BLAZE Paradigm Proposes Socialized AI for Scientific Discovery.

Scientific discovery has historically evolved through various stages, from empirical observation to theoretical frameworks, and more recently, computational and data-intensive methods. The current challenge is not merely generating more information, but effectively organizing the vast and growing body of knowledge, reasoning, and evidence into a cohesive discovery process. This research proposes a new framework called BLAZE, which stands for Bridging Literature, Agents, and Zero-gap Experimentation. BLAZE redefines AI's role in science, moving beyond individual task assistance to establishing an organizational infrastructure for discovery. It connects diverse elements like existing knowledge, collaborative AI reasoning, experimental validation, and human expertise into a continuous research cycle. The core idea is that true scientific intelligence emerges from ongoing interactions among these components, leading to more traceable, reproducible, and cumulative scientific progress while preserving human creativity and responsibility.