Information Processing for Generative Thinking Framework Content

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Solution Overview

Problem

Individuals unfamiliar with frameworks for supporting efficient thinking find it difficult to apply these frameworks effectively.

Innovation Solution

An information processing apparatus and method utilizing a generative model trained through machine learning to generate content for input into various thinking frameworks, such as decision making and idea generation, based on target-related information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If frameworks are used for supporting efficient thinking, then thinking efficiency is improved, but ease of operation deteriorates for users unfamiliar with frameworks

Engineering Contradiction:

Improvethinking efficiencyVSAvoidease of applying frameworks

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The patent introduces an automated content generation system that acts as an intermediary between the user and the framework. The system automatically generates the content needed for framework application based on user input, eliminating the need for users to manually create framework content and thus resolving the contradiction between thinking efficiency and ease of operation

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system enables self-service by automatically generating framework content without requiring user expertise in framework application. The automated generation process serves itself by understanding the framework requirements and producing appropriate content, allowing users to benefit from framework efficiency without dealing with the complexity of content creation

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250284700A1Information processing apparatus, thinking support method, and storage medium

Publication Date: 2025.09.11 NEC CORP

AI summary

To easily carry out efficient thinking using frameworks, an information processing apparatus includes: a reception section that receives an input of target-related information related to a target of thinking; and a generation control section that causes a generative model trained by performing machine learning to generate, using the target-related information, content to be inputted into a framework capable of being used in thinking about the target.