Aether AI has unveiled CRIS-0, a causality-driven robotic intelligence system. Comprising two core components—a causality-driven robotic agent and a causal world model—CRIS-0 employs mechanisms such as hierarchical design and structured state transition loops. These enable it to swiftly identify disturbances and adjust action strategies in dynamic physical environments. It excels in interference resistance, long-range task execution, and response to ambiguous instructions, addressing the limitations of traditional statistical prediction methods in adapting to the real physical world. CRIS-0 builds upon the team's previous explorations, RSIAgent and CausalWM, and has now validated two key capabilities: task-level planning, verification, and recovery, as well as physical change deduction and control. Looking ahead, the team will continue to develop the underlying causal model architecture, aiming to create an intelligent brain capable of adapting to real-world environments. Related approaches can also extend to fields such as biopharmaceuticals and new material research.