When did AI become a separate discipline? It is difficult to say for sure, but there’s certainly some overlap. Artificial intelligence (AI) is an important field that helps computer systems make better decisions, such as those resulting in the development of self-driving cars. Information science, meanwhile, is concerned with the application of AI in many aspects of life. Information science has a long way to go before it can compete with AI in many areas.
In 1983, the United States launched the Strategic Defense Initiative (SDIS). This program, also known as “Star Wars,” began with research on a defensive shield, ground-based missile systems, and intelligence gathering. Those investments eventually benefited AI, which was used for autonomous vehicles, battle management systems, pilot assistants, and intelligent filtering of intercepted communication. But even with these early advances, artificial intelligence was not ready to take over the world.
AI was originally conceived as a branch of computer science. In its early stages, it was a new science that sought to study the ‘human mind’ and “automated processes”. The central premise of AI was that computers could mimic human thought processes. But while early researchers believed this goal would be achievable in a few decades, it was never quite achieved. Instead, they credited advances in the digital computer and formal logic with bringing AI closer to reality.
AI has been around for several decades, but only recently began to enter the technology industry. The success of AI research was largely due to the increasing power of computers, the focus on isolated problems, and the highest standards of scientific accountability. But its reputation in the business world was not exactly pristine. AI scientists were split on why human intelligence couldn’t be replicated with computer programs. It also seemed like researchers were overly optimistic about the difficulty of the task and made unrealistic assumptions about how hard it would be to implement.
The first phase of AI research was called “the AI winter.” The government and industry stopped funding undirected AI research in 1974. In the 1980s, the Japanese initiative inspired the government and industry to provide billions of dollars for the field. But by the late 1980s, the funding had dried up and investors started to withdraw from the field. The next phase of AI research came in the form of deep learning techniques and expert systems.
The term “AI winter” was coined at an annual meeting of the American Association for Artificial Intelligence in 1984. Researchers like Roger Schank and Marvin Minsky saw that the boom and bust cycle of the 70s and 80s had repeated itself. The optimistic AI of the 1950s and 1960s had a burgeoning industry, but the pessimistic AI of the 80s had lost momentum, and the field was being criticized as not meeting grand objectives.
The history of AI is long and intertwined with the history of computers. In this article, we will outline the main periods in the history of AI and how they evolved. The history of AI and the development of computers goes back to Turing, who invented the first electronic computer. Artificial intelligence has evolved from that time, and has continued to evolve through every decade. The future of AI is a real possibility now.
Traditionally, AI has been defined as the ability of machines to perform tasks. Minsky and McCarthy’s 1950s definition is very broad and aims for a machine that has the ability to perform tasks as if it were a human. More recent definitions of artificial intelligence have become more precise. Google AI researcher Francois Chollet developed the machine learning software library Keras. He has suggested that intelligence is tied to adaptability, generalisation, and the ability to apply knowledge to new situations.
In 1956, a conference was held at Dartmouth College, which was sponsored by the Defense Advanced Research Projects Agency. During this conference, 10 luminaries in the field convened, including the economist Herbert Simon and physicist Samuel. They discussed the definition of AI and outlined goals for the field. The goal of the conference was to define what AI was and how it would benefit society.