About

I have studied and explored Chinese medicine over the long term. My understanding of the field remains limited, but it is the direction to which I continue to devote time, sustain my interest, and hope to stay committed.

I am concerned with more than a particular illness, herb, or school of thought. I want to understand how diagnosis, treatment, and feedback unfold over time: what happens to a patient from first consultation to follow-up; why a clinician revises a judgment or prescription; and whether seemingly conflicting explanatory frameworks can reveal comparable structures in practice. The tools I am making to structure Shang Han Lun and to study cloud-based clinical follow-ups are, first of all, for learning and preserving material, so that these questions may one day be studied more seriously.

While studying Chinese medicine, I keep encountering questions at another level: How should knowledge be structured? How can a vague intuition become a question that can be discussed and tested? Can someone unfamiliar with a field enter it with AI? When AI produces results beyond a person's capacity to review, what mechanisms should judge and govern them?

These questions have led me to AI, Minimax, MRI, formal proof, and engineering reproduction. They are not my professional fields, and cannot demonstrate mastery of those domains. They are more like by-products that grew out of studying Chinese medicine: through unfamiliar problems, I observe how people and AI can research together, and how such research might avoid producing answers that are internally coherent yet meaningless.

I am a heavy user of AI, but not a programmer. I know only a very limited amount of programming syntax and basic computing knowledge; I have always been poor at mathematics, and I know nothing at all about MRI. AI does most of the code, mathematical derivation, and formal work in these projects. My role is chiefly to formulate questions, hold a direction, choose constraints, notice drift, and move the results into contact with reality.

The work recorded here is therefore not evidence that I have mastered programming, mathematics, or MRI. It is the product of work shared among me, AI, tools, and feedback from reality. The advertising system was first of all a solution to a real production problem for a friend; Minimax and MRI served more as experiments in meta-research. They need not be presented as achievements across several specialist fields.

For me, research usually begins with an interest I cannot set aside. A question may remain in my mind for a long time without clear language, until one day it creates a strong urge to build. Building is also part of thinking: with AI, I turn intuitions that have not yet taken shape into writing, software, experiments, and objects open to refutation.

The beginning of research is wanting to know why something is interesting; its end is finally understanding why it is interesting. Whether it expands the boundaries of human knowledge is a possible result of research, not a grand objective I set in advance.

Ultimately, I hope to make complex knowledge of Chinese medicine something ordinary people can naturally access in daily life, so that some problems can be seen before a person becomes ill. Other explorations may continue to appear, but Chinese medicine is the place from which they repeatedly depart and to which they return.

Those are traces of thought in motion.

In a Station of the Metro

The apparition of these faces in the crowd:
Petals on a wet, black bough.

— Ezra Pound