A knowledge building platform with semantic consensus generation
Maestro-4 is an advanced knowledge building platform that combines FIL-Diffusion models with semantic physics to generate consensus from multiple knowledge sources. The platform enables users to visualize and explore knowledge graphs through an intuitive Session Graph interface.
The system uses diffusion-based models to synthesize information from diverse inputs, creating a unified understanding through semantic consensus. This approach allows for more robust and reliable knowledge representation compared to traditional methods.
Advanced diffusion-based architecture for semantic consensus generation from multiple knowledge sources.
Interactive visualization of knowledge relationships, allowing users to explore connections and patterns.
Modern monorepo structure with Next.js frontend, FastAPI backend, and shared type definitions.
Available on GitHub for collaboration and community contributions.