Tagged “efficiency”

3 posts.

All Model Architecture13 Training & Alignment8 Inference & Serving11 Agents & Orchestration10 Reasoning & Evaluation7 Safety, Security & Governance3 Platforms & Practice11

Model Architecture 20 min

Do Transformers Need Three Projections? Rethinking Q, K, and V

Every attention head learns three weight matrices for query, key, and value. A 2026 study trained models up to 1.2B parameters to ask which of them are actually load-bearing, and found that keys and values can share one projectio…

transformers attention kv-cache inference ∑ ◫

Inference & Serving 21 min

Four Bits Per Weight: How Low-Precision Quantization Stopped Hurting LLMs

A 70B model in FP16 needs 140 GB of memory it spends most of its time waiting to read. Dropping each weight to four bits cuts that to 35 GB, and for years that cut also broke the model. Here is what changed.

quantization inference gptq awq ∑ ◫

Model Architecture 4 min

The Length of a Thought: Why Context Windows Became the New Battleground

A 512-token model could read a paragraph. A million-token model can read a novel. The journey between those two numbers is a story about quadratic cost, clever approximations, and what it means for a machine to "remember."

transformers attention context scaling