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3. What do we understand by Ai with the historical background? How is AI related to ChatGPT with the Turing Test? Can you briefly explain Machine Learning?

Artificial Intelligence (AI) towards Machine Learning (ML)


Artificial Intelligence, commonly known as AI, has revolutionised the computerised era. Artificial Intelligence reflects ideas that allow computers to do things that make people appear intelligent. AI will bring a new technological revolution and make the working environment so convenient that modern machines are programmed to think and then act with some level of human Intelligence. For example, AI is widely used in the car park to recognise the car plate registration number. The military, medical sector, insurance companies, aviation industry, and education institutes are widely using the AL and depend on this daily. Modern business can only be successful with AI’s intervention, so it is needed most in the commerce and business industry. And to be good at perfect AL, somebody has to know the statistical techniques and programming languages like R, SAS, and python are few of them.


By the 1950s, we had seen a generation of scientists, mathematicians, statisticians, and philosophers with the idea of Artificial Intelligence (AI), which became a cup of tea in their daily life. Later in 1956, Artificial Intelligence was first minted at Dartmouth College in the United States of America. Finally, in the first half of the 20th century, science fiction familiarised the world with the idea of artificial robots.

The first young British mathematician and logician, Alan Turing, explored the mathematical possibility of Artificial Intelligence—the department of Mathematics building called Alan Turing at the University of Manchester, with respect to Alan Turing. From 1948 to 1950, Turin’s programming system was applied in the Ferranti Mark I, the first commercial electronic digital computer (1951). It is widely known as Turing, was a founding father of Artificial Intelligence and modern cognitive science.

Turing suggested that humans use available information and reason to solve problems and make decisions, so why can machines not do the same thing? After this, a lot of research and development took place to make AI more advantageous for humanity. Finally, in 1950, Turing suggested what we know as “The Turing Test” as a benchmark for whether an Artificial Computer is thinking. In late 2022, the advent of ChatGPT reignited the conversation about the likelihood had met the components of the Turing test.


Machine Learning:

On the other hand, Machine Learning, known as ML, is a branch of Artificial Intelligence which concentrates on using data and algorithms to emulate how humans learn, gradually improving its accuracy.

Machine Learning (ML) is the study of algorithmic induction to develop algorithms, and it grew out as a subset or a core branch of Artificial Intelligence (AL). In 1959, Arthur Samuel defined it as the “field of study that gives computers the ability to learn without being explicitly programmed” [1].

Practical machine-learning techniques are regression or estimation, classification, clustering, association, sequence mining, anomaly detection, etc. Some vital machine learning techniques applied to dynamic pricing problems include evolutionary algorithms, reinforcement learning, Q-learning, neural networks, particle swarm optimisation, simulated annealing, Markov chain Monte Carlo methods, and the aggregating algorithm, direct search methods, and so on [2].