A visual AI learning roadmap: 3Blue1Brown, Transformer Explainer, Neuronpedia and more
techNmak · x · 2026-09-04
A complete visual-first roadmap for learning AI from scratch:
- Math: 3Blue1Brown → Seeing Theory
- ML: TensorFlow Playground → Distill
- Transformers: Jay Alammar → Transformer Explainer → Bycroft
- Modern LLMs: RoPE → GQA/MLA → MoE
- Inference: Modular; Embeddings: Embedding Atlas; Interpretability: Neuronpedia
Key advice: don't spend weeks watching 15 explanations of basic attention — once the canonical Transformer clicks, move on to RoPE, GQA/MLA, MoE, KV caching, FlashAttention, batching, quantization, speculative decoding and interpretability, where modern LLM engineering gets interesting.
Related event: Stop learning AI from static diagrams: a curated visual learning roadmap(13 posts)→
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