Samsung electronics co., ltd. (20240098533). AI/ML MODEL MONITORING OPERATIONS FOR NR AIR INTERFACE simplified abstract
Contents
- 1 AI/ML MODEL MONITORING OPERATIONS FOR NR AIR INTERFACE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 AI/ML MODEL MONITORING OPERATIONS FOR NR AIR INTERFACE - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
AI/ML MODEL MONITORING OPERATIONS FOR NR AIR INTERFACE
Organization Name
Inventor(s)
Jeongho Jeon of San Jose CA (US)
Kyeongin Jeong of Allen TX (US)
Caleb K. Lo of San Jose CA (US)
AI/ML MODEL MONITORING OPERATIONS FOR NR AIR INTERFACE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240098533 titled 'AI/ML MODEL MONITORING OPERATIONS FOR NR AIR INTERFACE
Simplified Explanation
An AI/ML monitoring operation is described in the patent application, which involves receiving a monitoring configuration as part of a larger configuration for using an AI/ML model in a communications system operation. Based on this monitoring configuration, assistance information related to the AI/ML model is reported, including monitoring results from the AI/ML monitoring operation. Additionally, management and adaptation information for the AI/ML model is received based on the monitoring results, leading to a series of AI/ML model management and adaptation operations.
- The patent application focuses on utilizing an AI/ML model in a communications system operation.
- The monitoring configuration plays a crucial role in reporting AI/ML model assistance information and monitoring results.
- The received management and adaptation information is used to perform AI/ML model management and adaptation operations, which may involve actions like model switch, refinement, or update.
Potential Applications
The technology described in the patent application could be applied in various industries and fields, including telecommunications, data analysis, predictive maintenance, and automation.
Problems Solved
This technology helps in efficiently managing and adapting AI/ML models used in communications system operations, ensuring optimal performance and accuracy. It streamlines the monitoring process and facilitates timely adjustments based on monitoring results.
Benefits
- Improved performance of AI/ML models in communications systems - Enhanced accuracy and reliability of data analysis - Streamlined monitoring and management processes - Facilitates quick adaptation based on monitoring results
Potential Commercial Applications
"AI/ML Model Management and Adaptation in Communications Systems" could find applications in telecommunications companies, data analytics firms, automation industries, and predictive maintenance services.
Possible Prior Art
One possible prior art could be existing systems or methods for monitoring and managing AI/ML models in various applications, such as data analysis, predictive maintenance, and automation.
Unanswered Questions
== What specific types of AI/ML models are most commonly used in communications system operations? The patent application does not specify the exact types of AI/ML models that are typically utilized in communications system operations. It would be beneficial to know which models are most prevalent in this context and why.
== How does the monitoring configuration impact the overall performance of the AI/ML model in a communications system operation? The patent application discusses the importance of the monitoring configuration but does not delve into the specific ways in which it influences the performance of the AI/ML model. Understanding this relationship could provide valuable insights into optimizing model management and adaptation strategies.
Original Abstract Submitted
an ai/ml monitoring operation is based on a received monitoring configuration forming part of a configuration for using an ai/ml model for a communications system operation. based on the monitoring configuration, ai/ml model assistance information is reported, including ai/ml model monitoring results from the ai/ml monitoring operation. ai/ml model management and adaptation information based on those ai/ml model monitoring results is received, an ai/ml model management and adaptation operation is performed. the ai/ml model management and adaptation information may include parameters that characterize an action of ai/ml model management and adaptation or an indication of an action of ai/ml model management and adaptation. the action of ai/ml model management and adaptation may comprise one of model switch, model refinement or update, or model transfer.
