Interactive semantic document mapping and navigation with meaning-based features

This invention helps users understand large collections of text documents by mapping them based on meaning. It uses an AI model to score how strongly each sentence in a document relates to specific ideas the user defines. These scores are then combined for each document and displayed on a two-dimensional map, which can be adjusted based on user feedback to improve accuracy, including a process to debug the AI model using a few examples.

Why it matters: The rapid evolution of large language models (LLMs) since 2024 has made advanced NLI capabilities more accessible and efficient, potentially simplifying the development and fine-tuning of the semantic classification and debugging processes described.

Status: Under examinationA pending application. It has not been granted, and it has not been abandoned.
How hard to build: SpecializedHeavy software system, machine learning expertise.

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