@claraiglesias957p6v8i The Evolving Landscape of Artificial Intelligence: From Narrow Expertise to General Intelligence

The trajectory of artificial intelligence has long been defined by a paradox: systems that surpass human capability in narrowly defined tasks while remaining brittle and inflexible outside their training domains. Over the past decade, advances in deep learning, reinforcement learning, and large-scale transformer architectures have delivered machines that can generate fluent text, recognize objects with superhuman accuracy, and defeat world champions in complex games. Yet the gap between these isolated competencies and the flexible, context-sensitive intelligence that characterizes human cognition remains vast. Understanding this gap—and the research directions attempting to bridge it—requires examining not only technical breakthroughs but also the conceptual foundations that shape the field.