Reading Guide
Translation status
This English page provides a localized entry and navigation shell. The full article body is currently available in Chinese.
This site is organized by topic rather than by publishing timeline. The goal is to help you build a stable mental model for enterprise AI systems, not just follow a stream of articles.
Main tracks
- Enterprise Agents: roles, memory, semantics, and architecture for business-facing agents.
- Ask-Data Agents / Semantic Layer: trustworthy data access, semantic layers, and ask-data workflows.
- Enterprise AI: AI-native organizations, enterprise operating models, and capability building.
- AI Engineering: inference cost, KV quantization, VRAM, deployment, and compute planning.
- RAG / Embeddings: knowledge augmentation, embedding models, and vector infrastructure.
- AI Foundations: models, algorithms, math foundations, and the Hugging Face and Foundations series.
Recommended starting points
- For enterprise rollout: start with Enterprise AI and Enterprise Agents
- For data intelligence: start with Ask-Data Agents / Semantic Layer
- For cost and deployment: start with AI Engineering
- For fundamentals: start with AI Foundations