File-based persistent memory for LLM assistants (metamemoryworks.com)

MetaMemoryWorks has introduced an innovative architecture for persistent AI memory, designed to enhance user interaction with large language models (LLMs) by making them more effective personal assistants. Unlike existing chat-based AI, which often leads to loss of context, MetaMemoryWorks stores information in files, ensuring that users don’t lose progress on projects or context for conversations. This new architecture facilitates organized and structured AI workflows, making it especially beneficial for both personal and professional use. The system launches with three foundational modules: noteOS, a versatile notebook for various tasks; scanOS, which converts images and documents into structured data; and trainingOS, a personal training coach to help users manage and evaluate their progress. Each module is tailored to different needs, from personal use aimed at enhancing daily life and personal projects to professional settings that require structured workflows, reproducible processes, and seamless integration into existing systems. While personal use is free, professional users will need a license to ensure responsible application of the technology. This development is significant for the AI/ML community as it moves toward creating more reliable, explainable, and user-friendly applications of AI in everyday tasks.