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Artificial Intelligence Definition – The Basics

What is the process behind Artificial Intelligence Work?

What is AI?

Just a decade after aiding the Allied forces in winning World War II by breaking the Nazi encryption machine Enigma the mathematician Alan Turing revolutionized the world a second time by asking a query: “Can machines think?”

Turing’s paper from 1950, ” Computing Machinery and Intelligence,” and the following Turing Test set the primary concept and purpose of AI.

At its heart, AI is the branch of computer science that aims to answer Turing’s query with a positive answer. It’s the attempt to duplicate or replicate the human brain within machines. The broad scope that is the goal of AI has led to a variety of debates and questions. This is the reason why there is no one-size-fits-all description of AI that has been widely accepted.

Definition of AI

The main problem with the idea of defining AI as just “building smart machines” has to do with the fact that it fails to define the definition of AI or the factors that make machines capable of being intelligent. AI is an interdisciplinary science that employs numerous approaches, yet advances in the field of machine understanding, as well as deep learning, have led to an era-changing paradigm in almost every aspect of the technology business.

However, several new tests have been suggested in recent times that have been well-received, including the 2019 research paper titled ” On the Measure of Intelligence.” In the article, a seasoned Deep Learning researcher, as well as Google engineer Francois Chollet argues that intelligence is the “rate at which a student transforms their prior knowledge and experience into new capabilities for tasks that require uncertainty and adaptability.” In the words of experts: The most intelligent systems can only take a few years of knowledge and proceed to speculate on the outcome of a wide range of scenarios.

In their work Artificial Intelligence A Contemporary Approach, the writers Stuart Russell and Peter Norvig discuss the notion of AI by uniting their work on the subject of intelligent agents within machines. This is why they say that AI refers to “the study of agents that detect perceptions from their environment and carry out actions.”


  • Thinking like a human by mimicking thoughts that are based on the human brain.
  • Thinking rationally mimicking thought that is based on logic.
  • Humanizing yourself means acting in a manner that resembles human behavior.
  • Being rational: acting in a manner designed to accomplish a specific purpose.

The first two ideas are about thinking processes and reasoning, and the remaining ideas focus on behavior. Norvig and Russell concentrate on rational agents who act in a way that will yield the greatest results and note that “all the capabilities required to pass taking the Turing Test also allow an agent to behave rationally.”

A former MIT faculty member of AI and computer science Patrick Winston defined AI as “algorithms that are facilitated by constraints, revealed by representations that help models that target loops that link actions, perception and thinking together.”

While these definitions could appear abstract to most people, however, they can help define the field into a specific area of computer science. They also provide an outline for integrating machines and software using AI, ML, or other forms that comprise Artificial Intelligence.

Future of AI: The Future of AI

If you consider the cost of computation and the data infrastructure, which is the basis for Artificial Intelligence, working using AI is a complicated and expensive business. There are massive advances in the field of computing, as evidenced by Moore’s law which says that the amount of transistors in the microchip increases every two years while the price of computers is reduced by half.

While many specialists believe Moore’s Law will likely expire around the year 2020, it has had a huge impact on the current AI methods — without it deep learning, it would be impossible economically speaking. Recent research has revealed that AI advancements have actually over-performed Moore’s Law, doubling every six months or so, instead of two years.

According to this logic, it is clear that the advances artificial intelligence has brought to a range of industries have been significant in the past few years. It is possible to make an even greater impact in the next few decades is likely.