17454568. MODEL PRODUCTIZATION ASSESSMENT simplified abstract (International Business Machines Corporation)

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MODEL PRODUCTIZATION ASSESSMENT

Organization Name

International Business Machines Corporation

Inventor(s)

Rahul Nair of Dublin (IE)

Andrew T. Penrose of Dublin (IE)

MODEL PRODUCTIZATION ASSESSMENT - A simplified explanation of the abstract

This abstract first appeared for US patent application 17454568 titled 'MODEL PRODUCTIZATION ASSESSMENT

Simplified Explanation

The abstract describes a technology for improving the integration of machine learning models into applications using processors in a computing system. Here are the key points:

  • The technology inspects artifacts of machine learning models.
  • It determines the compatibility between the machine learning models and an application by inspecting the artifacts.
  • Based on the compatibility, the technology recommends adjustments to the artifacts.
  • These adjustments aim to facilitate the integration of the machine learning models into the application.

Potential Applications

This technology has various potential applications, including:

  • Integrating machine learning models into software applications.
  • Improving the compatibility between different machine learning models and applications.
  • Enhancing the performance and efficiency of machine learning models within applications.

Problems Solved

This technology addresses the following problems:

  • Difficulty in integrating machine learning models into applications.
  • Lack of compatibility between machine learning models and applications.
  • Inefficiencies or performance issues when using machine learning models within applications.

Benefits

The technology offers several benefits, such as:

  • Streamlining the integration process of machine learning models into applications.
  • Ensuring compatibility between machine learning models and applications.
  • Optimizing the performance and efficiency of machine learning models within applications.


Original Abstract Submitted

Various embodiments are provided for improving machine learning model integration using one or more processors in a computing system. One or more artifacts of one or more machine learning models may be inspected. A degree of compatibility may be determined between the one or more machine learning models and an application based on inspecting the one or more artifacts. One or more adjustments may be recommended to the one or more artifacts based on the degree of compatibility for integrating the one or more machine learning models into the application.

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