Privacy-Preserving AI

In a field where many agents act like well-trained dogs, obediently waiting for commands, Galaxy offers something more radical: a system that watches, thinks, adapts, and evolves—without needing to be told. It’s not just an intelligent personal assistant (IPA); it’s an architecture that redefines what intelligence means for LLM-based agents. Let’s dive into why Galaxy is a leap beyond chatty interfaces and into cognition-driven autonomy. 🌳 Beyond Pipelines: The Cognition Forest At the heart of Galaxy lies the Cognition Forest, a structured semantic space that fuses cognitive modeling and system design. Each subtree represents a facet of agent understanding: ...

The CoRAG Deal: RAG Without the Privacy Plot Twist The tension is growing: organizations want to co-train AI systems to improve performance, but data privacy concerns make collaboration difficult. Medical institutions, financial firms, and government agencies all sit on valuable question-answer (QA) data — but they can’t just upload it to a shared cloud to train a better model. This is the real challenge holding back Retrieval-Augmented Generation (RAG) from becoming a truly collaborative AI strategy. Not the rise of large context windows. Not LLMs like Gemini 2.5. But the walls between data owners. ...