Understand How AI Thinks
No math PhD needed. Interactive 3D visualizations make complex LLM concepts intuitive.
9 free modules from tokenization to RAG. Click, explore, and learn at your own pace.
Start from Scratch →Your Learning Journey
Follow the recommended order, or jump to any topic
Understand BPE, WordPiece, and SentencePiece — how text becomes tokens for LLMs.
2Visualize how tokens become vectors in high-dimensional space and why similarity matters.
3Explore the complete Transformer architecture in 3D — Encoder, Decoder, Attention, and data flow.
4Multi-Head, Grouped Query, Sliding Window, and Flash Attention — the evolution of attention.
5How KV caching accelerates autoregressive inference and the PagedAttention optimization.
6Pre-training, supervised fine-tuning, and the complete training loop with loss landscapes.
7Low-Rank Adaptation — efficient parameter-efficient fine-tuning for large models.
8Reinforcement Learning from Human Feedback — aligning LLMs with human preferences.
9Retrieval-Augmented Generation — grounding LLM outputs in external knowledge sources.