SELECTIVE LEARNING OF INFORMATION FOR THE GENERATION OF PERSONALIZED RESPONSES BY A GENERATIVE RESPONSE ENGINE

Smart overview of the Invention

The patent application discusses a generative response engine designed to learn and utilize information relevant to a user account. This system aims to enhance the personalization of responses by automatically gathering and applying user-specific data without needing explicit instructions from the user to remember such information.

Learning Mechanism

A key feature of this technology is its ability to absorb facts, preferences, and contexts through conversational prompts. Users interact with the chatbot, and during these interactions, the engine captures relevant data, allowing it to tailor future responses more accurately. This process eliminates the need for users to manually instruct the system on what information to retain.

Personalization

The generative response engine leverages the learned information to generate responses that are uniquely personalized. By accessing the stored data, the system can address user inquiries with greater relevance and depth, enhancing the overall interaction experience.

Forget Functionality

An additional aspect of this technology is its flexibility concerning data retention. Users have the ability to instruct the generative response engine to forget certain learned facts. This feature ensures users maintain control over their personal information and can manage what data is stored or discarded.

User-Centric Design

Overall, the system prioritizes user convenience by streamlining the process of personalizing interactions. It autonomously learns from user inputs while offering options for data management, making it a versatile tool for enhancing user engagement through tailored communication.