Evolution of LLMs - Rule Based, Statistical Model, Transformer Model, Modern LLMs - Generative AI

Explore the evolutionary journey of Large Language Models (LLMs) in this 10-minute tutorial that traces the development from early rule-based systems to modern generative AI. Learn how language models progressed through distinct phases, starting with rule-based approaches that relied on predefined linguistic rules and patterns. Understand the transition to statistical models that introduced probabilistic methods for language processing and prediction. Discover the revolutionary impact of transformer architecture that fundamentally changed how machines process and understand language through attention mechanisms. Examine how these foundational technologies evolved into today's sophisticated LLMs that power modern generative AI applications. Gain insights into the key technological breakthroughs, architectural improvements, and methodological advances that shaped each generation of language models, providing essential context for understanding current AI capabilities and future developments in natural language processing.