A crawlable AI concept map for foundations, model architectures, agents, multimodal AI, prompt engineering, applications, and open-source ecology.
Linear algebra, probability, calculus, tensors, gradients, neural networks, and machine learning basics.
Transformer, attention, embeddings, tokenization, MoE, context windows, RAG, and inference.
Tool use, function calling, MCP, planning, memory, multi-agent systems, browser use, and coding agents.
Text-to-image, video generation, speech, OCR, diffusion models, vision-language models, and world models.
Prompt patterns, structured output, chain-of-thought alternatives, evaluation, and safety.