examples in a support set, the plurality of few-shot examples including an annotated label for the target named entity, performing annotation on the input sentences with the trained first machine learning model using the plurality of few-shot examples and using no prompt, generating labeled data including the annotated input sentences, performing post-annotation on the labeled data with a second machine learning model that performs confident learning based label noise detection, and generating cleaned labeled data excluding one or more noisy labels from the labeled data. Other embodiments are disclosed.
36 - Services financiers, assurances et affaires immobilières
Produits et services
Providing financial information via a website, namely, providing online credit scoring and financial health services for businesses, namely, credit health evaluation services, providing business entities’ credit scores, information about business credit reports, and educational information regarding how establishing a business credit profile can affect possible future financial outcomes
36 - Services financiers, assurances et affaires immobilières
Produits et services
Providing financial information via a website, namely, providing online credit scoring and financial health services for businesses, namely, credit health evaluation services, providing business entities’ credit scores, information about business credit reports, and educational information regarding how establishing a business credit profile can affect possible future financial outcomes
89.
SYSTEMS AND METHODS FOR SAMPLING AND TRAINING IN A MACHINE LEARNING ENVIRONMENT
The techniques described herein relate to a method including: retrieving a subset of data files from an original dataset, wherein data files not included in the subset of data files are a remaining dataset; dividing the subset of data files into an initial training dataset and a validation dataset; executing an in initial training pass on a machine learning model, wherein the initial pass trains the model using the initial training dataset; determining, after the initial pass, a predictive accuracy of the model using the remaining dataset; determining, by a targeted sampling process, a number of least learned data files from the remaining dataset; generating a second training dataset including the number of least learned data files; and executing a second pass on the model, wherein the second pass trains the machine learning model using the second training dataset.
Systems and methods for reconciling software release scope requirements are disclosed. A method may include: identifying code release version for a release candidate codebase; retrieving a log of changes made to the release candidate codebase and an implemented requirements identifier for each change; retrieving planned requirements identifiers for the code release version from a code requirements database; comparing the implemented requirements identifiers and the planned requirements identifiers; determining, based on the comparison, that an out-of-scope code change is included in the code release version; reverting the code release version to a prior version of the release candidate codebase that does not include the out-of-scope code change; retaining or reapplying in-scope code changes for the planned requirement identifiers to the prior version of the release candidate codebase; and deploying the prior version of the release candidate codebase with the in-scope changes to a production environment.
A method may include a first verifier computer program receiving an interaction with a first prover computer program for a client that requires verification comprising an identifier for the client; generating a challenge using a public identification key; issuing the challenge to the first prover computer program and to a second prover computer program; receiving a first response from the first prover computer program and a second response from the second prover computer program; determining that the first response and the second response were received within a predetermined amount of time; determining the first response and the second response are consistent; and informing the first prover computer program that the verification was successful.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
92.
SYSTEM AND METHOD FOR OFFLINE DATA-DRIVEN DISCOVERY AND DISTILLATION FOR SEQUENTIAL DECISION-MAKING WITH LARGE LANGUAGE MODELS
A method and system for performing a task requiring a plurality of sequential decision-making operations by an autonomous agent are disclosed. The method includes acquiring a portion of offline data from a database, and discovering a set of separate skills. The method further includes segmenting the offline data and segmenting the offline data according to skill, and abstracting the segmented offline data into reusable functions. From the abstracted reusable functions, distilling primitives for each skill and distilling reusable tips in various functions. Modifying skill based text-based and code-based policies for augmenting the autonomous agent, and processing a task requiring a set of sequential decision-making operations using the augmented autonomous agents.
Systems and methods for identifying and remediating architecture design defects are disclosed. In one aspect, a method includes generating a new architecture graph pattern based on an architecture design document of an evaluated architecture; determining a model graph pattern, wherein a shape of the model graph pattern is similar to a shape of the architecture graph pattern; determining, based on a comparison of the shape of the model graph pattern with the shape of the new architecture graph pattern, that the new architecture graph pattern includes a design defect; generating, based on the shape of the model graph pattern, a remediated graph pattern; and determining, based on the differences between the remediated graph pattern and the new architecture graph pattern, a suggested remedial change to the architecture design document.
G06F 30/398 - Vérification ou optimisation de la conception, p. ex. par vérification des règles de conception [DRC], vérification de correspondance entre géométrie et schéma [LVS] ou par les méthodes à éléments finis [MEF]
In some aspects, the techniques described herein relate to a method including: receiving, as input to a binary search process, a subject vector embedding and a class vector embedding, wherein the subject vector embedding is generated from a plurality of subject text strings and wherein the class vector embedding is generated from a class text string; generating a similarity score; determining that the similarity score is below a threshold value; splitting the plurality of subject text strings into a first new plurality of subject text strings and a second new plurality of subject text strings; receiving a new subject vector embedding, wherein the new subject vector embedding is generated from the first new plurality of subject text strings; and calling the binary search process recursively using the new subject vector embedding and the class vector embedding as input to the binary search process.
Various methods, apparatuses, systems, and media for implementing an application programming interface (API) integration library are disclosed. A receiver receives a user request of a process flow to access one or more resources. A processor creates a configuration file having a reusable and standardized format, wherein the configuration file includes detail data that specifies how the API connects to the one or more resources to execute the user request, how to create a standardized request, how to map a standardized response back in response to the user request, and how to handle retry attempts when the user request fails. The processor also causes a library to receive the configuration file as input that utilizes the configuration file to process the user request. The processor automatically creates, by the library, a desired application as output of the process flow based on the received configuration file.
A method for using a privacy preserving linear optimization technique to perform computations on encrypted data while ensuring that the original data remains confidential and secure from any unauthorized access based on secure multi-party computation is provided. The method includes: receiving, from each of several entities, a respective input that includes encrypted data; constructing a table that includes first information that relates to an objective function, second information that relates to a boundary value, and third information that relates to a polynomial function that is applicable to each respective input; and determining a value that maximizes the polynomial function subject to a constraint that a result of applying the objective function to the value is less than or equal to the boundary value.
Aspects of the subject disclosure may be directed to, for example, a method including receiving a first text input that represents entity description at an entity encoder, receiving a second text input that represents Automatic Speech Recognition (ASR) transcription at a text encoder, receiving a third text input that represents ground truth transcription at the text encoder, performing embeddings of the first text input, the second text input, and the third text input, training a natural language processing model, and generating a predicted entity output and a predicted non-entity output using the trained natural language processing model. Other embodiments are disclosed.
Method and systems for obtaining direct feedback from a payment card by using energy received from a radio frequency identification (RFID) card reader is provided. The method is implemented by a processor that is embedded in the payment card. The method includes: receiving, from the RFID card reader, a radio frequency (RF) signal that relates to a proposed transaction; transmitting, to the RFID card reader, account information that relates to the proposed transaction; and causing an actuator that is embedded in the payment card to actuate a feedback action based on the RF signal. The actuator may include a haptic device that generates a vibration that is detectable by a touch of a user of the payment card.
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
