121 results about "Orchestration" patented technology

Some implementations of the disclosure provide a computer-implemented method including operations of receiving, by an orchestration agent, user input corresponding to a user question, wherein generating a response to the user question includes one of generating, editing, or refining programming code, and generating, by the orchestration agent, a prompt instructing a first sub-large language model (LLM) to perform a first task. In response to the prompt, generating, by the first sub-LLM, instructions for a second sub-LLM to perform a second task, wherein results of performing the second task by the second sub-LLM are provided to the first sub-LLM and performing, by the first sub-LLM, the first task utilizing the results of the second task generated by the second sub-LLM. An additional operation includes generating, by the orchestration agent, a GUI that displays the response to the user question, wherein the response includes or is based on the programming code.

A system for context-sensitive orchestration of autonomous agents in cloud platforms, consisting of: a hardware-based orchestration device configured for integration into a distributed cloud infrastructure; a context inference engine within the orchestration device, wherein the context inference engine is configured to receive and aggregate real-time telemetry data from a variety of distributed nodes, including at least one system-level parameter, at least one application-level parameter, and at least one environment parameter; a semantic inference module within the context inference engine, configured to generate a context-related state representation by correlating the parameters using a knowledge graph-based model of interdependencies; an optimization unit for machine learning within the orchestration device, which is communicatively connected to the context inference engine and is configured to predict resource requirements and operational states using reinforcement learning models trained on historical and real-time data streams; a policy-driven orchestration controller configured to translate the contextual state representation into actionable orchestration decisions by applying dynamic orchestration policies stored in a domain-specific policy repository; and a distributed agent interaction bus configured to delegate orchestration decisions to a variety of autonomous agents deployed on the cloud platform.

A system for latency-aware orchestration and performance optimization in AI-driven telephone communication, consisting of: a speech capture unit configured to capture an analog audio signal from a telephone interface and convert the analog audio signal into a digital audio signal stream; a feature extraction unit that is operationally coupled with the speech acquisition unit and is configured to generate a feature representation of the digital audio signal stream through spectral decomposition, noise reduction, and temporal segmentation; an AI inference processor communicatively connected to the feature extraction unit, configured to run one or more AI models for automatic speech recognition, natural language understanding, and emotion recognition on the feature representation to generate intermediate results for inference; a latency orchestration controller coupled to the AI ​​inference processor, wherein the latency orchestration controller is configured to monitor latency across multiple processing stages, predict cumulative delay propagation using a hybrid latency estimation model, and orchestrate the execution scheduling of the AI ​​inference processor based on the predicted latency deviation; a performance optimization unit coupled with the latency orchestration controller and configured to dynamically adjust computational accuracy, inference batch size, and feature processing resolution based on latency thresholds and quality constraints set by the latency orchestration controller; and a transmission synchronization array configured to time-align the processed output generated by the AI ​​inference processor and transmit it to a remote communication node, with the transmission synchronization array maintaining deterministic time coordination between successive packets and the orchestrated inference results.

The invention provides a service orchestration method and device and related equipment, and the method comprises the steps: obtaining a first state space and a first action space of a to-be-orchestrated service, the first state space being used for representing the states of a server and an interface related to the to-be-orchestrated service, and the first action space being used for representing the states of the server and the interface related to the to-be-orchestrated service; the first action space is used for representing an interface function and a calling relation of an interface related to the to-be-arranged service; based on the first state space and the first action space, generating first calling information of an interface related to the to-be-arranged service; based on the first action space, M candidate interface calling sequences of the to-be-arranged service are generated, and M is a positive integer; selecting a target interface calling sequence matched with the first calling information from the M candidate interface calling sequences; and performing link configuration on the to-be-arranged service based on the target interface calling sequence.

The invention discloses a cross-culture melody feature extraction and musical instrument matching system based on deep learning, and belongs to the technical field of music information processing and artificial intelligence. The system comprises an audio acquisition module, an audio preprocessing module, a melody feature extraction module, a cultural context understanding module, an emotion semantic analysis module, a musical instrument timbre database, a musical instrument matching recommendation module, a distributor scheme generation module, a user interaction module and an audio synthesis module. Multi-dimensional melody features are extracted through a multi-scale convolutional neural network and a bidirectional long-short term memory network, cultural semantic understanding is realized through reasoning on a music knowledge graph by using a graph neural network, and musical instrument matching is performed by using a multi-objective optimization algorithm in combination with three dimensions of timbre integrating degree, cultural consistency and emotional expressive power. According to the system, automation of the whole process from humming melody to musical instrument configuration is achieved, the efficiency of the instrument is improved by 400%, the accuracy rate reaches 92%, and an intelligent tool is provided for cross-culture music creation and national music modernization reorganization.

The invention relates to the technical field of virtualization orchestration, in particular to an industrial control virtualization orchestration system and method, and the system comprises a task extraction module, a node behavior monitoring module, a stability evaluation module, an orchestration load adjustment module and a control task migration module. According to the method, the scheduling cycle closed-loop feature recognition is performed by collecting the control task scheduling mapping table and the execution instruction queue and combining the cycle control mark and the interrupt mark, so that an orchestratable task set can be effectively recognized, the behavior success rate is calculated according to parameters such as node response delay and task completion proportion, and node stability screening is performed; stability grade division of control nodes is achieved, a scheduling priority list is formed by setting a release threshold value, then the task migration opportunity is judged based on task residence time and IO completion conditions, migration targets are accurately selected in a behavior pattern matching mode, and the stability of task scheduling, the precision of resource allocation and the adaptability of control logic are remarkably improved.

Various systems and methods for implementing intent-based orchestration in heterogenous compute platforms are described herein. An orchestration system is configured to: receive, at the orchestration system, a workload request for a workload, the workload request including an intent-based service level objective (SLO); generate rules for resource allocation based on the workload request; generate a deployment plan using the rules for resource allocation and the intent-based SLO; deploy the workload using the deployment plan; monitor performance of the workload using real-time telemetry; and modify the rules for resource allocation and the deployment plan based on the real-time telemetry.

Techniques are described for performing an automated region build. An orchestration service (e.g., a Multi-Flock Orchestrator) may managing bootstrapping efforts for any suitable number of services within a region corresponding to one or more data centers. Each service can be associated with a respective set of resources (e.g., infrastructure components, software artifacts, etc.). The orchestration service can identify dependencies between services based on corresponding configuration files associated with the services. The orchestration service can determine, based on the identified dependencies, an order by which operations for bootstrapping the services are to be performed. The orchestration service can incrementally instruct other system components (e.g., a provisioning and deployment manager) to perform operations for bootstrapping the plurality of services in accordance with determined order.

Long-term memory data objects may be generated for orchestrations agents. When a session completes or ends, a long-term memory data object may be generated according to a specified long-term memory type based on turn inputs during the session. When a new session is started, the long-term memory data object may be used as part of inputs to a generative machine learning model to perform or respond to turn inputs of the new session.

Various systems and methods for reactive intent-driven end-to-end (E2E) orchestration are described herein. An orchestrator system, includes a processor; and memory to store instructions, which when executed by the processor, cause the system to: receive, at the orchestrator system, an intent-based service level agreement (SLA) for execution of a series of tasks on a plurality of compute nodes; calculate, based on the intent-based SLA, intermediate latency thresholds corresponding to each task of the series of tasks; calculate slack estimates based on the latency thresholds and real-time telemetry of the plurality of compute nodes or real-time telemetry of connections between the plurality of compute nodes; monitor execution of the series of tasks on the plurality of compute nodes; and perform a corrective action in response to determining that the execution of the series of tasks is predicted to exceed one of the intermediate latency thresholds.

Approaches presented herein provide for the management of resources to be used to process a request, such as may involve orchestration of nodes for an inference request. Upon receiving an inference request, an orchestrator can determine a sequence of context nodes and inference nodes to be used to process the inference request, based in part upon a determined class of inferencing to be performed. The orchestrator can append metadata to the inference request that identifies the sequence, and can transmit the appended request to one or more first nodes in the sequence. If the nodes have a network programmable device, or similar capability, the request can be forwarded to the nodes in sequence without having to go back to the orchestrator between nodes.

Systems and methods for providing trusted local orchestration of workspaces are described. In some embodiments, an information handling system (IHS) can include: a processor; and a system memory coupled to the processor, the system memory having program instructions stored thereon that, when executed, cause the IHS to: receive, from a workspace orchestration service, orchestration code; use a trusted controller coupled to the processor to record a log, the log including: the orchestration code, and an indication of a sequence of operations performed by a local management agent during instantiation of a workspace; provide, to the workspace orchestration service, a copy of the log; and in response to the workspace orchestration service successfully: (i) authenticating the orchestration code, and (ii) verifying the sequence of operations, establish a connection between the workspace and the workspace orchestration service.

A system and method are disclosed for generating personalized motivational, wellness, educational, and entertainment multimedia content using multimodal artificial intelligence. The system constructs an Emotion State Vector (ESV) from user inputs, diaries, biometric data, and context. A Modality Script Generator (MSG) defines time-coded orchestration across music, narration, captions, and visuals. Scripts execute via a Model-Agnostic Adapter Layer (MAAL) across heterogeneous Al engines. A Synchronization Graph (SyncGraph) maintains acceptable inter-modal drift, while a Dynamic Media Formatter (DMF) applies bounded repair policies and packages synchronized outputs with timed metadata. A Policy / Constraint Graph enforces rights and provenance, logged in a Transform Manifest.

Computer systems and methods with decentralized blockchain orchestration architecture use multiple orchestrators embedded at the cluster level. A push architecture is provided for manipulating and verifying workload configurations, including the ability to determine differences between stored configurations and actual configurations.

A cloud infrastructure orchestration service (CIOS) may track build progress by any suitable number of area orchestrators. The orchestrator control plane may be configured to generate an area build plan for guiding a plurality of services within the data center. The orchestrator control plane may instruct the area orchestrator to perform the build according to the build plan. The region orchestrator may be configured to update an execution state corresponding to execution of the region construction plan when it executes a step of the ordered steps of the region construction plan. Intervention data may be received at any suitable time (e.g., when performing one of the steps fails), using which new region building plans may be generated. The new region build plan may be used for subsequent region build execution. This may enable runtime correction.

The invention proposes a computer-implemented mobile orchestration instance (2) which is designed a) to define task types (3, 3a), wherein the task types (3, 3a) each comprise a sequence of work steps (5, 6) and associated parameters (4, 7, 8) which are necessary for a mobile device of a process system of a specific type to implement a specific transport operation and / or handling operation, b) to instantiate one or more of the task types (3, 3a) as an executable software instance (4, 7, 8) as part of the computer-implemented mobile orchestration instance (10) in order to define one or more task services (9, 9a), c) to encapsulate the task services (9, 9a) as services (10a, 10b, 10c, 10d, 10e, 10f) according to the standard VDI / VDE / NAMUR 2658 which is valid at the time of the present patent application, and d) to integrate the encapsulated task services (9, 9a) into a computer-implemented orchestration instance (1) using an OPC UA server (12) provided by the computer-implemented mobile orchestration instance (2).

As described herein, a system, method, and computer program are provided for general intent to specific service modeling in intent-based orchestration. An intent specifying one or more parameters of a service required for a network is received. The intent is modeled as a root intent service that represents the one or more parameters of the service specified by the intent. The root intent service is decomposed into one or more specific services of a network orchestrator. The one or more specific services are caused to be instantiated in the network in order to fulfill the intent.

Disclosed are methods and systems for orchestrating application performance testing using state machines. For instance, at least a portion of information included in a request to run a performance test on an application may be received, the portion including each component of the application. Each component of the application may be deployed in a performance testing environment, and a script for the performance test may be generated based on one or more application performance metrics associated with the application. The performance test may be generated in accordance with the script and run on the application in the performance testing environment. Upon detecting a completion of the performance test, each component of the application deployed in the performance testing environment may be destroyed.

An information processing system may include at least one processor and a memory. The information processing system may be configured to: execute a workload orchestrator configured to distribute workloads to multiple nodes for execution thereon; receive an event notification indicating a hardware problem associated with a specific node; translate the event notification into an orchestration state for the specific node; and, based on the orchestration state, stop distributing workloads to the specific node.

A computer system for training a plurality of chatbots using artificial intelligence (AI) tools to process statements is provided. The computer system includes an orchestration computing device, and an AI module. The AI module is programmed to: (i) receive a verbal statement of the user including a plurality of words; (ii) translate the verbal statement into a text statement; (iii) augment the text statement by determining at least one intent of the text statement; (iv) provide recommendations for responding to the augmented text statement; (v) analyze the augmented text statement and the recommendations; (vi) generate data representing an audio response to the analyzed augmented text statement; and (vii) present the audio response to the user by causing a selected chatbot to execute the generated data.

Techniques are described for configuring and using analytics for requested software components deployed within cloud-based and other distributed computing environments. An orchestration system may determine particular analytics for a requested component implemented within a computing environment, based on the deployed workloads and / or computing resources on which the requested component was deployed. In conjunction with orchestration of the requested component, the orchestration system may determine the associated performance metrics, including particular telemetry metrics and / or composite metrics, based on the orchestration of the requested component. The orchestration system also may manage the presentation of the performance analytics for the requested component, including customized dashboards with component-specific metrics and / or alerts to target devices associated with the requested component.

The invention discloses a melody perception music reorganization method and system based on structure-texture feature decoupling. The method comprises the steps of constructing a weak pairing data set containing the same melody skeleton and different acoustic texture audio pairs, training a comparison melody encoder based on the data set to extract pure melody structure characterization, then training a double-circulation-flux recompilation generation model, and finally completing recompilation generation of a target audio. The system comprises a data set construction module, an encoder training module, a generative model training module and a reasoning generation module, and the core of the system comprises a contrast melody encoder and a double-circulation-flux modification generative model. According to the method, the problems of feature entanglement and text control failure are solved, the melody consistency and the model generalization ability are improved, and the method can be widely applied to the fields of digital music creation, short video content production, old audio reproduction and the like.

A traffic strategy and / or management system is adapted to generate and / or implement one or more strategy options to achieve user-defined objectives. The system includes an orchestration device connected to at least one data source device, at least one infrastructure device, and at least one management or control device. The orchestration device is also connected to a strategy generation device configured to create at least one traffic management strategy and / or a set of control instructions for all infrastructure devices associated with the strategy to achieve the user-defined objectives. The data source device includes modeling data and real-time data, which are provided and utilized by the strategy generation device and received by the orchestration device to create the traffic management strategy and / or the set of control instructions in real-time and / or near real-time.

Long-term memory data objects may be generated for orchestrations agents. When a session completes or ends, a long-term memory data object may be generated according to a specified long-term memory type based on turn inputs during the session. When a new session is started, the long-term memory data object may be used as part of inputs to a generative machine learning model to perform or respond to turn inputs of the new session.

In some implementations, a management system may receive a request from an independent moving object. The management system may determine, based on the request, a group of moving objects including a leader moving object. The management system may transmit, to the leader moving object, group information to enable the independent moving object to join the group of moving objects.

Systems and methods for orchestration based on workspace component scores are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the IHS to receive, at a local management agent from a workspace orchestration service, one or more files or policies configured to enable the local management agent to instantiate a workspace based upon a workspace definition, where the workspace comprises a plurality of workspace components, where the workspace definition is created based, at least in part, upon a security target, and where an aggregated security score for the plurality of workspace components meets the security target; and instantiate the workspace.

The present disclosure relates to the technical field of computers and relates to a variable processing method and apparatus for a flow orchestration process, and a storage medium and a program product. The variable processing method for a flow orchestration process comprises: for a plurality of flow nodes provided in a flow orchestration interface, creating a storage space corresponding to each flow node; storing, in the storage space corresponding to each flow node, a variable defined on each flow node; and in response to an operation for acquiring a variable accessible to any flow node, acquiring a variable in a storage space corresponding to a first flow node having a first association relationship with said flow node, and using the variable as the variable accessible to said flow node for display in the flow orchestration interface.

A computer system for training a plurality of chatbots using artificial intelligence (AI) tools to process statements is provided. The computer system includes an orchestration computing device, and an AI module. The AI module is programmed to: (i) receive a verbal statement of the user including a plurality of words; (ii) translate the verbal statement into a text statement; (iii) augment the text statement by determining at least one intent of the text statement; (iv) provide recommendations for responding to the augmented text statement; (v) analyze the augmented text statement and the recommendations; (vi) generate data representing an audio response to the analyzed augmented text statement; and (vii) present the audio response to the user by causing a selected chatbot to execute the generated data.

A request to deploy an application is received at a network function management service of a cloud computing environment. Based on an expected geographical distribution of the application, a premise is selected from a set of premises at which computing resource are managed from the cloud computing environment. A virtualized network function of the application is executed at a resource located at the premise.

The present invention relates to an MSA-based device orchestration apparatus in a digital federated twin, the MSA-based device orchestration apparatus comprising: a request reception unit that receives a control request message for a device and carries out a unit processing partitioning operation for the control request message to generate divided control commands; a control sequence request transmission unit that receives the divided control commands, identifies a control sequence required for the device, determines a command order and task content, and requests execution of the control sequence from the device; a control sequence processing result reception unit that receives a processing result of the control sequence from the device, applies a filter for determining, on the basis of the processing result, whether to execute business logic and whether to proceed with a next control sequence, and transmits, to the control sequence request transmission unit, the next control sequence that has passed through the filter; a request state check unit that checks a processing state of the divided control commands and schedules a control sequence required for the device; and a request processing result transmission unit that transmits a processing result of the device upon completion of the divided control commands.