Definition and how it works
Artificial intelligence (AI) is the field of computer science concerned with developing methods and software that enable machines to perform tasks associated with intelligence. These tasks can include perceiving aspects of an environment, learning from available information, and choosing actions aimed at defined goals. Rather than merely carrying out simple instructions, AI systems can analyze large datasets and produce predictions or recommendations.
The expression covers many kinds of systems, not a single machine or technology. Broadly, the idea is for computers to demonstrate capabilities such as reasoning and learning in ways that resemble some aspects of human thought. That does not necessarily mean they have the same experience or understanding as a person: the definition describes capabilities and tasks that systems can perform.
Origins and development
The history of AI as a research field dates to the 1950s, although some of its concepts have older antecedents. In 1950, English mathematician Alan Turing considered whether a machine could think and imitate intelligent behavior, outlining a research direction for investigating that possibility. Artificial intelligence was formally established as an academic discipline in 1956.
Since then, the field has gone through cycles of optimism and slowdown. The so-called “AI winters” were periods of stagnation and reduced funding. Interest and resources later increased substantially from 2012, when deep learning surpassed earlier technological models. Progress accelerated after 2017; in the early 2020s, investments worth billions of dollars contributed to rapid growth known as the AI boom.
Applications and scope
Capabilities associated with AI include analyzing large amounts of data, generating predictions, and making recommendations. Expert systems and autonomous machines are examples of research goals: developing programs able to carry out complex tasks with some degree of independence. The purpose of a particular system depends on the goals for which it was designed and the information it can use.
AI is therefore both a research field and a broad collection of computational methods and systems. The definition does not imply that every program is intelligent in the same way, or that every application has the same capabilities. The central idea is to develop systems that use data and learning to perform tasks or select actions directed toward goals.