25 results about "Virtual team" patented technology

Systems and methods for integrating generative artificial intelligence (AI) capabilities within Software as a Service (SaaS) platforms. One of the computer-implemented methods are for querying a generative AI model about structured data in a SaaS environment, enabling users to interact with and manipulate data through AI-assisted interfaces. One of the systems maintains a generative AI agent configured to interact with SaaS platform data as a virtual team member, capable of understanding context and nuances of project data. Also described are methods for color-context aware data analysis, generation of interactive elements in messaging sessions, and cross-application generative AI agent interactions triggered by user mentions. Also described is facilitating the creation of custom SaaS platform products by combining functionalities from existing products using generative AI. The systems and methods represent advancement in AI-driven SaaS customization and data analysis.

A system for conducting a training session for a plurality of players comprises a training device, a hub network device, and wearable devices. The training device displays icons representing players associated with the wearable devices. The training device creates a plurality of virtual teams based on the selection of the players and associates the virtual teams with different colors. In addition, the training device transmits signals to illuminate visual indicators of the wearable devices of the players in each virtual team with respective associated colors to indicate commencement of different predefined activities. Furthermore, the training device also associates at least one icon representing at least one player with a different color from a previously associated color and transmits a signal to at least one wearable device corresponding to the player to illuminate the visual indicator of the wearable device in the different color to indicate commencement of a different predefined activity by the player.

A system and method for system and method for monitoring data before it is input into a machine learning model is provided. Generally, the system and methods of the present disclosure are designed to allow for the secure use of machine learning modules in virtual team environments. A chat module may be used to allow a user to control the use of one or more machine learning modules by inputting commands. The chat module may be incorporated into an existing user interface to add machine learning module functionality to said existing user interface. In some embodiments, a security module may monitor input data entered into the chat module by a user to prevent sensitive information from being distributed to the machine learning module.

The invention provides a task processing method, a task processing device, computer equipment and a storage medium. The method is applied to a virtual team, the virtual team comprises a plurality of roles and an engine execution unit, the plurality of roles comprise a coordinator and at least one executor, and the plurality of roles are large model agents based on a large language model; the method comprises the steps of splitting a target task through a coordinator to generate at least one subtask, and allocating a corresponding executor to the at least one subtask based on at least one executor; executing the allocated sub-tasks through an executor, and generating sub-task execution results of the sub-tasks; and monitoring a subtask execution result of the at least one subtask through an engine execution unit, and determining a task processing result of the target task. A coordinator in a virtual team splits and allocates a task, an executor executes the allocated sub-task, and an engine execution unit determines a task processing result of a target task to process the target task.

Systems and methods for integrating generative artificial intelligence (AI) capabilities within Software as a Service (SaaS) platforms. One of the computer-implemented methods are for querying a generative AI model about structured data in a SaaS environment, enabling users to interact with and manipulate data through AI-assisted interfaces. One of the systems maintains a generative AI agent configured to interact with SaaS platform data as a virtual team member, capable of understanding context and nuances of project data. Also described are methods for color-context aware data analysis, generation of interactive elements in messaging sessions, and cross-application generative AI agent interactions triggered by user mentions. Also described is facilitating the creation of custom SaaS platform products by combining functionalities from existing products using generative AI. The systems and methods represent advancement in AI-driven SaaS customization and data analysis.

A voice interaction processing method and apparatus, and a device, a computer-readable storage medium and a computer program product. The method comprises: acquiring team formation information in a virtual scene, wherein the team formation information comprises a team identifier of at least one virtual team and terminal information corresponding to game players comprised in each virtual team; on the basis of the team identifier of each virtual team, acquiring from the terminal information corresponding to the virtual team an audio component state of each terminal corresponding to the virtual team; and when it is determined, on the basis of the audio component state of each terminal corresponding to the virtual team, that a group session creation condition is met, creating a group session for the virtual team to perform voice interaction.

The invention provides a virtual item interaction method which comprises the steps that a graphical user interface is displayed through terminal equipment, the graphical user interface comprises a game scene and a first virtual object located in the game scene, and the first virtual object corresponds to the terminal equipment; distance information between a first virtual object and a second virtual object is obtained, and the first virtual object and the second virtual object belong to the same virtual team; when the distance information meets a first distance condition, controlling to display a knapsack information identifier at a position corresponding to the azimuth information of the second virtual object in the graphical user interface; and when the distance information meets a second distance condition, controlling to cancel display of the backpack information identifier of the second virtual object. The display state of the knapsack information is dynamically adjusted based on the distance between the virtual objects, the user interaction operation process is simplified, unnecessary interface switching and operation steps are reduced, and the interaction experience is improved.

The application discloses a virtual enterprise collaborative decision-making method and system for team heterogeneity identification and management strategy recommendation, and the method comprises the following steps: collecting team member basic information, dynamic cooperation behavior and periodic psychological measurement data; constructing task and relationship heterogeneity indexes based on the collected data; establishing and training a machine learning model; deploying the model, predicting future high-intensity conflict probability based on the heterogeneity indexes; and generating conflict management strategy suggestions in combination with the heterogeneity indexes and the predicted probability. The application integrates multiple data sources, constructs quantitative task and relationship heterogeneity indexes, and accurately portraits the team state. On this basis, the trained machine learning model is used to dynamically predict the future high-intensity conflict probability. This changes the passive situation of the existing team management system in responding after the event, improves the collaborative decision-making efficiency and overall management efficiency of the virtual team, and realizes the scientization and foresight of team management.

A system for conducting a training session for a plurality of players comprises a training device, a hub network device, and wearable devices. The training device displays icons representing players associated with the wearable devices. The training device creates a plurality of virtual teams based on the selection of the players and associates the virtual teams with different colors. In addition, the training device transmits signals to illuminate visual indicators of the wearable devices of the players in each virtual team with respective associated colors to indicate commencement of different predefined activities. Furthermore, the training device also associates at least one icon representing at least one player with a different color from a previously associated color and transmits a signal to at least one wearable device corresponding to the player to illuminate the visual indicator of the wearable device in the different color to indicate commencement of a different predefined activity by the player.

The present application relates to the technical field of enterprise team time management, in particular, the present application relates to a virtual team management method based on enterprise information sharing, the present application sets a time stamp for key task cooperation link and collects multiple types of data on the information sharing platform, a dynamic reminding threshold model is constructed by using the method of combining transfer learning and adversarial generative network, the social network factor of the task is considered, the quantum annealing algorithm is used to optimize the model parameters, in the task reminding stage, the model is used to monitor the task processing time in real time, the reminding frequency is dynamically adjusted based on cognitive computing, the busy state of the members is obtained by using blockchain and edge computing, the reminding time is postponed by using time series prediction and multi-agent negotiation, emotion computing and virtual reality technology are also used to trigger the reminder, so as to avoid interfering with the work of the members, improve the acceptance and attention of the members to the reminder, and significantly improve the cooperation efficiency of the key task of the virtual team, and optimize the virtual team management effect.

Systems and methods for integrating generative artificial intelligence (AI) capabilities within Software as a Service (Saas) platforms. One of the computer-implemented methods are for querying a generative AI model about structured data in a SaaS environment, enabling users to interact with and manipulate data through AI-assisted interfaces. One of the systems maintains a generative AI agent configured to interact with SaaS platform data as a virtual team member, capable of understanding context and nuances of project data. Also described are methods for color-context aware data analysis, generation of interactive elements in messaging sessions, and cross-application generative AI agent interactions triggered by user mentions. Also described is facilitating the creation of custom SaaS platform products by combining functionalities from existing products using generative AI. The systems and methods represent advancement in AI-driven SaaS customization and data analysis.

A system for conducting a training session for a plurality of players comprises a training device, a hub network device, and wearable devices. The training device displays icons representing players associated with the wearable devices. Tire training device creates a plurality of virtual teams based on the selection of the players and associates the virtual teams with different colors. In addition, the training device transmits signals to illuminate visual indicators of the wearable devices of the players in each virtual team with respective associated colors to indicate commencement of different predefined activities. Furthermore, the training device also associates at least one icon representing at least one player with a different color from a previously associated color and transmits a signal to at least one wearable device corresponding to the player to illuminate the visual indicator of the wearable device in the different color to indicate commencement of a different predefined activity by the player.

According to the game information processing method provided by the invention, the graphical user interface is provided through the terminal, and the graphical user interface displays the game scene; the method comprises the steps that in response to a sign rehearsal operation for a target plot in a game scene, a virtual drilling interface is displayed, and the virtual drilling interface displays a team scheduling slot and a virtual team; in response to a configuration operation of adding the virtual team to the team scheduling slot, determining a target virtual team, and generating combat process information based on correlation parameters of the target virtual team and the target land parcel; and displaying the combat process information on the virtual drilling interface. Therefore, the player can preview the combat condition of each team and the final land occupation condition in real time, the calculation pressure is effectively reduced, and the success rate of takeout is improved.

A system for conducting a training session for a plurality of players comprises a training device, a hub network device, and wearable devices. The training device displays icons representing players associated with the wearable devices. The training device creates a plurality of virtual teams based on the selection of the players and associates the virtual teams with different colors. In addition, the training device transmits signals to illuminate visual indicators of the wearable devices of the players in each virtual team with respective associated colors to indicate commencement of different predefined activities. Furthermore, the training device also associates at least one icon representing at least one player with a different color from a previously associated color and transmits a signal to at least one wearable device corresponding to the player to illuminate the visual indicator of the wearable device in the different color to indicate commencement of a different predefined activity by the player.

The invention discloses a virtual game processing method and device, equipment and a storage medium, and belongs to the technical field of human-computer interaction. The method comprises the following steps: displaying a virtual team which is organized, wherein the virtual team comprises a first virtual object; under the condition that the first virtual object meets an assistant game condition, team forming prompt information is displayed, the assistant game condition is used for indicating the condition that the first virtual object needs to obtain additional assistance in the virtual game, and the team forming prompt information is used for prompting that the permission of adding the NPC in the virtual team exists; in response to a role adding operation, displaying that the NPC joins the virtual team; and displaying that the NPC executes the virtual activity in the virtual environment of the virtual game.

Systems and methods for integrating generative artificial intelligence (AI) capabilities within Software as a Service (SaaS) platforms. One of the computer-implemented methods are for querying a generative AI model about structured data in a SaaS environment, enabling users to interact with and manipulate data through AI-assisted interfaces. One of the systems maintains a generative AI agent configured to interact with SaaS platform data as a virtual team member, capable of understanding context and nuances of project data. Also described are methods for color-context aware data analysis, generation of interactive elements in messaging sessions, and cross-application generative AI agent interactions triggered by user mentions. Also described is facilitating the creation of custom SaaS platform products by combining functionalities from existing products using generative AI. The systems and methods represent advancement in AI-driven SaaS customization and data analysis.

The application provides a scenic spot playing guiding system, including a flow monitoring module, a project reservation module, a playing recommendation module, a virtual queuing module and a push reminding module. The flow monitoring module is responsible for real-time monitoring of the flow data of each project in the scenic spot, the project reservation module is responsible for generating the reserved data according to the reservation operation of the user, the playing recommendation module is responsible for generating the playing recommendation route for the user based on the flow data and the reserved data of each project, the virtual queuing module can update the queuing situation of the user in real time according to the flow data of the project after detecting that the user joins the virtual team of any project through the real-time operation of the reservation interface or the predetermined operation of the reserved data, and the push reminding module is responsible for pushing the project reminding notification to the user at the appropriate time point according to the real-time position and the queuing situation of the user. Through the cooperative operation of the modules, the system of the application can meet the demand of flexibility and individualization of the tourists when playing.

This application discloses an operating system interaction method and system based on multi-agent collaboration, belonging to the field of operating system interaction technology. First, a multi-level agent collaboration system is constructed; then, the coordinating agent performs semantic parsing and complexity assessment on user requests, and routes tasks to corresponding agents based on the assessment results; for complex tasks, the planning agent generates a task flowchart, identifies composite sub-task nodes, and assigns them to corresponding composite domain agents for recursive task decomposition; the supervising agent performs task scheduling and status monitoring based on the task flowchart, and, upon receiving intervention instructions, determines the influence domain through dependency path propagation analysis to perform local adjustments, sub-task replanning, or global task replanning; after task completion, execution data is collected, agent collaboration patterns are identified, and a virtual team template is generated. This method can be used for operating system interaction and task processing in complex task scenarios.

The invention relates to the technical field of computers, and discloses a game control method and device, equipment, a medium and a product, and the method comprises the steps that a first virtual terrain is displayed, and the first virtual terrain comprises a plurality of virtual land parcels with terrain differences; setting a preset identifier in the target virtual land parcel of which the terrain height meets a preset condition; responding to a first moving instruction for the first virtual object, and controlling the first virtual object to move to a first parcel area corresponding to the target virtual parcel; in response to the fact that a first virtual object located in the first plot area meets the occupation condition for the target virtual plot, the target virtual plot is configured to belong to the first virtual unit, and a first gain effect is provided for the first virtual object; the first virtual unit is a first virtual team to which the first virtual object belongs or a first virtual camp to which the first virtual team belongs. The utilization rate of the virtual highland can be improved, and the playing diversity and strategy of the virtual highland are improved.

The invention discloses a task grouping method and device, equipment, a medium and a program product, and relates to the technical field of computers. The method comprises the following steps: displaying a first application interface in which a first account is logged; displaying the team forming area; displaying the account identification element of the second account in the team formation area under the condition of receiving an interaction operation on the account identification element of the second account; and based on the at least one second account in the team formation area, a virtual team containing the first account is established, and the accounts in the virtual team jointly execute the virtual task. That is to say, the user can quickly find teammates from the public social platform and add the teammates to the list to be invited, so that the step of adding other users as friends and then sending team forming invitations to other users is omitted, the team forming operation steps are simplified, the man-machine interaction efficiency is improved, the virtual team forming process is simplified, and the user experience is improved. And the team forming efficiency is improved.

According to the information processing method provided by the invention, a first terminal provides a graphical user interface, the graphical user interface displays a scene map and a plurality of virtual objects, and the method comprises the following steps: responding to a trigger operation for a target virtual object in the plurality of virtual objects, displaying team identifiers of a plurality of virtual teams which initiate a sign to the target virtual object at present; and in response to a selection operation for a first target virtual team identifier in the plurality of virtual team identifiers, adjusting a scene map display scale to display a team overview marching line corresponding to the first target virtual team. In this way, army marching details can be checked more conveniently, and the efficiency of acquiring battle information of players is improved.

A system and method for system and method for monitoring data before it is input into a machine learning model is provided. Generally, the system and methods of the present disclosure are designed to allow for the secure use of machine learning modules in virtual team environments. A chat module may be used to allow a user to control the use of one or more machine learning modules by inputting commands. The chat module may be incorporated into an existing user interface to add machine learning module functionality to said existing user interface. In some embodiments, a security module may monitor input data entered into the chat module by a user to prevent sensitive information from being distributed to the machine learning module.

A task teaming method and apparatus, a device, a medium, and a program product. The method comprises: displaying a first application interface logged in with a first account (310); displaying a teaming area (320); when an interactive operation on an account identification element of a second account is received, displaying the account identification element of the second account in the teaming area (330); and on the basis of at least one second account in the teaming area, forming a virtual team comprising the first account (340).

The application discloses a kind of operating system interaction method and system based on multi-agent cooperation, belong to operating system interaction technical field.First, multi-level agent cooperation system is constructed;Again, by coordination agent, semantic analysis and complexity evaluation are carried out on user request, and according to the evaluation result, the task is routed to the corresponding agent;For complex task, the task flow chart is generated by planning agent, the composite subtask node is identified and assigned to the corresponding composite field agent to execute recursive task decomposition;Task scheduling and state monitoring are carried out by supervisory agent according to task flow chart, and after receiving intervention instruction, the influence domain is determined by dependence path propagation analysis to execute local adjustment, subtask re-planning or global task re-planning;After task completion, execution data is collected, agent cooperation mode is identified and virtual team template is generated.The method can be used for operating system interaction and task processing in complex task scenario.

The invention relates to an AI agent enabling research and development collaboration method and system based on dynamic arrangement, belongs to the field of artificial intelligence, and solves the problems of tool island, process stiffness and knowledge fault of heterogeneous research and development in the prior art. The method comprises the following steps: obtaining an agent library and structured task description of a research and development task, wherein the agent library comprises a basic scene agent and a basic role agent; according to the structured task description and the first agent description of each basic scene agent, determining a target scene agent, performing task decomposition, and determining corresponding research and development sub-tasks; capacity vectors of the basic role agents are obtained, the capacity matching degree is calculated, and a target role agent set is determined and comprises a plurality of target role agents; obtaining an execution path of each target role agent, determining an execution directed graph, constructing a research and development virtual team, obtaining a task execution result, and updating the agent library. According to the invention, roles and tools are dynamically arranged based on tasks, and knowledge closed-loop evolution is realized.