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AI Architecture
Grouped Query Attention (GQA): How Modern LLMs Shrink KV Cache
GQA cuts KV cache 4-8x vs. multi-head attention with minimal quality loss. Architecture, memory math, MHA vs MQA vs GQA trade-offs, and which models (LLaMA 3, Mistral, Gemma) use it.
AI Architecture
How Speculative Decoding Works: Draft Models and 3x Speedup
Speculative decoding proposes token batches with a small draft model and verifies them in one large-model pass — 2-3x speedup with zero quality loss. Here's the algorithm, the acceptance math, and when it fails.
AI Architecture
How Vector Databases Actually Work: HNSW, ANN, and Retrieval Architecture
Vector databases are not magic. This deep-dive covers HNSW graph structure, ANN tradeoffs, index construction costs, and the retrieval pipeline behind every RAG system.