ForceInjection/AI-fundamentals resource

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2376 stars · 364 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A comprehensive Chinese-language learning resource collection covering the full AI infrastructure stack, from GPU/TPU hardware architecture, CUDA programming, and interconnects (PCIe, NVLink, GPUDirect) to LLM training, inference optimization, RAG, and AI Agent systems. It includes 15 content modules with 800+ articles and courses, plus hands-on guides for Kubernetes-based AI platforms, cluster operations, and tools like vLLM, Ollama, and DeepSeek.

Use cases

• learn GPU architecture and CUDA programming from scratch
• understand how NVLink, PCIe, and GPUDirect interconnects work
• set up and operate a large-scale AI training cluster with InfiniBand and NCCL
• build a Kubernetes-based AI platform with GPU virtualization and scheduling
• learn LLM fine-tuning techniques like SFT, LoRA, and QLoRA
• design RAG systems and GraphRAG pipelines
• study AI agent design patterns, multi-agent collaboration, and MCP protocol
• optimize LLM inference with vLLM and KV cache compression

When to choose

• you want a systematic, end-to-end learning path for AI infrastructure from hardware to applications
• you are an AI engineer or architect needing deep dives into GPU internals, cluster ops, and cloud-native AI tooling
• you prefer practical, engineer-written guides with real deployment and tuning experience
• you need coverage of both training (CUDA, distributed training) and inference (vLLM, KV cache) topics in one place

When to avoid

• you need runnable software or code libraries rather than documentation and tutorials
• you require English-language content only, as the material is primarily in Chinese
• you are looking for a beginner-only intro to AI/ML without infrastructure depth
• you need a structured course with certification rather than a self-guided article collection

Facets

learning-resource · maturity active

gpu-computing llm-inference llm-training rag agent-framework mcp machine-learning monitoring container-orchestration documentation artificial-intelligence gpu-computing large-language-models developer-tools tutorials infrastructure-as-code microservices python cpp ai-infrastructure cuda-programming gpu-architecture nvlink infiniband nccl vllm kv-cache lora-fine-tuning graphrag multi-agent-systems hami gpu-virtualization deepseek ollama chinese-language-content ai-agents retrieval-augmented-generation containers gpu linux kubernetes docker web-server

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