At 28, Zeng Guoyang, co-founder and CTO of Mianbi Intelligence, leads efforts to compress large models for edge devices like smartphones and cars. At age 22, he led training of China's first large language model, CPM-1. His team focuses on "knowledge density," using "model wind tunnel" technology to validate performance in small-scale experiments, with knowledge density doubling every 3.5 months and parameter scale for equivalent intelligence decreasing exponentially. Mianbi's MiniCPM, with only 2B parameters, outperformed its 8B competitors at the same time. Zeng envisions edge AI evolving from "cloud computing power" to "deep understanding," requiring solutions for power consumption, latency, and hardware compatibility, plus personalized memory via a "默契 system" (intuitive system) for proactive, "invisible" intelligence. The team developed the ForgeTrain training framework and a five-tier hierarchical standard from data governance to hardware deployment, emphasizing that data quality determines the model's upper limit.