Human-Level AI, often synonymous with Artificial General Intelligence (AGI), represents a future milestone in AI development where machines will possess the ability to understand, learn, and apply knowledge across a wide range of tasks, matching or surpassing human intelligence. This concept encompasses not only the replication of human cognitive abilities but also the capacity for autonomous reasoning, problem-solving, and creativity across diverse domains without specific task programming. Achieving Human-Level AI would mean the creation of systems capable of generalizing learning and adapting to new situations in ways currently limited to humans, marking a significant leap beyond today's specialized AI applications.
Historical Overview: The idea of machines reaching human-level intelligence has been a part of AI discourse since the field's inception in the 1950s, but the term "Artificial General Intelligence" and the modern conception of Human-Level AI began to gain prominence in the early 21st century as advances in machine learning and computational power made the goal seem more attainable.
Key Contributors: While many researchers have contributed to the discussion and development towards Human-Level AI, notable figures include Alan Turing, who laid the foundational ideas of computing and AI, and more contemporary researchers like Ben Goertzel and Nick Bostrom, who have extensively explored the theoretical frameworks and implications of AGI.