Artificial Intelligence (AI) has been a topic of study for the last seven decades, marking what some consider to be the beginning of the field. Since that time, there has been an upsurge of interest in newly developed methods, which has led to the development of a wide variety of useful applications.
In this article, we will address the history of Artificial Intelligence – the reasons behind the current enthusiasm around machine learning and explore some of the highs and lows of AI.
The emergence of Artificial Intelligence
Alan Mathison Turing, a British mathematician and computer scientist, is credited as being the first person to propose the concept of Artificial Intelligence in the year 1950.
The issue of whether or not computers are capable of thought is posed at the beginning of Alan Turing’s work titled “Computing Machinery and Intelligence.”
This inquiry is generally regarded as the moment when artificial intelligence (AI) came into being and marks the beginning of a short history of Artificial Intelligence.
In his work, he proposed the idea of “The Imitation Game,” sometimes known as the “Turing Test.” An interrogator will pose questions to a computer as well as a real person, and the computer should act as if it is the actual person in order to deceive the human interrogator with its responses.
All responses must be written down, and audio cannot be utilized in any way. In order for the computer to succeed in the exam, the interrogator must not be able to tell who the actual person is. In order for machines to pass the exam, they will need to convincingly impersonate humans.
The evolution of AI throughout the years
1940s-1950s
Alan Turing, a mathematician and cryptanalyst from the United Kingdom, is in charge of the group that deciphers the German Enigma Machine coding encryption during World War II. In the year 1950, Alan Turing proposed that computer programs might be trained to think in the same way that people do. He also developed a hypothetical test to assess whether or not a machine could impersonate a human well enough to mislead another human.
1960s
Joseph Weizenbaum of MIT develops ELIZA, one of the first examples of a natural language processing system. Weizenbaum designs ELIZA to have a conversation with partners in a way that is realistic by using pattern matching and replacement. This is done so that he can illustrate how shallow communication may be between people and robots. The software, which is considered to be one of the earliest chatbots, is incapable of understanding the context of events.
1970s-1980s
Shakey, one of the early Artificial Intelligence (AI) robots, was created at the Stanford Research Institute. Shakey was able to observe its surroundings, navigate, plan a route, compensate for mistakes, enhance its route-planning skills via learning, as well as speak in basic English when it was tethered to a mainframe computer and connected through a tether cable.
1990s
Work on machine learning is moving away from techniques that are knowledge-driven and toward approaches that are data-driven. Researchers get started writing computer programs to examine massive volumes of data, come to conclusions based on those analyses, and learn from their experiences.
2000s
Google develops an autonomous vehicle that may be seen cruising about the streets of Mountain View, California. The vehicle has sensors, a global positioning system (GPS), cameras, radar, and lasers, which allow it to identify things up to two football fields away.
Also, Siri is Apple’s new digital assistant that will be available for use on iPhones. The Artificial Intelligence Center of SRI International was the original developer of this technology. Siri employs voice-activated inquiries and a natural-language interface to answer questions, make suggestions, as well as execute administrative duties utilizing the applications that are pre-installed on the user’s phone as well as Internet connectivity.
In addition to that, Microsoft showcases their Kinect technology, which is capable of recognizing twenty human traits at a pace of thirty times per second.
Because of this advancement, individuals are now able to communicate with computers via gestures and motions.
Applications based on machine learning are starting to take the role of text-based passwords. It is becoming more popular to unlock a smartphone by utilizing a biometric safeguard, such as a fingerprint or a photograph of the user’s face. Monitoring how and where a user operates a device is done by behavior-based security systems.
Conclusion
As a result of seeing and experiencing the history of Artificial Intelligence as well as what artificial intelligence is capable of doing in the world as it exists now, it is abundantly clear that AI will accomplish far more in the future.
AI has the potential to improve accuracy and speed up the completion of laborious or repetitive jobs that would take humans far longer. This results in increased productivity for working individuals as well as companies. It is possible that this is evidence that AI will become more important in the future and that it will be the answer to all of our issues.
