84:13
Andrew Ng + Google showed the foundation behind modern "RAG",...
Morlex@0xMorlex
8 views
Aug 16, 2026
~1 min read
Andrew Ng + Google showed the foundation behind modern "RAG", "Graph RAG" and semantic retrieval:
• 12:00 - turning text into embeddings that capture meaning
• 24:00 - visualizing semantic relationships between vectors
• 35:00 - using embeddings for classification, clustering and outlier detection
• 50:00 - controlling LLM generation with temperature, top-k and top-p
• 1:04:00 - semantic search with ScaNN
• 1:15:00 - combining retrieval + an LLM into a RAG-style Q&A system
- 84-minute deep dive, and one of the clearest explanations of what happens underneath retrieval systems
The progression is simple: Text → Embeddings → Similarity → Semantic Search → Retrieval → LLM Answer
Most people jump straight into RAG frameworks without understanding this layer
Andrew Ng starts one level lower and shows why retrieval works in the first place
Watch it today, then read the full "RAG → Context Graphs" roadmap below
• 12:00 - turning text into embeddings that capture meaning
• 24:00 - visualizing semantic relationships between vectors
• 35:00 - using embeddings for classification, clustering and outlier detection
• 50:00 - controlling LLM generation with temperature, top-k and top-p
• 1:04:00 - semantic search with ScaNN
• 1:15:00 - combining retrieval + an LLM into a RAG-style Q&A system
- 84-minute deep dive, and one of the clearest explanations of what happens underneath retrieval systems
The progression is simple: Text → Embeddings → Similarity → Semantic Search → Retrieval → LLM Answer
Most people jump straight into RAG frameworks without understanding this layer
Andrew Ng starts one level lower and shows why retrieval works in the first place
Watch it today, then read the full "RAG → Context Graphs" roadmap below
