18294985. SIGNALLING MODEL PERFORMANCE FEEDBACK INFORMATION (MPFI) simplified abstract (Telefonaktiebolaget LM Ericsson (publ))
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 18294985 titled 'SIGNALLING MODEL PERFORMANCE FEEDBACK INFORMATION (MPFI)
The abstract describes a method performed by a network node involving obtaining model performance feedback information for an AI model and providing this information to a model training function to determine if the AI model needs updating or replacement.
- The method involves obtaining model performance feedback information (MPFI) for an AI model.
- The network node provides the MPFI to a model training function.
- The MPFI helps the model training function determine if the AI model needs to be updated or replaced.
- This process aims to improve the performance and efficiency of AI models.
- The method enhances the adaptability and effectiveness of AI systems in various applications.
Potential Applications: - Enhancing the performance of AI models in various industries such as healthcare, finance, and manufacturing. - Optimizing AI systems for better decision-making processes in autonomous vehicles and robotics. - Improving the accuracy and reliability of AI models in natural language processing and image recognition tasks.
Problems Solved: - Addressing the need for continuous monitoring and improvement of AI model performance. - Streamlining the process of updating or replacing AI models based on feedback information. - Enhancing the overall efficiency and effectiveness of AI systems in real-world applications.
Benefits: - Increased accuracy and reliability of AI models. - Improved decision-making processes in various industries. - Enhanced adaptability and performance of AI systems in dynamic environments.
Commercial Applications: Title: "Enhancing AI Model Performance in Various Industries" This technology can be utilized in industries such as healthcare, finance, and manufacturing to optimize AI systems for better decision-making processes, leading to improved efficiency and productivity. The market implications include increased demand for AI solutions that can adapt and evolve based on real-time feedback information.
Questions about AI Model Performance Improvement: 1. How does the method of obtaining model performance feedback information contribute to the overall effectiveness of AI models? - The method allows for continuous monitoring and improvement of AI model performance, leading to enhanced accuracy and reliability in various applications.
2. What are the potential implications of using the model training function to determine the need for updating or replacing AI models? - By utilizing the model training function, organizations can streamline the process of improving AI model performance based on feedback information, resulting in more efficient and effective AI systems.
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.
