Artificial Intelligence can occasionally seem like a relatively new technological advancement. After all, its usage has only gained traction in recent years, right? In actuality, AI’s foundation was laid in the early 1900s. Without the efforts of early professionals in a wide range of subjects, the greatest advancements would not have been conceivable, even though they weren’t made until the 1950s.
The development of Artificial Intelligence has changed our perception of machine intelligence and its possibilities, from its theoretical underpinnings to the complex systems of today. From the foundation established in the early 1900s to the significant advancements achieved in recent years, we discuss every significant development in artificial intelligence in this article.
Can you Explain Artificial Intelligence?
In computer science, artificial intelligence is the field that focuses on developing systems that can mimic human intelligence and problem-solving skills. To simplify and get better in the future, they do this by absorbing a lot of data, digesting it, and drawing lessons from the past. Because of its capacity for adaptation and improvement, AI is very different from conventional computer programs.
Conventional software needs pre-established rules and human updates to work, while AI can independently improve its procedures by continuously learning from fresh data. Because AI can make precise forecasts, identify irregularities, and streamline processes, it is advantageous for sectors like marketing, healthcare, and finance.
Artificial Intelligence History: A Comprehensive Chronology of This Magnificent Technology
What was our first technology, do you know? The start of the Stone Age was brought forth by stone implements. Electricity, the foundation of all technology, was later acquired. We entered the era of computers as technology developed over time.
Humankind benefited greatly from these devices, which revolutionized the way we work and live. The next revolutionary development after computers was artificial intelligence (AI), a technology that is still reshaping and redefining our contemporary society. However, when was artificial intelligence created? In the following section, we will examine its beginnings.
AI foundations:
1900–1950 There was a lot of media produced in the early 1900s that focused on the concept of artificial humans. So much so that researchers from many walks of life began to wonder if it would be possible to build an artificial brain. Inventors started creating early mechanical machines that resembled what we now refer to as robots at this time. Despite their relative simplicity—they were frequently steam-powered—some of these machines were able to replicate fundamental human behaviors, such as walking and facial expressions.
Important Turning Points Include:
1921: In his science fiction play Rossum’s Universal Robots, Czech playwright Karel Čapek coined the term “robot” and presented the concept of “artificial people,” which he called robots. This was the word’s first recorded usage.
1929: saw the creation of Gakutensoku, the first Japanese robot, by professor Makoto Nishimura. An important step toward creating machines that resemble humans was taken when this robot was able to produce facial expressions.
In 1949: the computer scientist Edmund Callis Berkley released “Giant Brains, or Machines That Think.” This book raised the prospect of machines having the capacity for autonomous thought by drawing comparisons between contemporary computers and the human brain.
Birth of AI: 1950-1956
Between 1950 and 1956, artificial intelligence (AI) was created. It began in 1950 with Alan Turing’s publication of “Computer Machinery and Intelligence” and his introduction of the idea of machine intelligence in The Imitation Game. Turing made a groundbreaking contribution by moving the conversation about AI from theoretical theory to actual practice. The phrase “artificial intelligence” was created and became widely accepted.
Significant dates:
1950: In his 1950 work “Computer Machinery and Intelligence,” Alan Turing suggested the Imitation Game as a test of computer intelligence. He was the first to take artificial intelligence seriously and to seek to make it a reality.
1952: The first program to learn checkers on its own was created by computer scientist Arthur Samuel.
1956: At Dartmouth, John McCarthy arranged an artificial intelligence workshop. The term “artificial intelligence (AI)” was used for the first time, and this was acknowledged as the formal beginning of the discipline.
Maturation of AI: 1957-1979
Between the creation of the term “artificial intelligence” and the 1980s, the field of AI study experienced both tremendous expansion and hardship. There was a period of creation from the late 1950s to the 1960s. From programming languages that are still in use today to novels and movies that delve into the concept of robots, artificial intelligence swiftly gained popularity.
AI was then taught to play chess and given its first programming language. In the 1970s, artificial intelligence was gradually maturing. Nevertheless, the chronology that follows will go into greater detail about AI’s development. Now let’s get started.
Among the Noteworthy dates are…
1958: The first programming language for AI research, LISP (an acronym for List Processing), was developed by John McCarthy and is still widely used today.
1959: Arthur Samuel coined the phrase “machine learning” in this year. In his lecture about teaching machines to play chess more effectively than humans, he used this phrase.
1961: saw the introduction of Unimate, the first industrial robot, to an assembly line at General Motors in New Jersey. Its duties included welding parts on automobiles and moving die casings, tasks that were considered too hazardous for humans to perform.
1965: Artificial intelligence truly developed the ability to think and act like a human in 1965! The first “expert system,” which gave AI the capacity for thought and decision-making, was developed by Edward Feigenbaum and Joshua Lederberg.
1966: ELIZA, a mock psychotherapist that employed natural language processing (NLP) to communicate with people, was the first “chatterbot” (later abbreviated as “chatbot”) developed by Joseph Weizenbaum in 1966. 1968 saw the publication of “Group Method of Data Handling” in the journal “Avtomatika,” by Soviet mathematician Alexey Ivakhnenko. This paper introduced a novel technique for artificial intelligence that would eventually be known as “Deep Learning.”
1968: Are you familiar with the term “Deep Learning”? In 1968, Alexey Ivakhnenko, a Soviet mathematician, introduced the concept in his paper “Group Method of Data Handling,” which was published in the journal “Avtomatika.” The novel AI method that Alexey detailed in his paper is today referred to as “Deep Learning.”
1973: The British government significantly decreased its support and financing for AI research when an applied mathematician named James Lighthill presented a report to the British Science Council highlighting the fact that scientific advancements were not as remarkable as had been promised.
1979: The first autonomous vehicle, the Stanford Cart, was built by James L. Adams in 1961. This cart was able to navigate a room full of chairs in 1971 without assistance from people.
Artificial Intelligence’s Development: Obstacles and Advancements
There have been difficulties along the way as AI has developed. Known as the ‘AI winter,’ the subject saw a decline in funding and interest during the 1960s and 1970s as a result of technological constraints. This period was characterized by dwindling interest and investment because of technological constraints and the failure to fulfill lofty goals. When did AI start to advance significantly? When IBM’s Deep Blue defeated world chess champion Garry Kasparov in 1997, it was the first breakthrough following this difficult time.
This momentous triumph demonstrated AI’s capacity to handle challenging, human-level tasks. The development of AI was made possible by this accomplishment, which came at the same time that the internet and processing power increased dramatically in the late 1990s and early 2000s.
The Development of Contemporary AI: Neural Networks and Deep Learning
With the title “2006 Deep Learning,” the background is dark. A picture of Geoffrey Hinton with an animated brain that reads “Deep Learning” is seen below. Geoffrey Hinton’s introduction of “deep learning” techniques in 2006 marked a turning point in the history of artificial intelligence. Inspired by the human brain, deep learning neural networks demand a lot of data and processing power, which are just starting to become accessible.
The field advanced quickly thanks to several significant developments:
2012: Up to that year, AI was able to identify voice and body motions, play chess, and perform some difficult tasks. This year, without any prior information, the AI was able to identify cats from their unlabeled photos. Deep neural networks were upgraded by Stanford and Google researchers through innovative unsupervised learning research.
2017 saw the introduction of transformers by the Google Brain team, which transformed natural language processing.
2019: Google’s AlphaStar achieved Grandmaster status in the video game StarCraft 2, outperforming all human players save for.2%.
FAQs on the History of AI
What Makes AI Dangerous?
AI is concerning for several reasons, including biased programming, unclear legal regulations, and consumer privacy. However, if we can take into account all of these concerns and take the appropriate steps to control AI, it will be a blessing.
By 2030, How Will AI Affect the World?
By 2030, AI will be more potent. It will assist people in the study and creation of novel medications to treat a variety of currently incurable illnesses. In addition, AI will be a fantastic educational aid, instructing kids in a variety of general and academic subjects.
How Does AI Get Made?
Machine Learning is a subfield of artificial intelligence and computer science that focuses on using data and algorithms to enable AI to learn in the same way as people and progressively increase its accuracy.
