1477 results about "Multiple applications" patented technology

An example operation may include one or more of ingesting data from one or more websites via one or more application programming interfaces (APIs) and storing the data within a data store of a host platform, displaying one or more prompts on a user interface of a user profile page within a software application hosted by the host platform, receiving one or more responses to the one or more prompts, generating a travel itinerary based on execution of an artificial intelligence (AI) model on the data from the one or more websites, the one or more prompts, and the one or more responses, and displaying the travel itinerary via the user interface of the user profile page of the software application.

An example operation may include one or more of ingesting profile data from one or more websites via one or more application programming interfaces (APIs) and storing the profile data within a data store, displaying one or more prompts on a user interface of a user profile page within a software application hosted by a host platform, receiving one or more responses to the one or more prompts, determining a goal for a user of the user profile page based on execution of an artificial intelligence (AI) model on the profile data, the one or more prompts, and the one or more responses to the one or more prompts, and displaying an identifier of the goal via the user interface of the user profile page of the software application.

The present application provides a shopping guide method and system based on a large language model, and the method is applied to the technical field of artificial intelligence. The method comprises: acquiring a training shopping guide requirement and a carried content enhancement configuration (S201); on the basis of the content enhancement configuration, generating a training prompt describing the training shopping guide requirement (S202); using a large language model to be trained to perform semantic analysis on the training prompt so as to determine a plurality of application interfaces required for responding to the training shopping guide requirement (S203); on the basis of a preset database, performing screening and summarization processing on returned results of the plurality of application interfaces to obtain predicted shopping guide information (S204); on the basis of the predicted shopping guide information and the training shopping guide requirement, performing parameter adjustment on the large language model to obtain a trained large language model (S205); and, when shopping guiding is conducted, on the basis of a prompt corresponding to a shopping guide requirement inputted by a user end, guiding the trained large language model to generate and output target shopping guide information. According to the method, target shopping guide information that is more in line with a user's natural language can be provided for the user end.

The invention discloses a large-model-driven intelligent calculation method and system for a water conservancy mechanism model. According to the method, natural language input, structured conversion and intelligent optimization calculation of a scheduling target are realized by integrating a field-enhanced large language model and a water conservancy professional mechanism model. The method comprises the steps of receiving a calculation target expressed by a user in a natural language, and analyzing and converting the calculation target into a constraint condition and a target function which can be recognized by a water conservancy mechanism model; a hydrological model, a hydraulic model, a hydrodynamic model and other models are called based on a workflow engine, and reverse calculation is carried out by adopting a hybrid optimization strategy of'coarse adjustment-fine adjustment-verification '; synchronously and visually displaying the parameter change and the result convergence state in the calculation process; and outputting a calculation result including parameter adjustment logic, standard conformity analysis and multi-scheme comparison. The system comprises a natural language interaction module, a target conversion module, an intelligent calculation engine module, a visualization module and a result generation module, and supports multiple application scenes such as multi-target scheduling, emergency decision making and ecological guarantee. Compared with a traditional scheme, the method has the advantages that the model use threshold is lowered, the dispatching efficiency and calculation transparency are improved, and the method is suitable for complex hydraulic engineering calculation tasks such as reservoir dispatching, cross-basin water transfer and flood control emergency.

Methods and apparatus for application aware memory patrol scrubbing techniques. The method may be performed on a computing system including one or more memory devices and running multiple applications with associated processes. The computer system may be implemented in a multi-tenant environment, where virtual instances of physical resources provided by the system are allocated to separate tenants, such as through virtualization schemes employing virtual machines or containers. Quality of Service (QoS) scrubbing logic and novel interfaces are provided to enable memory scrubbing QoS policies to be applied at the tenant, application, and / or process level. This QoS policies may include memory ranges for which specific policies are applied, as well as bandwidth allocations for performing scrubbing operations. A pattern generator is also provided for generating scrubbing patterns based on observed or predicted memory access patterns and / or predefined patterns.

The invention discloses a micro posture recognition method based on multi-modal feature fusion and fine adjustment, and relates to the field of computer vision and action recognition. The method is characterized in that a universal cross-modal knowledge fusion framework is provided, and multi-modal features are respectively extracted through a fine tuning network by using three kinds of modal information of video, skeleton and text. Meanwhile, a video-skeleton and text-skeleton fusion module is introduced to enhance the interactivity between modals. Compared learning is adopted to align feature distribution, and model training is optimized in combination with a freezing-fine tuning strategy, so that the calculation complexity is reduced, and the recognition efficiency is improved. According to the method provided by the invention, the problem of single-mode information loss can be solved, the perception capability of tiny attitude change is enhanced, the recognition precision and robustness are improved, and the method is suitable for multiple application scenes such as behavior monitoring, human-computer interaction and safety protection.

While AI models, like large language models, are powerful tools with multiple applications, they can be complex to use and can require a lot of resources to operate. The disclosed systems and methods provide tools to generate customized models (or AI agents) that are configured with features like tailored knowledge, capabilities, and instructions that make them faster, more efficient, and use less computational resources. AI agents may offer several technical advantages of improved efficiency, resource use, and connectivity. This disclosure describes systems and methods to configure, evaluate, generate, and deploy the custom models that can more efficiently run specific tasks. Disclosed systems and methods are configured to, for example, receive a query to generate a custom model, generate the AI agent custom model with the information in the query, and then resolve user queries more efficiently using the custom model.

Described herein are methods and systems for a conversational assistant that may be configured for use with one or more applications. The disclosed systems and methods may be configured as an outer loop / inner loop architecture incorporating one or more large language models (LLMs) and / or RAG functionality to support dialog-based interactions.

Example systems and methods described herein relate to the automated generation of sample expressions. Metadata is accessed for each of a plurality of applications. The metadata includes a functional description of each application. Prompt data is provided to a generative machine learning model. The prompt data includes the metadata for each of the plurality of applications and an instruction to generate, for each of the plurality of applications, a plurality of sample expressions corresponding to user input provided to a digital assistant to invoke an action related to the application. One or more responses that were generated by the generative machine learning model based on the prompt data are processed to obtain output data including the plurality of sample expressions for each of the plurality of applications in a structured format. The output data is used to configure the digital assistant.

The invention belongs to the field of satellite laser communication, and particularly relates to an optimal avoidance method for satellite laser communication under a sunshine or interference light source. Comprising the following steps: acquiring satellite historical position information based on a remote control telemetering receiver; establishing adaptive position prediction by adopting a UKF (Unscented Kalman Filter); determining whether a sunshine phenomenon occurs based on the predicted position information; and establishing a target optimization model of the optimal pointing path based on the minimum solar-solar evasion vector. According to the invention, calling of on-satellite computing resources can be avoided or high-precision blind tracking of the target can be realized in a remote control and telemetering unavailable stage, the dependence on the system is reduced, and the stability is improved; according to the method, the planning of a sun-sun avoidance autonomous path at a given angle can be realized, the most suitable pointing vector is found according to the shortest distance and the fastest speed, and the dependence on manpower and satellite computing resources is reduced; the time required for scanning and capturing again under the condition that the link is suddenly disconnected can be shortened by the system according to the predicted result; the method is multiple in application scenes and high in adaptability.

The present invention extends to methods, systems, and computer program products for optimizing resource allocation in view of predicted network traffic patterns and predicted power consumption. Network packets defining a network traffic flow can be received at a platform over time. Metrics can be derived from one or more applications executing on resources of the platform and processing data contained in the network data packets. Model training data can be formulated from the metrics. A resource adjustment model can be trained using the model training data. Executing the model can be automated to adjust resource allocation at the platform. Additional network packets defining an additional network traffic flow can be received at a platform over time. Data contained in the additional network packets can be processed using the adjusted resource allocation.

Methods, systems, and computer-readable storage media for restoring microservice persistencies. A disruptive event potentially affecting a computing system functionality and data synchronization of one or more applications and one or more microservices is determined. Each application and microservice stores respective data records in separate data tables. A restoration of the computing system functionality is determined. A synchronization process is initiated by using a synchronization identification engine. Data record synchronization is verified across a plurality of data tables, by matching record identifiers according to a call mapping between the applications and the microservices. The data record synchronization is restored across the plurality of data tables. An access to the applications and the microservices is reactivated.

The invention discloses a solution for intelligent low-code construction and automatic deployment of a multi-terminal application full stack, belongs to the technical field of software development, and solves the problems that an existing low-code development platform is high in use threshold, does not support customized development and is disjunction in application construction and application use. The invention provides an intelligent low-code construction platform. The intelligent low-code construction platform comprises a low-code construction platform, an application rendering unit, an application deployment unit and a display interaction unit, the low-code construction platform is used for constructing a plurality of application pages according to the developer personalized configuration information, and associating the plurality of application pages according to set association logic information among the plurality of application pages to obtain an application program; generating application data according to the application program, and storing the application data; the page cross-end rendering unit is used for performing Web end and App end rendering on the application program according to a defined page rendering protocol to obtain a Web end application and an App end application; and the display interaction unit is used for displaying the interaction function and the application logic of the Web end application and the App end application.

Disclosed herein are methods and systems for generating and using a shared knowledge language. In one embodiment, a method comprises retrieving data generated as a result of at least one computing device accessing one or more applications from a set of applications; generating a computer model comprising a set of nodes where each node having an identifier corresponding to a series of nouns and verbs generated in accordance with a schema associated with a shared knowledge language; when the processor receives a request: identifying a node that corresponds to the request; retrieving a pair of related nodes within the nodal data structure the processor identifying whether the relevance threshold has been satisfied using each respective node's identifier corresponding to the schema.

The invention discloses a high-resolution peak value positioning method based on multi-pulse superposition and offset clock cooperation, and belongs to the technical field of laser radar ranging. Aiming at the problems that a traditional laser radar depends on a high-sampling-rate ADC, so that hardware cost is high, power consumption is large, and sampling errors are likely to be caused by echo jitter, the method does not need to replace an existing ADC, and the technical breakthrough is achieved through the following core steps that firstly, the basic sampling rate X Hz and the target equivalent sampling rate improvement multiple N of the ADC are determined; laser pulses are emitted to a target object for N times, during Kth emission, ADC sampling is started by delaying (K-1) / (X * N) seconds, and N groups of echo data with time sequence offset are obtained; performing cross combination on the N groups of data, and constructing an N-time equivalent high-sampling-rate data sequence; repeating the sampling and combining process for S times, and performing alignment superposition and averaging on S groups of data to suppress echo jitter and noise; and estimating initial parameters (amplitude, mean value and standard deviation) of a Gaussian model based on the superposed data, optimizing the parameters through an LM nonlinear optimization algorithm, and finally taking the optimized mean value as a high-precision peak position of an echo signal to realize accurate measurement of the laser flight time. Under the condition of low-sampling-rate hardware, through the collaborative design of clock skew and multi-pulse superposition, the physical limitation of the sampling rate is broken through, low cost, low power consumption and high ranging precision are taken into account, and the method is adaptive to multi-scene application of automatic driving, industrial ranging and the like.

The invention discloses a machine tool running state collection and evaluation method and system, and relates to the field of intelligent machine tools, and the method comprises the steps: collecting machine tool multi-dimensional data through a multi-channel collection device; performing time alignment on different sampling frequency signals by adopting a dynamic synchronization algorithm of clock drift compensation; executing noise suppression, feature extraction and compressed encoding at the edge computing node to generate local state abstract data; sending the abstract data to a central server through a distributed message queue, and realizing multi-application concurrent access based on load dynamic scheduling; and the central server performs fusion analysis on the abstract data by using a multi-modal fusion deep network model, and outputs a health degree index and an overall operation score of the key parts of the machine tool, thereby realizing intelligent evaluation and health prediction of the operation state of the machine tool. The method realizes global perception and intelligent evaluation of the machine tool operation state, and can be widely applied to operation monitoring and health management of high-end numerical control machine tools, complex machining centers and unmanned production lines.

The invention provides a method for automatically deploying artificial intelligence models, which simplifies a model building process through systematic data preprocessing, model selection, parameter optimization and performance monitoring mechanisms, and dynamically updates or switches models in an application environment to maintain overall prediction performance at the best state while improving the performance of the model in multiple application environments.

A method is performed at a computer system that is in communication with a display generation component and one or more input devices. A first window and a second window are concurrently displayed. An input that changes a spatial arrangement of the first window is received at the computer system. In response, in accordance with a determination that the change in the spatial arrangement of the first window would cause the first window to occlude the second window such that less than a predetermined amount of the second window would be visible, moving the second window so that, after the second window is moved, at least the predetermined amount of the second window is visible.

A computer-implemented method executed using an assistant application and a web browser hosted or executed using a first computer, the computer-implemented method comprising receiving a first signal that first application is executing, with text within a workspace of the first application; receiving a second signal that a control was selected; instantiating and causing displaying an app actions window comprising at least one app label respectively corresponding to at least one second application; receiving input from the first computer specifying a selection of the at least one app label; updating the app actions window to display one or more app-specific widgets corresponding to widgets, fields, or functions available in the second application; receiving data entered into and / or selection(s) of one or more of the one or more app-specific widgets; programmatically invoking one or more application programming interface (API) calls of the second application using the data and / or selections; receiving one or more response(s) from API call(s) to the second application; updating the workspace of the first application based upon the one or more response(s). The method enables a user's computer to access functions of a second application from within a compact window over a first application without switching context to interact with the second application in a separate window or tab.

The subject technology implements a unified query frame that may retrieve identity records from multiple, asymmetric identity spaces. The unified queries of the unified query framework may include one or more steps, one or more paths, and a resolution scheme that may extract sets of identity records from multiple identity spaces. The unified query framework may be implemented in a graph analysis system that generates one or more identity subgraphs using the extracted sets of identity records. One or more aspects of the unified queries and or identity subgraphs may be configured to customize the data retrieval process for one or more applications. One or more search operations of the graph analysis system may be optimized to improve the speed and efficiency of data retrieval and reduce compute resources and cost.

The objective of the present invention is to provide a mobile terminal in which a layout of execution screens of two or more applications displayed together can be automatically changed to be suited for a user's viewing. According to an aspect of the present invention, provided is a mobile terminal comprising: a body; a display coupled to the body such that a display area viewed from the front of the body can be changed according to the switching between an extension display mode and a contraction display mode; and a control unit for controlling such that a layout for two or more application execution screens displayed together on the display is changed in response to the switching from the extension display mode to the contraction display mode.

A processor of a wearable device, according to an embodiment, may be configured to display, on a display, an area comprising at least one parameter for controlling an application screen and a speaker. The processor may identify an input for connecting the application screen and the area to each other. After identifying the input, the processor may output, through the speaker, an audio signal having a volume included in the at least one parameter, in response to audio data corresponding to the application screen. Certain example embodiments may be associated with a metaverse service for enhancing interconnectivity between an actual object and a virtual object. For example, the metaverse service may be provided through a network that is based on fifth generation (5G) and / or sixth generation (6G).

The present disclosure generally relates to viewing and updating application views. A device receives a user input, the input, when received initiating display of a plurality of application views of a set of application views. The device, in response to receiving the user input, displays the plurality of application views of the set of application views, wherein the set of application views includes preselected application views and an adaptive view that corresponds to a most recently opened application that is not one of the preselected application views.

Implementations of the present invention provide a digital twin intelligent edge terminal and an operation method therefor pertaining to the field of digital twin terminals. The terminal comprises: a state perception module physically connected to a cloud digital twin system and single or multiple application objects and sensors via various data interfaces; a decision reception and execution module configured to perform the dispatch of decision information according to whether a control system for controlling application objects has an instruction interface and a transmission protocol; a human-computer interaction module; a digital twin local control module interacting with the cloud digital twin system or collaborating with the state perception module, the decision reception and execution module, and the human-computer interaction module in different working modes; and a functional module manager implementing information interaction between the modules.

A system, method, and computer-program product includes obtaining, via an application programming interface (API), a test object that includes application usage data of a deployed AI application for a target time span, executing, in real-time by one or more computer processors, one or more application behavior tests that assess an operational behavior of the deployed AI application, detecting, by the one or more computer processors, that a misbehavior occurred in the deployed AI application during the target time span and one or more deviant features contributing to the misbehavior in response to executing the one or more application behavior tests, and returning, by the one or more computer processors, the one or more deviant features contributing to the misbehavior to a subscribing entity associated with the deployed AI application.

The utility model discloses a forklift fuel cell system and relates to the field of fuel cells. Comprising a fuel cell system module, a solid-state metal hydrogen storage module and a power cell module, and the fuel cell system module, the solid-state metal hydrogen storage module and the power cell module are all fixed in a forklift box body. According to the utility model, the whole system is divided into three modules, namely the fuel cell system module, the solid metal hydrogen storage module and the power cell module which are mutually independent, clear in boundary and free from mutual influence, so that the whole system can simultaneously take into account a solid metal hydrogen storage form and a gas hydrogen storage bottle form, and meanwhile, the power cell can also take into account various sizes and specifications; therefore, the whole system has a plurality of integration modes and a plurality of application scenes, and the extension and application range is wide.

The invention provides a battery safety and service life synchronous prediction method and device, equipment and a storage medium, and relates to the technical field of battery detection, the method comprises the following steps: obtaining charging and discharging data of a battery in a plurality of application scenes, carrying out data preprocessing on the charging and discharging data, and obtaining a standard data set; constructing a characteristic curve according to the standard data set; performing random masking on the characteristic curve to obtain a mask characteristic curve; constructing a deep neural network model, and training the deep neural network model according to the mask feature curve to obtain an initial prediction model; constructing a target mask feature curve of the battery in the target application scene, and performing optimization adjustment on the initial prediction model according to the target mask feature curve to obtain a target prediction model; and constructing a target characteristic curve of the target battery in the target application scene, predicting the target characteristic curve by using the target prediction model, and synchronously obtaining the safety state, the health degree and the service life of the target battery. According to the invention, the battery prediction precision and coverage can be improved.

The invention discloses a carbon emission flow analysis method for carbon emission evaluation in multiple application scenes, belongs to the technical field of power system carbon emission modeling and evaluation, constructs a connection relationship among nodes, branches and a power supply in a power system, and collects output data and type information of a power generation power supply and a power flow result in multiple operation conditions. The method comprises the following steps: calculating carbon emission of a power generation node, distributing the carbon emission to a load node according to a power flow path, identifying a carbon emission source of the load node by adopting a power tracking method, and calculating carbon emission intensity and a carbon potential index; a transmission structure of carbon emission in a power grid is defined, step-by-step distribution and flow direction tracking of the carbon emission are realized, and the defect that a carbon emission path is unobservable in the prior art is overcome; the identification precision of the carbon emission composition is improved, and a basis is provided for the priority division of energy-saving and emission-reducing measures; a carbon emission path mapping matrix and a transition probability matrix are constructed, dynamic identification of path changes is realized, and discovery of key paths and nodes is facilitated.

Data characterizing a prompt and / or a parameter set can be received. Data characterizing an enhanced prompt can be generated. The enhanced prompt can be stored in a template. When a change in ta type of the artificial intelligence based model, a setting of the artificial intelligence based model, or a configuration for an enterprise in which the artificial intelligence based model is deployed, is determined to be above a threshold, the enhanced prompt can be modified. The modified enhanced prompt can be provided to one or more applications interfacing with the artificial intelligence model, or derivative of the template. Related apparatus, systems, techniques, and articles are also described.

An endpoint framework is implemented for sharing one or more applications between one or more endpoint devices. To initiate sharing of an application, the system includes a first endpoint device running an application that generates notifications based on a condition or status of the application running. The first endpoint device provides these notifications to a second endpoint device which are output by the second endpoint device. The second endpoint device receives interactions with the output notifications and provides these interactions to the first endpoint device. In response to the interactions indicating the initiation of application sharing, the first endpoint device generates an application stream relating to the running application and provides it to the second endpoint device.