Microsoft Technology Licensing, LLC (20240296275). GUARDRAILS FOR EFFICIENT PROCESSING AND ERROR PREVENTION IN GENERATING SUGGESTED MESSAGES simplified abstract

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GUARDRAILS FOR EFFICIENT PROCESSING AND ERROR PREVENTION IN GENERATING SUGGESTED MESSAGES

Organization Name

Microsoft Technology Licensing, LLC

Inventor(s)

Caleb Whitmore of San Francisco CA (US)

Susan Marie Grimshaw of Krikland WA (US)

Poonam Ganesh Hattangady of Seattle WA (US)

GUARDRAILS FOR EFFICIENT PROCESSING AND ERROR PREVENTION IN GENERATING SUGGESTED MESSAGES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240296275 titled 'GUARDRAILS FOR EFFICIENT PROCESSING AND ERROR PREVENTION IN GENERATING SUGGESTED MESSAGES

Simplified Explanation

The patent application describes systems and methods for using a generative artificial intelligence model to generate a suggested draft reply to a selected message, with guardrails in place to prevent accidental sending of the AI-generated draft.

  • Guardrails are implemented to limit unnecessary AI model processing and accidental sending of drafts.
  • Draft reply-generation is restricted to a subset of messages and triggered only after user interaction criteria are met.
  • A confirmation message is presented when attempting to send a draft without changes or quickly after generation to prevent accidental sending.
  • The guardrails also restrict the number of times the AI model is invoked to generate suggested replies and prevent accidental sending of drafts.

Key Features and Innovation

  • Use of a generative artificial intelligence model to generate draft replies to messages.
  • Implementation of guardrails to prevent unnecessary AI model processing and accidental sending of drafts.
  • Limiting draft reply-generation to specific message subsets and triggering based on user interaction criteria.
  • Presentation of a confirmation message to prevent accidental sending of drafts without changes.
  • Restriction on the number of times the AI model is invoked to generate suggested replies.

Potential Applications

This technology can be applied in various messaging platforms to assist users in drafting replies to messages more efficiently and accurately.

Problems Solved

  • Prevents accidental sending of AI-generated drafts.
  • Improves efficiency in drafting replies to messages.
  • Enhances user experience in messaging applications.

Benefits

  • Saves time for users in composing replies.
  • Reduces the risk of sending unintended messages.
  • Enhances the overall user experience in messaging platforms.

Commercial Applications

  • Title: Enhanced Message Drafting System with AI Technology
  • This technology can be commercialized in messaging applications, customer service platforms, and email clients to improve communication efficiency and accuracy.

Questions about the Technology

How does the system prevent accidental sending of AI-generated drafts?

The system implements guardrails and presents a confirmation message to users before sending a draft reply, reducing the risk of accidental sending.

What criteria trigger the generation of draft replies in the system?

Draft reply-generation is triggered based on user interaction criteria being satisfied, ensuring that the AI model is only invoked when necessary.


Original Abstract Submitted

systems and methods for using a generative artificial intelligence (ai) model to generate a suggested draft reply to a selected message. a message generation system and method are described that use guardrails that prevent unnecessary ai model processing and accidental sending of an ai model-generated draft. in some examples, draft reply-generation is limited to a subset of messages (e.g., focused, non-confidential) and triggering of the draft reply generation is performed only after user interaction criteria are satisfied. in some examples, a confirmation message is presented when the draft reply is attempted to be sent with no changes or quickly after the draft is generated. for instance, the guardrails limit the number of times the ai model is invoked to generate suggested replies and further prevents users from accidentally sending drafts generated from the ai model.

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