Attention Mechanisms and KV Cache Deep Dive

Attention Mechanisms and KV Cache: From First Principles to Gemma 4's Architecture

Every modern LLM generates tokens by attending to all previous tokens. The way this attention is computed — and the way its intermediate results are stored — is the single most important architectu...

May 28, 2026 AI Infrastructure, Deep Dives

A Quantization Primer: Formats, Architecture Sensitivity, and a Gemma 4 Case Study

A 70B parameter model in FP16 weighs 140GB. That won’t fit on any consumer GPU. Quantization is how you shrink it to 35GB (Q4) or even 18GB (Q2) — trading precision for the ability to actually run ...

May 21, 2026 AI Infrastructure, Deep Dives

Securing Autonomous Agents - Introducing Nvidia NemoClaw

Autonomous AI agents are transforming how developers work, write code, and interact with tools. Frameworks like OpenClaw have made it incredibly easy to deploy always-on assistants. However, this p...

Mar 17, 2026 Gen AI, Agents

Chapter 10 - Agentic Frameworks and Generative UI

This article is part of my book Generative AI Handbook. For any issues around this book or if you’d like the pdf/epub version, contact me on LinkedIn The era of the “Chatbot”—a simple text-in,...

Feb 14, 2026 Gen AI, Architecture

Chapter 9 - Context Engineering and RAG

This article is part of my book Generative AI Handbook. For any issues around this book or if you’d like the pdf/epub version, contact me on LinkedIn A modern LLM doesn’t run on “the prompt.” ...