18077006. ANALYZING AND ALTERING AN EDGE DEVICE POLICY USING AN ARTIFICIAL INTELLIGENCE (AI) REASONING MODEL simplified abstract (International Business Machines Corporation)

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ANALYZING AND ALTERING AN EDGE DEVICE POLICY USING AN ARTIFICIAL INTELLIGENCE (AI) REASONING MODEL

Organization Name

International Business Machines Corporation

Inventor(s)

Nathan Andrew Phelps of Durham NC (US)

Ryan Anderson of Kensington CA (US)

Ashok Kumar Iyengar of Encinitas CA (US)

Kavitha Bade of Durham NC (US)

Joseph Andrew Pearson of Brookhaven GA (US)

Troy Fine of Sutter Creek CA (US)

ANALYZING AND ALTERING AN EDGE DEVICE POLICY USING AN ARTIFICIAL INTELLIGENCE (AI) REASONING MODEL - A simplified explanation of the abstract

This abstract first appeared for US patent application 18077006 titled 'ANALYZING AND ALTERING AN EDGE DEVICE POLICY USING AN ARTIFICIAL INTELLIGENCE (AI) REASONING MODEL

Simplified Explanation: The patent application describes a method for deploying policies to edge devices in an edge computing environment using artificial intelligence reasoning models to analyze and understand the intent of the policy deployment.

  • The method involves analyzing the policy to determine its intent and adjusting it based on the analysis.
  • The analysis includes discounting irrelevant data points that do not apply to the current decision of the edge device.
  • This technology aims to optimize policy deployment in edge computing environments by leveraging AI reasoning models.

Key Features and Innovation:

  • Deployment of policies to edge devices in an edge computing environment.
  • Analysis of policies using artificial intelligence reasoning models.
  • Discounting irrelevant data points to optimize policy deployment.
  • Altering policies based on the analysis to improve decision-making.

Potential Applications: This technology can be applied in various industries such as IoT, smart cities, healthcare, and manufacturing to enhance decision-making processes in edge computing environments.

Problems Solved:

  • Optimizing policy deployment in edge computing environments.
  • Improving decision-making processes in real-time.
  • Enhancing the efficiency of edge devices by analyzing policies effectively.

Benefits:

  • Enhanced decision-making capabilities in edge computing environments.
  • Improved efficiency and performance of edge devices.
  • Better utilization of data points for policy deployment.

Commercial Applications: Potential commercial applications include IoT devices, smart city infrastructure, healthcare systems, and manufacturing processes, where real-time decision-making is crucial for operational efficiency.

Prior Art: Prior research in edge computing, artificial intelligence reasoning models, and policy deployment in IoT devices may provide insights into similar technologies.

Frequently Updated Research: Stay updated on advancements in edge computing, artificial intelligence, and policy optimization in IoT devices to enhance the efficiency of this technology.

Questions about Policy Deployment in Edge Computing: 1. How does the use of artificial intelligence reasoning models improve policy deployment in edge computing environments? 2. What are the key factors to consider when analyzing policies for edge devices using AI reasoning models?


Original Abstract Submitted

A computer-implemented method, according to one embodiment, includes deploying a policy to edge devices in an edge computing environment. The method further includes analyzing, using an artificial intelligence (AI) reasoning model, the policy to understand an intent of deploying the policy. The analyzing includes discounting a weight value assigned to data points that are determined to not apply to a current decision of a first of the edge devices. The method further includes causing the policy to be altered based on the analysis. A computer program product, according to another embodiment, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

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