The term AI has a long history, and machine learning has been around for almost two decades. In fact, the term has become a synonym for AI, and the word itself is a noun that implies intelligence. It is also used to refer to artificial intelligence, but in more general terms, machine learning can be applied to other types of technology. A good example of this is when a computer program is taught to play the chess game “Deep Blue,” which beat the world chess champion in 1997. This program learned the game by using tree search algorithms and evaluated millions of moves at every turn.
Machine learning isn’t AI, but it does have some advantages. For example, it can perform tasks that would otherwise require the expertise of humans, including detecting tuberculosis. As a result, it is often used to replace humans for many tasks, including those involving complex math and decision-making. While these technologies are a great boon for the economy, they can also pose a risk to companies. However, as machine learning becomes more sophisticated, there are tools and protocols available to reduce the risk and maximize the potential of AI.
When was AI invented? As an industry, AI has experienced many ups and downs. In the early years of AI, the industry was awash in hype, and many scientists believed that human-level AI was within reach. But this prediction proved to be unfounded, and the industry went through a “AI winter” when funding and interest in the field decreased. Today, the term “AI” has been used to describe a variety of applications that make our lives more comfortable.
