The History of Machine Learning and Its Convergent Trajectory Towards AI

First came the goal of artificial intelligence, which eventually led to the development of machine learning (ML), as a means of achieving that goal. The emphasis on ‘learning’ in ML allows computers to make better decisions, based on previous experiences. It uses neural network models and algorithms to support the decision‐making process. In the 1960s, researchers focused on developing ML algorithms to solve mathematical problems. In the late 1960s, machine ‘vision’ learning became a popular line of research. ML was used in computer vision, with the goal of object and facial recognition. The nearest neighbour algorithm came about in 1967, initiating the use of basic pattern recognition. In 1968–1969, the nearest neighbour algorithm evolved into the K nearest neighbour algorithm. Deep learning, as a branch of ML, employs algorithms to process data and imitate the thinking process, or to develop abstractions. ‘Boosting’, as an evolutionary step in the process of machine thinking, is significant.