奇点逃逸
基础模型与学习范式
奇点逃逸的 Learnable System 把任务流、系统评测和递归优化结合，使智能体能从执行反馈中持续改进。其重点是将“自我进化”做成可重复的学习机制。
Antropy combines task flows, systematic evaluation and recursive optimization so agents can improve from their own execution feedback. The focus is a repeatable learning mechanism rather than a one-time capability gain.
