An AI concept map readable by people and agents: foundations, model architecture, agents, multimodal AI, prompts, applications, and open-source projects.
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.