Intel corporation (20240354654). ARTIFICIAL INTELLIGENCE/MACHINE LEARNING TRAINING SERVICES IN NON-REAL TIME RADIO ACCESS NETWORK INTELLIGENT CONTROLLER simplified abstract
ARTIFICIAL INTELLIGENCE/MACHINE LEARNING TRAINING SERVICES IN NON-REAL TIME RADIO ACCESS NETWORK INTELLIGENT CONTROLLER
Organization Name
Inventor(s)
Dawei Ying of Portland OR (US)
Jaemin Han of Portland OR (US)
ARTIFICIAL INTELLIGENCE/MACHINE LEARNING TRAINING SERVICES IN NON-REAL TIME RADIO ACCESS NETWORK INTELLIGENT CONTROLLER - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240354654 titled 'ARTIFICIAL INTELLIGENCE/MACHINE LEARNING TRAINING SERVICES IN NON-REAL TIME RADIO ACCESS NETWORK INTELLIGENT CONTROLLER
The patent application pertains to a non-real-time radio access network intelligent controller within a service management and orchestration framework. Communication between service consumers and producers includes requests for AI/ML training jobs, status queries, cancellation requests, and notifications.
- Non-real-time radio access network intelligent controller for service management and orchestration framework.
- Communication between service consumers and producers for AI/ML training jobs.
- Requests include training, status queries, cancellations, and notifications.
- Machine-readable storage medium, apparatus, and method for facilitating communication.
Potential Applications: - Telecommunications industry for efficient management of AI/ML training jobs. - Network optimization and resource allocation in non-real-time environments.
Problems Solved: - Streamlining communication between service consumers and producers. - Enhancing the efficiency of AI/ML training job management.
Benefits: - Improved coordination and monitoring of AI/ML training jobs. - Enhanced performance and resource utilization in non-real-time networks.
Commercial Applications: Optimizing network performance and resource allocation in telecommunications companies.
Prior Art: Research existing patents related to non-real-time network management and AI/ML training job coordination.
Frequently Updated Research: Stay updated on advancements in non-real-time network management and AI/ML training job optimization.
Questions about the technology: 1. How does the non-real-time radio access network intelligent controller improve network efficiency? 2. What are the key benefits of using AI/ML training jobs in service management and orchestration frameworks?
Original Abstract Submitted
a machine-readable storage medium, an apparatus and a method, each corresponding to either a service consumer or a service producer of a non-real-time (non-rt) radio access network intelligent controller (ric) of a service management and orchestration framework (smo fw). communications from the service consumer to the service producer include: a training request for artificial intelligence/machine learning (ai/ml) training job; a query regarding a training status of the ai/ml training job; a cancel training request to cancel the ai/ml training job; and a notification regarding the training status of the ai/ml training job.
