Abstract: A method for determining an object's position using different items of sensor information includes: a) reading the sensor information into a Kalman filter, b) merging the sensor information with the Kalman filter, with the Kalman filter supplying as a result estimated values for states and information associated with the estimated values regarding the accuracy of the estimates, c) monitoring the results of the Kalman filter by estimating a probability of accuracy, with which the estimation error lies within an error band, with the probability of accuracy being determined on the basis of a plurality of conditional probabilities, the conditions for which each relate to estimation errors from at least one earlier series.

Abstract: Training a Gaussian process state space model, which describes a correlation between selected control parameters of a plurality of control parameters for controlling a robotic device and output variables of the robotic device assigned in each case.

Abstract: An information processing apparatus includes a processor configured to: identify a target user and a companion accompanying the target user, in accordance with communication log information and a user identifier of the target user, the communication log information indicating a log of short-range wireless communication of a target mobile terminal used by the target user and including a user identifier of a nearby user using a nearby mobile terminal having performed short-range wireless communication with the target mobile terminal; and provide, to the target user and/or the companion, provision information that is selected in accordance with the target user and the companion.

Abstract: Non-limiting embodiments of the present technology are directed to a method and system for generating a training dataset. The method comprises: accessing data associated with a plurality of assessors executing digital tasks of a first type and digital tasks of a second type; generating, a first ranked list of assessors and a second ranked list of assessors based on their past performance; for a given one of the plurality of assessors: generating, a class score for the common class of digital tasks; acquiring a request for executing a digital task of a third type; ranking, the plurality of assessors based on respective class scores, the given one from the plurality of assessors being one of top ranked ones from the plurality of assessors; transmitting the digital task of the third type to the given one; generating the training data for the MLA based on a response from the given one.

Abstract: The present technology can receive a collection of candidate images that are candidates for posting on a social media platform, and then determine, using artificial intelligence model, a prediction of expected engagement on the social media platform for each image of the candidate images.

Abstract: A system and method for digitally testing a webpage are disclosed herein. The system receives, via one or more application programming interface (API) endpoints, user data. The user data includes one or more indications of one or more users interacting with the one or more variants of the webpage. The system inputs the one or more indications into a machine learning model. The machine learning model includes a Bayesian multi-arm bandit algorithm. The system generates, using the machine learning model, one or more results comprising causal performance estimates and a set of decision rules to adaptively design further testing experiments based on the causal performance estimates. The system generates a portal accessible to one or more end users. The portal includes the one or more results.

Abstract: Systems, methods and computer program products are provided for performing random walks on knowledge graphs. Knowledge graphs are received and for each knowledge graph there is constructed a multilayer network having unipartite layers and bipartite layers and interlayer couplings that (i) connect nodes of the unipartite layers and the bipartite layers representing the same entity (ii) are directed and (iii) weighted with a weight that depends on an activity of a target node in the unipartite layer or bipartite layer in which the target node resides. A walk on a random walk model of the multilayer network that takes into account saliencies of the different interlayer and intralayer connections of the nodes is then processed and one or more actions based on the random walk model are performed.

Abstract: An electronic apparatus may include a communication interface, a memory configured to store at least one instruction, and one or more processors configured to generate response information based on conversation content received through the communication interface by executing the at least one instruction to: identify a user request by confirming a current request and a previous request of a user in the conversation content, identify whether the user request is a multi-turn request or a single-turn request based on the conversation content, generate a confirmation request to request the user to confirm the user request based on the user request being identified as the single-turn request, and omit a generation of the confirmation request and generate a response corresponding to the user request based on the user request being identified as the multi-turn request.

Abstract: A method of generating responses responsive to input prompts including receiving a multimodal input prompt, the multi-modal input prompt comprising a first input prompt mode and a second input prompt mode, generating first and second derived prompts responsive to the first and second input prompt modes, transmitting the first and second derived prompts to first and second h-LLMs that are trained using data having a mode that is the same of the respective input prompt modes, receiving one or more first and second results from the first and second h-LLMs, generating at least one combined result from the one or more first and second results, and transmitting the combined result to the user.

Abstract: Application compliance policies can be dynamically updated. An agent can be deployed on user computing devices to monitor application install events to track how frequently users install applications on the user computing devices and whether applicable application compliance policies dictate that such applications should be removed. A policy management service of a management solution can interface with the agents to gather application metrics and use the application metrics to dynamically update the application compliance policies to prevent future removal of one or more applications that are determined to be commonly installed by the users. These dynamic updates could be made on a per-user basis, a per-group basis, or a global basis.

Abstract: Aspects of the subject disclosure may include, for example, receiving environmental data from a plurality of environmental data sources, identifying environmental risks based on the environmental data, obtaining profile information relating to a user or entity, based on the obtaining the profile information and the identifying the environmental risks, generating a recommendation for one or more locations of possible interest, and causing the recommendation to be presented to the user or entity, thereby providing location-based environmental risk information that is customized on a per user or per entity basis. Other embodiments are disclosed.

Abstract: Described is a system for generating and displaying decision recommendations. The system receives historical observations and courses of action corresponding to the historical observations. A conditional density between the historical observations and the courses of action is estimated, and the historical observations are clustered according to the conditional density to obtain observational clusters. Observational clusters are merged to determine a causal partition having corresponding causal features which map to various courses of action. A new observation is mapped to the causal partition and a ranking of courses of action for the new observation is computed. A visualization of causal features and a ranking of courses of actions corresponding to the new observation is provided to a display.

Abstract: Certain aspects of the present disclosure provide techniques for detecting data entry errors. A method generally includes receiving a string value as user input for a data field, selecting a plurality of reference values previously entered into the data field within a time period, processing, with an embedding model configured to classify an input string value as a valid or invalid entry, the string value and the reference values and thereby generating a first vector as output, computing one or more statistics for the reference values and the string value, creating a second vector based on the one or more statistics, generating a concatenated vector by concatenating the first vector and the second vector, processing, with a classifier model configured to classify the string value as valid or invalid, the concatenated vector and thereby generating a classification output, and taking action based on the classification output.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for storing incomplete dialog sessions between a user and an automated assistant in order that the dialog sessions can be completed in furtherance of certain actions. While interacting with an automated assistant, a user can become distracted and not complete the interaction to the point of the automated assistant performing some action. In response, the automated assistant can store the interaction as a dialog session. Subsequently, the user may express interest, directly or indirectly, in completing the dialog session, and the automated assistant can provide the user with a selectable element that, when selected, causes the dialog session to be reopened. The user can then continue the dialog session with the automated assistant in order that the originally intended action can be performed by the automated assistant.

Abstract: Quantum Information Processing (QIP) with the availability of Noisy Intermediate-Scale Quantum (NISQ) device(s) are available to work on quantum algorithms. Different problems, which are hard to solve by classical computation, but can be sped up (significantly in some cases) are also being populated. However, current approaches solve only two cluster max-cut problems. Mining the two cluster Max-Cut problem within the framework of quantum Ising model, embodiments of the present disclosure solve Quadratic Unconstrained D-ary Optimization (QUDO) problems by quantum computing with the identification of an appropriate Hamiltonian. More specifically, the problem is mapped to an Ising model to obtain a d-ray Quantum Ising Hamiltonian. The d-ray Quantum Ising Hamiltonian is then executed on one or more qudit processors, to obtain one or more resultant quantum states which are measured in a qudit computational basis to obtain at least one solution.

Abstract: Various embodiments are generally directed to techniques for crowdsourcing metadata, such as to create, maintain, utilize, and/or communicate metadata in a datastore. Some embodiments are particularly directed to collecting, managing, and/or distributing metadata via a user interface application (UIA), or an extension thereof. Many embodiments may facilitate collaborative creation of a repository for metadata, such as notes, characteristics, and/or statistics corresponding to data viewed with the user interface application. For example, the comments regarding websites may be collected from a first user via a first instantiation of the web browser extension and distributed to a second user via a second instantiation of the web browser extension. In several embodiments, the metadata may be collected and managed with instantiations of the web browser extension (herein after “WBE instants”) and a data manager may create, maintain, utilize, and/or communicate metadata in a datastore.

Abstract: A perturbation filtering system that employs a separate Filter AI to learn and filter injected noise from perturbed data fed to an existing AI System for continued operation in an adversarial situation. The Filter AI may be connected to the input data of the Supported AI so that all input data go through the Filter AI before reaching the Supported AI. Alternatively, Filter AI may be connected to the blocked data output of an AI Firewall so that all blocked data from the AI Firewall go through the Filter AI and if the filtering is successful, enters the AI Firewall. Alternatively, Filter AI may be connected to the AI Firewall input, or Filter AI may be connected to the blocked data output of the AI Firewall.

Abstract: The invention relates to a communication system and a method for providing a virtual meeting of a first user (U1, U2, U3, U4) and a second user (U1, U2, U3, U4), comprising a first communication device (12, 14, 16, 18, 24, 26, 28, 32, 34) with a first display device (12a, 14a, 16a, 18a, 24a, 26a, 28a, 32a) associated with the first user (U1, U2, U3, U4), and a second communication device (12, 14, 16, 18, 24, 26, 28, 32, 34) with a second display device (12a, 14a, 16a, 18a, 24a, 26a, 28a, 32a) associated with the second user (U1, U2, U3, U4).

Abstract: Systems and methods for a natural language survey system are provided. The natural language survey system may harness generative artificial intelligence (“AI”) and machine learning to enhance survey question generation, survey participance and completed survey analysis and research. The natural language survey system may include a dynamic interactive platform. The dynamic interactive platform may enable a researcher to create a survey using natural language. The dynamic interactive platform may enable a researcher to directly identify survey goals instead of creating a plurality of goal-oriented specific questions. The dynamic interactive platform may enable a plurality of participants to participate in the survey. The dynamic interactive platform may provide reports and insights to the researcher upon completion of the survey by the participants.

Abstract: An arrangement for determining external damage to hair is given. A device comprising: a reading unit adapted to obtain optical characteristics of hair; and a processing unit adapted to receive the optical characteristics from the reading unit and to determine surface properties of the hair from the optical characteristics, wherein the processing unit implements a pattern recognition algorithm and is adapted to assign, by employing the pattern recognition algorithm, the surface properties to a predetermined damage including at least one damage type and an associated damage level and to output the damage.

Abstract: There is provided a computer implemented method for the automated analysis or use of data, comprising the steps of: (a) storing in a non-transitory computer-readable medium a structured, machine-readable representation of data that conforms to a machine-readable language; in which the structured, machine-readable representation of data includes a plurality of tenets defining rules, the plurality of tenets including at least one constraint tenet, the at least one constraint tenet preventing a bad action; wherein the plurality of tenets comprise different sets of tenets; (b) using the different sets of tenets in different contexts, e.g. for different types of chatbots, or for different end-users.

Abstract: The present disclosure relates to systems, methods, and devices for controlling charging of vehicles, to avoid charging during charge-adverse time periods or during charge restriction events. This can advantageously reduce cost to vehicles owners, and or provide access to reward incentives. Further, power distribution entities (utility providers) advantageously have increased control over power distribution to avoid over-burdening of power distribution infrastructure. Further, systems and methods for determining or inferring whether a vehicle is connected to a charge station are described, which can be used to inform automatic restriction of vehicle charging.

Abstract: Embodiments of the present disclosure generally relate to a network-based real-time enterprise travel management system that can facilitate planning, booking, scheduling, and managing travel, while also facilitating expense budgeting and reporting. Embodiments of the present disclosure can provide systems and methods for generating and managing a predictive itinerary associated with travel and/or an event, as well as a centralized marketplace for accessing various services and events.

Abstract: A network state tracking system tracks the state of a network and recommends an action when the state of the network changes. The network state tracking system detects one or more nodes on the network and generates one or more snapshots of the network. The snapshots are generated by obtaining first and second status data from the nodes and detecting whether a change in the network has occurred based on the status data. The snapshots are generated based on the first and second status data when a change in the network is detected. The snapshots are then used to train a machine learning model to recommend an action to take when a change in the network occurs.

Abstract: A method includes receiving a spoken utterance that includes a plurality of words, and generating, using a neural network-based utterance classifier comprising a stack of multiple Long-Short Term Memory (LSTM) layers, a respective textual representation for each word of the of the plurality of words of the spoken utterance. The neural network-based utterance classifier trained on negative training examples of spoken utterances not directed toward an automated assistant server. The method further including determining, using the respective textual representation generated for each word of the plurality of words of the spoken utterance, that the spoken utterance is one of directed toward the automated assistant server or not directed toward the automated assistant server, and when the spoken utterance is directed toward the automated assistant server, generating instructions that cause the automated assistant server to generate a response to the spoken utterance.

Abstract: A device may receive user data identifying vitals of users when receiving treatments and dosages of the treatments, and may process the user data, with a divergence model, to determine divergence data identifying divergences between the users. The device may process the divergence data, with a clustering model, to group the users into clusters of users, and may train a first neural network model, with the user data, to generate a trained first neural network model. The device may train a second neural network model, with the user data, to generate a trained second neural network model, and may generate a treatment model based on the trained first and second neural network models. The device may process new user data identifying a new user, with the treatment model, to determine a recommended treatment for the new user, and may perform one or more actions based on the recommended treatment.

Abstract: Described embodiments provide systems and methods for enhancing user engagement with micro applications. A computing device can include one or more processors and memory. The computing device can receive an indication of an action to be completed with use of a micro application. The computing device can be in communication with a client device and one or more computing systems of record to execute the micro application. The computing device can values for one or more attributes of the micro application. The computing device can generate, based on the identified values, a score for the micro application. The computing device can provide the score to the client device for display within a user interface. The user interface can be configured to initiate the action with use of the micro application.

Abstract: A sequence of models accumulates r-squared values for an increasing number of variables in order to quantify the importance of each variable to the prediction of a targeted yield or parametric response.

Abstract: A method of processing multimedia data, a device, and a medium, which relates to a field of an artificial intelligence technology, in particular to fields of knowledge graph and deep learning. The method of processing the multimedia data includes: recognizing the multimedia data so as to obtain at least one key information of the multimedia data; querying a predetermined knowledge base according to the at least one key information, so as to determine a multimedia name associated with the at least one key information and an association degree between the multimedia name and the at least one key information; and determining, in the multimedia name, a name of the multimedia data based on a similarity between alternative multimedia data for the multimedia name and the multimedia data, in response to the association degree being less than a first threshold value.

Abstract: In some implementations, a system enables an administrator to customize a set of rules to dynamically adjust the configuration and output of an application provided to users. A configuration interface for setting rules that dynamically adjust output of an application is provided. Data indicating one or more rules are received through the configuration interface. Activity data indicating user interaction with the application or sensor data for at least some of a plurality of users of the application are then received from multiple client devices. A determination relating to the activity data satisfying at least one condition or trigger is then made. Instructions to adjust output of the application according to one or more system actions of the one or more rules are then communicated to client devices associated with the users in the first subset of the plurality of users.

Abstract: A device and method for recommending a custom function to the user in an electronic device. The electronic device may obtain information of a user gesture that repeatedly occurs based on interaction of the user detected by at least one sensor and determine one or more customized functions to be suggested to the user, among functions of the electronic device including a plurality of accessibility functions, in consideration of the information of the user gesture. The electronic device may execute a target customized function selected by the user from among the one or more customized functions.

Abstract: Provided is a control support apparatus, comprising: an equipment abnormality estimation section for estimating an abnormality of equipment based on measurement data by measuring the equipment; a simulation section for simulating a future state of the equipment when controlling the equipment by each of a plurality of candidate control methods according to an abnormality estimation result of the equipment; and a simulation abnormality estimation section for estimating a future abnormality of the equipment based on a future state of the equipment for each of the plurality of candidate control methods.

Abstract: A method of answering queries using one or more families of large language models (h-LLMs) including receiving a user prompt via an application programming interface (API) at an input broker from a user interface, generating a plurality of derived prompts from the user prompt at the input broker, transmitting the plurality of derived prompts to one or more h-LLMs via a cloud service API, each h-LLM of the one or more h-LLMs being in a cloud container environment, receiving a plurality of h-LLM results at an output broker, processing the plurality of LLM results at the output broker to generate a result, and transmitting the result to the user interface via the API.

Abstract: There is provided a computer implemented method for the automated analysis or use of data, comprising the steps of: (a) storing in a non-transitory computer-readable medium a structured, machine-readable representation of data that conforms to a machine-readable language; in which the structured, machine-readable representation of data includes a plurality of tenets defining rules, the plurality of tenets including at least one constraint tenet, the at least one constraint tenet preventing a bad action; wherein the plurality of tenets comprise different sets of tenets; (b) using the different sets of tenets in different contexts, e.g. for different types of chatbots, or for different end-users.

Abstract: A system and method for generating and applying meta-models in simulated environments, in which an agent simulation is selected, one or more agent goals are received, and agents are created which are individual instances of the agent simulation with each agent having at least one of the agent goals, wherein the agents are used in the execution of an environment simulation which dynamically changes based on the collective behavior of the agents. The agents operate in the environment simulation using meta-models which describe how the agents interact with other agent and how the agents interact within the simulation.

Abstract: A feedback based public safety method is provided. The method is implemented by a computing device and comprising receiving, from an external device of an individual, identification data of the individual associated with the external device, accessing from one or more databases, by the computing device of the user, ratings data specific to the individual, the ratings data is based on historical interactions of the individual, comparing the ratings data with one or more of a plurality of threshold values, determining, based on the comparing, whether the ratings data satisfies one or more of the plurality of threshold values, and initiating one or more of a plurality of actions sets responsive to the ratings data satisfying the one or more of the plurality of threshold values.

Abstract: Building and using a smart contract in order to resolve the isolation between database users and service operators for hyper-protect database as a service (DBaaS). The use of the smart contract in the hyper-protect DBaaS environment allows the service operator to perform operations on sensitive and secure data in the database owned by a user without necessarily revealing the content of the sensitive and secure data.

Abstract: Techniques are provided herein. The techniques can include obtaining current context data and determining a contextually-determined action based on the obtained context data and a reasoning model. The reasoning model may have been determined based on one or more sets of training data. The techniques may cause performance of the contextually-determined action and, potentially, receiving an indication that performing the contextually-determined action in the current context resulted in an anomaly. The techniques include determining a portion of the reasoning model that caused the determination of the contextually-determined action based on the obtained context data and causing removal of the portion of the model that caused the determination of the contextually-determined action, to produce a corrected reasoning model. Subsequently, second context data is obtained, a second action is determined based on that data and the corrected reasoning model, and the second contextually-determined action can be performed.

Abstract: Systems and methods are provided for creating and managing a data integration workspace. The workspace may comprise one or more views of data (or datasets) stored in or accessible by the system. Models may be generated and updated based on the plurality of datasets and presented via a graphical user interface. Feedback received via a graphical user interface presenting a model may be used to annotate an underlying dataset associated with the model. Responsive to a modification of the underlying dataset or the rules for using the underlying dataset to generate the model, other related datasets and/or models may be automatically updated accordingly. Templates associated with one or more types of users may be defined. Each template may comprise one or more specific models related to a specific type of user.

Abstract: An earpiece in embodiments of the present invention may have one or more of the following features: (a) an earpiece housing, (b) at least one speaker, (c) a plurality of sensors disposed within the earpiece housing, and (d) a processor disposed within the earpiece housing and operatively connected to the plurality of sensors and the at least one speaker, wherein the processor is configured to use an artificial intelligence framework to evaluate sensor input from the plurality of sensors to provide advice to the user.

Abstract: According to at least one embodiment, a method, a computer system, and a computer program product for handling an unreliable data sink is provided. The present invention may include reading, continuously, via a stream processor, a batch of data entering the stream processor via a reliable input stream, the stream processor comprising a daisy chain of sink nodes, wherein a first sink node is a primary sink node and a subsequent plurality of sink nodes in the daisy chain are fallback sink nodes; outputting processed data to a non-streaming target system; upon completion of the processed data to the non-streaming target system, invoking an asynchronous callback function listing successful and failed record IDs of the processed data; and passing the failed records to a first fallback sink within the daisy chain, while the primary sink node concurrently continues submitting new batches of data to the non-streaming target system.

Abstract: A system and method for generating a multi-label classifier of textual data is presented. The method includes training a plurality of single-label classifiers, wherein each of the plurality of single-label classifiers is trained to classify textual data to a single predefined revenue-based label; and training the multi-label classifier using labeled data output by the plurality of single-label classifiers, wherein the multi-label classifier is trained to classify textual data to a vector including revenue-based labels and their respective classification scores.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate generalization of a quantum imaginary time evolution process and simulation by tensor networks are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise a universal component that generalizes a quantum imaginary time evolution process to provide a quantum imaginary time evolution ansatz process. The computer executable components can further comprise a simulation component that applies the quantum imaginary time evolution ansatz process to one or more general multi-body quantum systems.

Abstract: Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.

Abstract: This disclosure relates generally to the field of program slicing, and, more particularly, to a method and system for function call and variable access based relaxed backward slicing. The method discloses a slicing criterion which focuses only on functions called from an entry function. The slicing criteria uses control and data flow information to slice the given entry function with respect to functions called from the body of the entry function and eventually remove all functions not called directly or indirectly from the entry function. The variables modified by calls in the entry function are considered through side-effect while identifying control and data dependence chain within body of entry function. The proposed technique identifies partitions of functions based on the variables accessible in and functions called from the entry function. Thus, unrelated sets of functions with respect to the entry function are computed and divided into different partitions.

Abstract: A building system that operates to receive building data from one or more building systems of the building, wherein at least a portion of the building data is associated with control of the one or more environmental conditions of the building and generate, based on the building data, a plurality of building health scores of the building, wherein an overall building health score is based on a combination of the plurality of building health scores. The building system operates to receive user feedback regarding the plurality of building health scores via one or more user devices, determine whether the user feedback confirms or denies an accuracy of the plurality of health scores, and generate a user interface and cause the user interface to display an indication of whether the user feedback confirms the accuracy of the plurality of building health scores.

Abstract: The present invention tracks provenance (people, place, time, permissions, machine characterization and identification) for an off-chain digital asset, provides data verifiability and enforces least privileged access within a single organization or across multiple organizations via a combination of Blockchain and communication agents to enable data assured operations in a normal operating environment and Logistics Under Attack (LUA) environment. The present invention creates data assurance for a digital asset across networks and within environments as it tracks provenance of the digital asset at rest or in motion allowing a data file to move directly from the originator to a customer at the point of use or point of origin to point of use and all points in between in a prescribed or random flow.

Abstract: A virtual reality application adaptively generates a virtual reality experience intended to improve a user's mood. A plurality of digital assets is stored together with associated scores. A score for a digital asset represents a predicted amount of mood improvement occurring in a cohort of users having similar profiles to a target user in response to virtual reality experiences including the digital asset. A customized virtual reality experience is generated for the target user based at least in part of the user profile data on the scores. The user's change in mood is detected through survey and/or biometric data. Scores for the digital assets may then be updated in order to further learn their respective effects on the cohort of users.

Abstract: The present disclosure relates to recording and tracking a local content enrichment submission via a local content enrichment platform that leverages distributed ledger technology. The system can comprise a memory to store computer executable instructions. Also, the system can comprise one or more processors, operatively coupled to the memory, that execute the computer executable instructions to implement a blockchain layer configured to record a local content enrichment submission to a distributed ledger and track a status of the local content enrichment submission via transactions with the distributed ledger. The local content enrichment submission includes data characterizing a proposal of an entity to comply with local content regulations of a region.

Abstract: A network device comprises processing circuitry configured to: receive a plurality of data chunks from at least one source; form a composite data chunk from at least first and second data chunks of the plurality of data chunks; process the composite data chunk to identify a match between a first pattern of characters within the composite data chunk and a stored pattern of characters; and validate or invalidate the match based on metadata of the composite data chunk.