Liu Ziming / 刘子鸣
Liu Ziming is the AI researcher interviewed in 149. 亲历中美 New Labs 资本狂潮，和清华刘子鸣聊：AI for AI、机制可解释性和 Max Tegmark. The source title names him 刘子鸣; parts of the episode summary render the name as 刘子明. In the episode he is described as an assistant professor at [[TsinghuaUniversity|Tsinghua University’s]] AI school, a PI at [[ShanghaiQizhiInstitute|Shanghai Qi Zhi Institute]], and a participant in creating [[YuanhuanIntelligence|圆环智能]].
The source frames Liu’s career as a staged reversal. He began in physics at [[PekingUniversity|Peking University]], moved to MIT for AI-and-physics work under Max Tegmark, spent time at [[StanfordUniversity|Stanford]], and then turned from using AI for physics toward using physics-like methods to understand and design AI. That turn becomes Physics Of AI and eventually Liu’s version of AI For AI.
His technical identity in the source is not only [[KolmogorovArnoldNetworks|KAN]]. KAN matters because it shows his neural-symbolic interest and model-architecture taste, but he treats the deeper problem as learning how to generate the next major architecture. That leads to OPHIS Research Workflow, Meta-Model Training Curve Prediction, Training Autopilot, and Vibe Training.
Key Claims
- Liu sees AI as offering faster feedback and more open frontier problems than the physics path he originally imagined.
- His research theme is joining neural and symbolic modes, or more broadly joining AI with physics and natural science.
- He treats research taste and intuition as analyzable processes rather than irreducible genius.
- His AI For AI route is intentionally different from pure paper-agent or coding-agent automation.
- He thinks short-term AI research automation needs structure, mechanism, and collected research-process data before it can become a reliable product.
Connections
- [[YuanhuanIntelligence|圆环智能]] — company/lab vehicle connected to Liu’s AI for AI work.
- Max Tegmark, MIT, [[PekingUniversity|Peking University]], [[StanfordUniversity|Stanford]], [[TsinghuaUniversity|Tsinghua]], and [[ShanghaiQizhiInstitute|Shanghai Qi Zhi Institute]] — education, advising, and institutional context.
- AI For Science, Physics Of AI, Mechanistic Interpretability, and [[KolmogorovArnoldNetworks|KAN]] — research trajectory.
- AI For AI, Auto Research, OPHIS Research Workflow, Meta-Model Training Curve Prediction, Training Autopilot, and Vibe Training — automation and product thesis.
- Research Taste, Transformer Architecture, Hardware Lottery, and World Models — broader technical judgment in the episode.