In Alan Turing’s seminal paper from 1950, "Computing Machinery and Intelligence," he considered whether machines could think. In this paper, Turing first coined the term artificial intelligence and presented it as a theoretical and philosophical concept.
Between 1957 and 1974, developments in computing allowed computers to store more data and process faster. During this period, scientists further developed machine learning (ML) algorithms. The progress in the field led agencies like the Defense Advanced Research Projects Agency (DARPA) to create a fund for AI research. At first, the main goal of this research was to discover whether computers could transcribe and translate spoken language.
Through the 1980s, the boosted funding available and the expanding algorithmic toolkit scientists used in AI streamlined development. David Rumelhart and John Hopfield published papers on deep learning techniques, which showed that computers could learn from experience.
From 1990 to the early 2000s, scientists achieved many core goals of AI, like beating the reigning world chess champion. With more computing data and processing power in the modern age than in previous decades, AI research is now more common and accessible. It's rapidly evolving into artificial general intelligence so software can perform complex tasks. Software can create, make decisions, and learn on their own, tasks previously limited to humans.