What is Artificial Intelligence?

Artificial Intelligence in simple words:

 Building intelligent computers that can carry out tasks that traditionally require human intelligence is goal of artificial intelligence (AI), broad field of computer science. While there are many different approaches to AI a i, it is an interdisciplinary discipline, and recent developments in the machine learning and deep learning in particular are causing a paradigm change in almost every area of the tech industry. 

Machine equipped with artificial intelligence are able to the mimic or even outperform human brain functions. And as generative AI tools like ChatGPT and Google's Bard proliferate and self-driving car technology advances, AI is quickly becoming a part of daily life and a field that businesses in every sector are investing in.

Who is the father of AI?

              A.I. is credited to John McCarthy as its founding father. Computer scientist John McCarthy was from the United States. He was the first to use the term "artificial intelligence." Along with Alan Turing, Marvin Minsky, Allen Newell, and Herbert A. Simon, he is one of the inventors of artificial intelligence.

Who Invented AI first?

             The Turing Test, developed by Alan Turing and used by experts to gauge computer intelligence, was first published in his essay "Computer Machinery and Intelligence." The phrase "artificial intelligence" was created and spread to the general public.

Who is the first AI in the world?

            Christopher Strachey's checkers-playing program and Dietrich Prinz's chess-playing program were the first functional AI programs created in 1951 for the University of Manchester's Ferranti Mark 1 computer.

Understanding AI:

Generally, artificially intelligent systems are capable of carrying out activities that are the frequently linked to the human cognitive abilities, like understanding speech, engaging in games, and spotting patterns. They often acquire this skill by sifting through vast volumes of data and seeking for patterns to mimic in their own judgment. Humans will frequently oversee an AI's learning process, rewarding wise choices and criticizing poor ones. However, some Artificial intelligence systems are built to learn on their own, for instance by the repeatedly playing a video games until they figure out the rules and how to win.

Artificial Intelligence examples:

1:Chatbot

2: Machine Learning

3: Virtual Assistant

4: Pattern Recognition

5: Natural Language Processing etc.

Strong AI vs. Weak :

 AI Intelligence is difficult to describe, which is why strong AI and weak AI are often distinguished by AI professionals.

Powerful AI :

A computer with strong AI, commonly referred to as artificial general intelligence, can tackle problems it has never been taught to address, much like a human can. The robots from Westworld and the character Data from Star Trek: The Next Generation are examples of this type of artificial intelligence. There isn't truly any AI of this kind yet.

The Holy Grail for many AI researcher is the development of computer with human-level intelligence that can used for any task, yet the path to artificial the general intelligence has not been easy. Additionally, some people think that research into powerful AI should be restricted because of the dangers of developing such a powerful AI without the necessary safeguards.

Weak AI :

Weak AI, also known as narrow AI or specialized AI, is a simulation of human intelligence used to solve a tightly specified issue (such as driving a car, transcribing human speech, or selecting material on a website). Weak AI functions inside a confined context.

Weak AI frequently focuses on excelling at a single activity. Despite the fact that these robots appear clever, they are subject to much more restrictions and limits than even the most primitive human intellect.

Examples of weak AI include:

Smart assistants like Siri, Alexa, and others

Autonomous vehicles

Google search

Interactive robots

Spam filters for email

Netflix's suggestions

Deep learning vs. machine learning :

Although "deep learning" and "machine learning" are frequently used interchangeably in discussions of AI, they should not be. Machine learning, which includes deep learning, is a branch of artificial intelligence.

Learning Machines :

A computer feeds data to a machine learning algorithm, which then use statistical methods to "learn" how to improve over time at a task without necessarily having been programmed for it. Instead, ML algorithms estimate new output values using historical data as input. Thus, supervised learning, where the expected output for the input is known owing to the use of labeled data sets, and unsupervised learning, where the expected outputs are uncertain due to the use of unlabeled data sets, make up ML.

Deep Learning :

Deep learning is a sort of the machine learning that processes inputs through a neural network design that was inspired by biological processes. The data is processed through a number of hidden layers in neural networks, enabling the machine to learn "deeply," forming connections and weighing input for the optimal outcomes.

Based on the kind and level of difficulty of the tasks a system is able to complete, there are four different types of AI. As follows:

1: machines that react

2: restricted memory

3: concept of mind

4: aware of oneself