18575792. ENHANCED ON-THE-GO ARTIFICIAL INTELLIGENCE FOR WIRELESS DEVICES simplified abstract (Intel Corporation)
Contents
ENHANCED ON-THE-GO ARTIFICIAL INTELLIGENCE FOR WIRELESS DEVICES
Organization Name
Inventor(s)
Markus Dominik Mueck of Unterhaching (DE)
Miltiadis Filippou of Muenchen (DE)
Thomas Luetzenkirchen of Taufkirchen (DE)
Leonardo Gomes Baltar of Muenchen (DE)
ENHANCED ON-THE-GO ARTIFICIAL INTELLIGENCE FOR WIRELESS DEVICES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18575792 titled 'ENHANCED ON-THE-GO ARTIFICIAL INTELLIGENCE FOR WIRELESS DEVICES
The abstract describes a system that helps User Equipment (UE) devices connected to a radio access network (RAN) with machine learning-based operations.
- Network AI/ML service identifies a request for a machine learning model configuration from a UE device.
- The system determines the location of the UE device and selects an available machine learning agent based on the request and location.
- A second request is formatted to the selected machine learning agent for the configuration.
- The system identifies and formats a response with the machine learning configuration for the UE device.
Potential Applications: - Enhancing machine learning capabilities in UE devices. - Improving network efficiency and performance through optimized machine learning configurations.
Problems Solved: - Streamlining the process of configuring machine learning models for UE devices. - Enhancing the overall user experience by providing tailored machine learning configurations.
Benefits: - Increased efficiency in machine learning operations. - Enhanced network performance and user satisfaction.
Commercial Applications: - Telecom companies can utilize this technology to enhance their network performance and provide better services to their customers.
Questions about the technology: 1. How does this system improve the overall performance of UE devices connected to a RAN? 2. What are the potential implications of using machine learning-based operations in network management and optimization?
Original Abstract Submitted
This disclosure describes systems, methods, and devices related to facilitating machine learning-based operations at a User Equipment (UE) connected to a radio access network (RAN). A network AI/ML (artificial intelligence/machine learning) service or function may identify a first request, received from a user equipment (UE) device, for a machine learning model configuration; determine a location of the UE device; select, based on the first request and the location, an available machine learning agent; format a second request to the available machine learning agent for the machine learning configuration; identify the machine learning configuration received from the available machine learning agent based on the second request; and format a response to the first request, the response comprising the machine learning configuration for the UE device.
