The Evolution of Generative AI: From Rule-Based to Transformers
The Evolution of Generative AI: From Rule-Based to Transformers Generative AI is reshaping how we create text, images, music, code, and more—but this didn't happen overnight. The journey of generative AI has seen a dramatic shift from rigid rule-based systems to today’s flexible and powerful transformer models like GPT-4 and beyond. This post explores the key stages in the evolution of generative AI and highlights how each step paved the way for the next. 1. Rule-Based Systems: The Early Days In the earliest days of AI, systems relied on handwritten rules and logic trees. These rule-based programs could perform specific tasks like generating templated text responses or basic dialogue systems. 🔹 Characteristics: Deterministic outputs No learning involved Limited flexibility and scalability 🧠 Example: Early chatbot ELIZA (1960s) mimicked a psychotherapist using pattern-matching rules but lacked true understanding. 2. Statistical Models: Learning from Data As computational power gre...