Foundations of Large Language Models

Large Language Models (LLMs) are indicated by this chapter as a major change maker for business analytics. Focusing on practical implementation strategies, it goes over and above the basic foundations like Transformers and tokenization. By analyzing operational metrics via real-world case studies such as (Klarna, BloombergGPT) the chapter spotlights critical cost-latency trade-offs. The “LLMOps” lifecycle is then established, and a strategic framework for deployment (API vs. Self-Hosted) and governance including hallucination risks and EU AI Act compliance is presented. The text then ends with the future trends in multimodal AI and agentic systems, granting the practitioners the needed actionable insights for a sustainable competitive advantage.