Telefonaktiebolaget lm ericsson (publ) (20240338596). SIGNALLING MODEL PERFORMANCE FEEDBACK INFORMATION (MPFI) simplified abstract
Contents
SIGNALLING MODEL PERFORMANCE FEEDBACK INFORMATION (MPFI)
Organization Name
telefonaktiebolaget lm ericsson (publ)
Inventor(s)
Ioanna Pappa of STOCKHOLM (SE)
[[:Category:Henrik Ryd�n of STOCKHOLM (SE)|Henrik Ryd�n of STOCKHOLM (SE)]][[Category:Henrik Ryd�n of STOCKHOLM (SE)]]
Angelo Centonza of GRANADA (ES)
SIGNALLING MODEL PERFORMANCE FEEDBACK INFORMATION (MPFI) - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338596 titled 'SIGNALLING MODEL PERFORMANCE FEEDBACK INFORMATION (MPFI)
Simplified Explanation:
The abstract describes a method performed by a network node involving obtaining model performance feedback information for an artificial intelligence model and providing this information to a model training function to determine if the AI model needs updating or replacement.
- The first network node obtains model performance feedback information for an AI model.
- The obtained information is provided to a model training function.
- The model training function uses the feedback information to decide if the AI model requires updating or replacement.
Key Features and Innovation:
- Utilization of model performance feedback information for AI model maintenance.
- Integration of feedback loop to enhance AI model efficiency.
- Automated decision-making process for AI model updates or replacements.
Potential Applications:
This technology can be applied in various industries such as healthcare, finance, and manufacturing where AI models are utilized for decision-making processes.
Problems Solved:
- Ensures AI models are up-to-date and efficient.
- Streamlines the process of AI model maintenance.
- Improves overall performance of AI systems.
Benefits:
- Enhanced accuracy and reliability of AI models.
- Cost-effective maintenance of AI systems.
- Increased efficiency in decision-making processes.
Commercial Applications:
Title: AI Model Maintenance Technology for Enhanced Performance
This technology can be commercially used in AI-driven industries such as predictive analytics, autonomous vehicles, and personalized recommendations, leading to improved operational efficiency and competitive advantage in the market.
Prior Art:
Readers can explore prior research on AI model maintenance, performance feedback mechanisms, and automated decision-making processes in AI systems to understand the evolution of this technology.
Frequently Updated Research:
Stay updated on advancements in AI model maintenance, feedback mechanisms, and decision-making algorithms to enhance the performance and reliability of AI systems.
Questions about AI Model Maintenance Technology:
1. How does the feedback loop in AI model maintenance contribute to overall system efficiency? 2. What are the potential challenges in implementing automated decision-making processes for AI model updates and replacements?
Original Abstract Submitted
a method () performed by a first network node (). the method includes the first network node obtaining (s) model performance feedback information (mpfi) for an artificial intelligence (ai) model. the method also includes the first network node providing (s) the mpfi to a model training function (). the mpfi provides information that the model training function () can use to determine whether the ai model needs to be updated or replaced by a new ai model.
