Artificial Intelligence Is The Future Of New Technologies

Humans have three percent human error, and a lot of companies can’t afford to be wrong three percent of the time anymore so, we close that three percent gap with some of the technologies. The AI we’ve developed doesn’t make mistakes.

Artificial intelligence as the name suggests is the intelligence that is contrived by art rather than nature. In technical terms, or say in computer science, artificial intelligence is sometimes known as the machine intelligence. That is, the intelligence exhibited by a machine in contrast to natural human or even animal intelligence. The idea of making a machine intelligent and think as we humans do is itself very fascinating and challenging at the same time.

The AI originated from Alan Turing’s theory of computation that put forward the ability of machines to simulate any conceivable act of mathematical deduction by simply shuffling symbols like ‘0’ and ‘1’. This is known as the ‘Church-Turing thesis’. Alan Turing proposed a test to consider the question, can machines think?. This test consists of two persons, out of which one is the interrogator, and one machine. Now the interrogator is connected to the other person and the machine via a terminal so that they cannot see each other. The interrogator’s task is to find out which of the two candidates is the machine, and which is the human only by asking them questions. If the machine succeeds in fooling the interrogator, it is intelligent.

The field of AI research began in 1956 at the Dartmouth college in Hanover, New Hampshire, United States, where Allen Newell, Herbert Simon, John Mc Carthy, Marvin Minsky and Arthur Samuel, the attendees of a workshop held at the college, became the founders and leaders of AI research.

In the early 1980s, expert systems came into picture. An expert system is nothing but a computer application that acts intelligently, and solves the problems just the same way a human expert would do.

Artificial Intelligence works based on its four basic agents which are explained below:

Simple reflex agent

This agent works based on its current information, that is, the knowledge or information that has been acquired before is used and no new information is gathered. They have very limited intelligence as it totally depends on the knowledge base.

Model based reflex agent

Model based reflex agent take decisions based on a model of the world, like what is happening in the world, and then they decide what actions they should take. Model based agent can perfectly manage partially observable states.

Goal based agent

The goal based agent works based on some pre-specified goals, that is, the description and desirability of some situations. The main aim of goal based agent is to reduce the distance between the current state and the goal state.

Utility based agent

Utility based agent works on preferences rather than any model or any kind of goals. Their main motive is to decide how happy the agent is by taking any particular decision.

Artificial intelligence has a great scope in game playing, and also in the problems like water-jug problem, missionaries and cannibal problem, hill climbing problem, monkey and banana problem, and many more.