Machine learning US 20,250,371,449 A1 Under examination

Dynamic agents with real-time alignment

This invention describes an AI agent that uses a layered memory system to understand a user's goal. It retrieves relevant information from memory, presents it to the user, and collects their feedback. This feedback, along with the goal and initial context, is then used to create a detailed instruction for a machine learning model. The model generates a step-by-step plan for the agent to follow, and can even learn user preferences like communication style or skill level from the ongoing interactions.

Why it matters: While large language models could generate plans in 2024, the practical integration of robust multi-layer memory and real-time preference learning for dynamic agent alignment has become significantly more efficient and performant.

Status: Under examinationA pending application. It has not been granted, and it has not been abandoned.
How hard to build: SpecializedSoftware logic, machine learning models, multi-layer memory system

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