125results about "Specific access rights" patented technology

Systems and methods are described for building artificial intelligence (“AI”) agents. A server can provide a user interface (UI) that includes options to select and connect various agent objects. The agent objects can include prompt objects, dataset objects, model objects, and one or more code objects. A subset of the agent objects can be identified as available for selection based on evaluation of at least one management policy associated with an administrative user. A manifest file is generated based on the connected agent objects, and the manifest is validated against dependency rules to ensure that the stages of the agent meet prerequisites for the stages. Then, the server performs a simulated execution of an agent that corresponds to the validated manifest file, including an identification of at least one execution metric associated with the simulated execution.

Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and / or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.

Systems and methods are described for building artificial intelligence (“AI”) agents. A server can provide a user interface (UI) that includes options to select and connect various agent objects. The agent objects can include prompt objects, dataset objects, model objects, and one or more code objects. A subset of the agent objects can be identified as available for selection based on evaluation of at least one management policy associated with an administrative user. A manifest file is generated based on the connected agent objects, and the manifest is validated against dependency rules to ensure that the stages of the agent meet prerequisites for the stages. Then, the server performs a simulated execution of an agent that corresponds to the validated manifest file, including an identification of at least one execution metric associated with the simulated execution.

Systems and methods are described for providing multitenancy in an artificial intelligence (AI) platform. The platform can provide a user interface (UI) that allows for creation of an organization, tenants within that organization, and groups within tenants. This hierarchy can dictate resource permissions that impact which AI pipelines and AI pipeline objects are available to a user. The different tenants can have segregated data and utilize different pipeline objects, such as different prompts, datasets, or models. A marketplace UI can prioritize additional marketplace pipelines for approval and inclusion with the tenant.

Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and / or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.

Systems and methods are described for tool discovery and ingestion for artificial intelligence (“AI”) agents. An AI platform can discover a first tool specification that includes an action and a description. The first tool specification is ingested to create a first tool object. The first tool object includes the action and an endpoint. Tool labels are determined from the specification and applied to the first tool object. A user interface displays the tool object, and it is added to an AI agent. The AI agent includes a manifest file that is used to execute the AI agent. This includes determining whether the AI agent is authorized to perform the action, and providing the AI agent with access to a tool credential, wherein the tool credential is sent to the endpoint.

Systems and methods are described for a maintaining consistent and reliable outputs from artificial intelligence (“AI”) based search systems that use pipelines with a dataset, AI model, and prompt. An application can send a query through a pipeline and set the result as a baseline for future results. The application can periodically resend the query through the pipeline and compare the new results to the baseline. If the new results vary from the baseline above a predetermined threshold, then corrective measures can be taken. This can include notifying an administrator or querying the pipeline for how to change the prompt so that results are more similar to the baseline.

Systems and methods are provided for managing computing services for an application comprising a plurality of virtual computing components executing on one or more host computing devices, wherein a service virtual computing component is to perform application functionality, and wherein a system computing component is to perform system functionality including management of the application virtual computing component; determining the service virtual computing component is to execute using a first access credential to provide a first computing service to the application virtual computing component, and the service virtual computing component is to execute using a second access credential to provide a second computing service to the system computing component, wherein the first access credential is assigned a different set of computing resource access permissions than the second access credential.

The system provides a permissions engine derives permissions for responses from artificial intelligence (AI) agents. The permissions are derived based on the access permissions of chunks used to generate the response, and the response is cached for reuse with users meeting the permissions level. The system can also derive an access permission level for a user attempting to access the cached result or other content. This can be based on a managed access profile that includes user behavior criteria and device criteria. Likewise, the system can validate and derive sensitivity levels of resources that are ingested for use in the artificial intelligence (AI) agents and discriminate between chunks to use in synthesizing results based on the derived permissions of the chunks and their relationship to the user.

The invention provides a rules engine that applies customizable security rules and artificial intelligence (AI) model routing to queries. The rules are evaluated with respect to the query, an anticipate result of the query, and the actual result. Remedial actions are taken when the rule evaluation exceeds a threshold. The remedial actions include transforming the query by replacing sensitive information with a reversible placeholder. The actual result can be modified by reversing the placeholder and redacting additional sensitive information. The system can notify the user, an administrator, and a supervisor regarding the security evaluation and remedial actions. The evaluations can be logged for auditing purposes.

Systems, apparatus, methods, and articles of manufacture for digital delegate computer system architecture that provides for improved multi-agent LLM implementations.

Methods and systems for managing operation of a data processing system are disclosed. A management controller of the data processing system may obtain identifying information for a user of hardware resources of the data processing system. Based on the identifying information, entitlement data for the user may be obtained for use in performance of an entitlement enforcement process. Performance of the entitlement enforcement process may be initiated by the management controller and may include obtaining entitlement compliant hardware resources of the data processing system. A computer-implemented service for which the user is entitled to may be provided using the entitlement compliant hardware resources.

According to examples, an apparatus may include a memory on which is stored machine-readable instructions that may cause a processor to determine, for each of a plurality of members in a group, a respective least privilege level for a resource and determine, based on the determined respective least privilege levels, a privilege level to be assigned to the group for the resource. The instructions may also cause the processor to assign the determined privilege level to the group for the resource and apply the assigned privilege level to the members of the group for the resource.

Systems and methods are described for tool discovery and ingestion for artificial intelligence (“AI”) agents. An AI platform can discover a first tool specification that includes an action and a description. The first tool specification is ingested to create a first tool object. The first tool object includes the action and an endpoint. Tool labels are determined from the specification and applied to the first tool object. A user interface displays the tool object, and it is added to an AI agent. The AI agent includes a manifest file that is used to execute the AI agent. This includes determining whether the AI agent is authorized to perform the action, and providing the AI agent with access to a tool credential, wherein the tool credential is sent to the endpoint.

This document describes systems and techniques directed at exposing application functionality using system-level large language model (LLM) agent services. An electronic device accesses one or more LLMs. An input prompt is received, the input prompt including a plurality of words in a natural-language format. The input prompt is used as an input for the one or more LLMs, which generates an inference output indicative of an intent of the input prompt. An action output is performed based on the intent of the input prompt. An application agent instantiated within an application interface generates the input prompt, parses the input prompt, receives the input prompt, or limits the action output.

The present disclosure generally relates to Blockchain-based systems configured to process access rights to resources in a computationally efficient manner. Certain embodiments of the present disclosure generally relate to systems and methods that generate distributed applications to represent digital access rights to resources. Additionally, certain embodiments of the present disclosure generally relate to systems and methods that enhance the processing of assigning access rights using a Blockchain-based system using metadata.

In some aspects, the HVAC field device described herein includes: a housing; an HVAC functional device; a non-volatile memory unit including: a first set of computer-executable instructions in a first memory partition configured to execute an operating system; and a second set of computer-executable instructions in a second memory partition configured to execute an application module, wherein the application module is configured to control operation of the HVAC functional device; a volatile memory unit; and at least one processor configured to: execute the operating system in a first memory region of the volatile memory unit and execute the application module in a second memory region of the volatile memory unit, wherein the application module is prevented from accessing the first memory region of the volatile memory unit.

Systems and methods are provided for managing computing services for an application, the application comprising a plurality of virtual computing components executing on one or more host computing devices, wherein service virtual computing components are for performing application functions, and wherein system computing components are for performing system functions, the system functions comprising management of the application virtual computing components; determining that a service virtual computing component is for performing using a first access credential to provide a first computing service to an application virtual computing component, and that the service virtual computing component is for performing using a second access credential to provide a second computing service to a system computing component, wherein the first access credential is assigned a different set of computing resource access permissions than the second access credential.

Techniques for deploying a workpiece to a computing environment are disclosed. The system includes a workpiece deployment tool. The workpiece deployment tool determines that a workpiece is available for deployment to a target computing environment. The workpiece deployment tool obtains a deployment token representing verification that a set of one or more customer-specified conditions for deploying a workpiece to a target computing environment is satisfied. The workpiece deployment tool generates a deployment request for deploying a workpiece to a target computing environment. The deployment request includes a deployment token. The workpiece deployment tool directs a deployment request to a deployment service for deploying a workpiece to a target computing environment. The deployment service obtains an acknowledgement of the deployment token and deploys the workpiece to the target computing environment in response to obtaining the acknowledgement of the deployment token.

Systems and methods are described for comparing execution of two or more artificial intelligence (AI) AI agents. A platform can provide a user interface (UI) that allows for selection or creation of multiple AI agents. The AI agents can utilize different agent objects, such as different prompts, datasets, or models. The AI agents can be displayed on a single UI screen, where execution of the AI agents is simultaneously simulated. The same inputs can be provided to the multiple AI agents, and the corresponding outputs can display on screen. The platform can also vectorize and compare the semantic similarity of the outputs, presenting an indicating of the semantic similarity on the same UI screen.

Disclosed are an inter-application data sharing method and an electronic device, and the method is applied to an electronic device, to reduce resource waste and improve efficiency of data sharing between a plurality of applications. The method includes: running a first application in response to a first operation of a user; determining a shared sandbox corresponding to the first application, and writing first data of the first application to the shared sandbox, where the first data is used for sharing with a second application; and running the second application in response to a second operation of the user, and reading the first data from the shared sandbox. The first application and the second application may separately write and read the data in the shared sandbox. Therefore, this can reduce storage resources and resource waste that are caused by partial data overlap between applications, and improve efficiency of data sharing.

Systems and methods are described for tool discovery and ingestion for artificial intelligence (“AI”) agents. An AI platform can discover a first tool specification that includes an action and a description. The first tool specification is ingested to create a first tool object. The first tool object includes the action and an endpoint. Tool labels are determined from the specification and applied to the first tool object. A user interface displays the tool object, and it is added to an AI agent. The AI agent includes a manifest file that is used to execute the AI agent. This includes determining whether the AI agent is authorized to perform the action, and providing the AI agent with access to a tool credential, wherein the tool credential is sent to the endpoint.

According to examples, an apparatus may include a memory on which is stored machine-readable instructions that may cause a processor to determine, for each of a plurality of members in a group, a respective least privilege level for a resource and determine, based on the determined respective least privilege levels, a privilege level to be assigned to the group for the resource. The instructions may also cause the processor to assign the determined privilege level to the group for the resource and apply the assigned privilege level to the members of the group for the resource.

Techniques of remote computing resource access using sharable links are disclosed herein. One example technique includes receiving, at a security portal of a private network, an access request from a client device of a user for accessing a virtual machine ("VM") on the private network via a public network. The technique can then include retrieving a copy of a configuration file corresponding to the virtual machine according to the VM identifier in the access request and accessing the virtual machine according to operating parameters in the retrieved copy of the configuration file to generate an execution result. The technique can further include transmitting, from the security portal, the execution result to the client device of the user via the public network, thereby shielding, with the security portal, the virtual machine on the private network from actions initiated via the public network.

Methods, systems, apparatuses, and computer program products are provided for protecting data in a memory of an integrated circuit (IC). A process token is obtained in a special purpose IC from a host that is external to and communicatively connected to the special purpose IC. The process token is stored in a first memory portion of the special purpose IC. In response to receiving a processing request from the host, the processing request is processed, and data generated by processing the processing request is written in a second memory portion of the special purpose IC. When a read request is received to read the data in the second memory portion, a determination is made whether the read request includes a read token that matches the previously stored process token. If the read token matches the process token, the data in the second memory portion may be returned to the host.

The invention relates to a computer-implemented method for starting up a container instance on a guest computer (H), wherein a runtime environment (L) provided on the guest computer is set up and / or is configured for executing at least one application operated in the container instance, characterized by the following method steps: a) Before starting up the container instance, called the workload container instance (WC), provide and start a container instance initializing the workload container instance, called the init container instance (IC); b) The init container instance creates a namespace (C) with privileges configured for the workload container instance, which is to be assigned to the workload container instance, wherein the namespace to be assigned is created from at least a part of the namespace existing on the guest computer and is returned to the runtime environment as a reference;and c) assigning the generated namespace to the workload container instance and starting the workload container instance through the runtime environment.;

Techniques are described for executing a satisfiability modular theory (SMT) solver in a "shadow" system configuration in which an input query is provided to a primary SMT solver system and additionally to one or more secondary SMT solver systems. The SMT solver system can be used by a cloud provider and used in other computing environments to analyze the effects of configured user account policies that define permissions within the computing environment about user computing resources and associated actions to help ensure security of the computing resources and user data, among other things. The results generated by the primary SMT solver system may be provided to one or more secondary SMT solver systems, where each of the secondary SMT systems may include different system components or different versions of system components to assess correctness of the primary SMT solver system, compare performance metrics, and perform other possible types of analysis.

Methods, systems, and computer program products for modelling and governance for transitive privileged access are provided. A method may include receiving potential transitive access data associated with at least one potential transitive access path, receiving privileged access data associated with a plurality of privileged accesses including a current privileged access, and determining a first target privileged access based on the current privileged access, the potential transitive access data, and the privileged access data. The method may also include generating a first directional graph edge from a first graph node associated with the current privileged access to a second graph node associated with the first target privileged access, the first directional graph edge representing a first transitive access path from the first graph node to the second graph node. The method may also include terminating the current privileged access based on the first transitive access path.

Techniques are described for executing satisfiability modulo theories (SMT) solvers in a "shadow" system configuration where input queries are provided to a primary SMT solver system and additionally to one or more secondary SMT solver systems. SMT solver systems can be used by cloud providers and in other computing environments to analyze the implications of configured user account policies defining permissions with respect to users' computing resources and associated actions within a computing environment, to help ensure the security of computing resources and user data, etc. The results generated by a primary SMT solver system can be provided to one or more secondary SMT solver systems, where each of the secondary SMT systems can comprise different system components or different versions of system components, to assess the correctness of the primary SMT solver system, to compare performance metrics, among other possible types of analyses.