Opening — Why this matters now There is a quiet but decisive shift happening in the world of AI agents. For the past two years, we’ve been told that agents “learn” by remembering — storing prompts, reflections, and reasoning traces. A polite fiction. Memory, in this context, is little more than annotated hindsight. But real systems don’t scale on hindsight. They scale on reusable execution. ...
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: ...
When was the last time a machine truly surprised you—not with a quirky ChatGPT poem or a clever image generation, but with scientific reasoning that evolved on its own? Meet STELLA, an AI agent for biomedical research that doesn’t just solve problems—it gets better at solving them while solving them. The Static Curse of Smart Agents Modern AI agents have shown promise in navigating the labyrinth of biomedical research, where each inquiry might require cross-referencing papers, running custom bioinformatics analyses, or interrogating molecular databases. But the vast majority of these agents suffer from a fatal limitation: they rely on static, pre-installed toolkits and hard-coded logic trees. Like a PhD student who memorized a textbook but never updated it, they can’t adapt to new tasks or new knowledge without human intervention. ...