Introduction Large language models like ChatGPT are impressive. They can write essays, answer questions, and generate code. But they have a fundamental limitation: they only know what they were trained on. Ask a question about your company’s internal documents, your customer data, or the latest news from yesterday, and they will either admit ignorance or—worse—hallucinate
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