1) Executive Summary: Why Quantization Matters for Edge Agents The promise of edge AI is compelling: intelligent agents that run directly on devices—smartphones, IoT sensors, industrial controllers, and embedded systems—without relying on cloud connectivity. But there’s a fundamental tension: the most capable AI models are large, requiring significant memory and compute, while edge devices have…
Introduction Behind every AI model—whether it is a chatbot answering questions, a vision system detecting defects, or a language model generating text—there is infrastructure. Massive computing power. Specialized hardware. Cloud platforms that scale to millions of requests. Without the right infrastructure, even the most sophisticated AI model is useless. AI infrastructure has evolved rapidly. What…
1) Executive Summary: Why Fine-tune Llama 3 for Agentic Tasks? Llama 3 represents a watershed moment in open-source AI. With performance rivaling GPT-4, a 128K-token vocabulary, and permissive licensing, it has become the foundation of choice for enterprises building custom AI agents. However, the base Llama 3 Instruct model, while powerful, lacks native capabilities essential…