17806794. SCENARIO AWARE DYNAMIC CODE BRANCHING OF SELF-EVOLVING CODE simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

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SCENARIO AWARE DYNAMIC CODE BRANCHING OF SELF-EVOLVING CODE

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

Saraswathi Sailaja Perumalla of Visakhapatnam (IN)

Sarbajit K. Rakshit of Kolkata (IN)

Sowjanya Rao of Hyderabad (IN)

SCENARIO AWARE DYNAMIC CODE BRANCHING OF SELF-EVOLVING CODE - A simplified explanation of the abstract

This abstract first appeared for US patent application 17806794 titled 'SCENARIO AWARE DYNAMIC CODE BRANCHING OF SELF-EVOLVING CODE

Simplified Explanation

The patent application describes computer technology that allows an AI-enabled edge device, such as an autonomous vehicle or industrial robotic device, to dynamically adapt its code based on successful execution of a contextual scenario. This technology predicts a second contextual scenario where the device can perform a specific activity and proactively deploys self-adapted code on the device.

  • The technology enables dynamic code branching of self-adapted code on an AI-enabled edge device.
  • It relies on the successful execution of a contextual scenario by the device.
  • The technology predicts a second contextual scenario where the device can perform a predetermined activity.
  • It proactively deploys self-adapted code on the device to handle the predicted scenario.

Potential Applications

This technology has potential applications in various fields, including:

  • Autonomous vehicles: The AI-enabled edge device can adapt its code based on successful execution of contextual scenarios, improving its ability to handle different driving situations.
  • Industrial robotics: The technology allows robotic devices to dynamically adapt their code to perform specific activities based on contextual scenarios, enhancing their efficiency and versatility.
  • Smart home systems: AI-enabled edge devices in smart homes can use this technology to adapt their code and perform different tasks based on changing environmental conditions or user preferences.

Problems Solved

The technology addresses several problems:

  • Lack of adaptability: Traditional code in AI-enabled edge devices is typically static and cannot adapt to changing scenarios. This technology solves this problem by enabling dynamic code branching and self-adaptation.
  • Inefficiency: Without proactive deployment of self-adapted code, AI-enabled edge devices may not be able to efficiently handle predicted scenarios. This technology solves this problem by proactively deploying the necessary code.
  • Limited versatility: AI-enabled edge devices may have limited capabilities to handle different contextual scenarios. This technology solves this problem by predicting and preparing for specific scenarios, expanding the device's range of applications.

Benefits

The technology offers several benefits:

  • Improved performance: By dynamically adapting its code, the AI-enabled edge device can optimize its performance based on successful execution of contextual scenarios.
  • Enhanced efficiency: Proactively deploying self-adapted code allows the device to efficiently handle predicted scenarios, reducing response times and resource consumption.
  • Increased versatility: The ability to predict and prepare for specific scenarios enables the device to perform a wider range of activities, making it more versatile and adaptable to different environments.


Original Abstract Submitted

Computer technology for performing dynamic code branching of self-adapted code upon successful execution of a contextual scenario by artificial intelligence (AI) enabled edge device (for example, an autonomous vehicle or an industrial robotic device). predicting a second contextual scenario where the AI enabled edge device can perform a predetermined activity, and proactively deploying self-adapted code on the AI enabled edge device.