Build a TCM-Focused Large Language Model

1. 1

   Assemble the proprietary corpus

   The model's value comes from a massive, high-quality corpus of classical texts, national textbooks, and examination databases, so securing rights to and structuring that corpus is the foundational work. Classical Chinese medical language is specialized and hard to process, adding real difficulty. The corpus is both the moat and the largest early effort.

2. 2

   Train and fine-tune the domain model

   Building a capable domain LLM requires substantial compute for training or fine-tuning, plus expert-guided evaluation to ensure the model reflects TCM knowledge accurately rather than hallucinating. Partnering with strong infrastructure (as Tianjin University did with Huawei) is common for a reason. This is a resource-intensive engineering undertaking.

3. 3

   Build for multi-language deployment

   A key design goal is multi-language capability so the model can serve markets beyond Chinese, extending TCM knowledge internationally. Multi-language accuracy in a specialized domain is challenging and must be validated per language. This reach is part of what makes the model commercially valuable.

4. 4

   Target enterprise customers

   The buyers are pharmaceutical companies, retail drug shops, and community medical services that need TCM knowledge at scale, not individual consumers. Understand each segment's use case (product information, decision support, education) and package accordingly. Enterprise deployment is where the revenue is.

5. 5

   Ensure safety and accuracy

   Any model touching medical knowledge must be rigorously evaluated for accuracy and safe behavior, with clear boundaries around what it will and will not assert. Expert oversight and guardrails are non-negotiable in health contexts. Trustworthiness is what makes enterprises adopt it.

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