AI Interview Questions and Answers

AI is a domain of computer science that refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.

AI was introduced in the year 1956, at a conference at Dartmouth College, in Hanover, New Hampshire, where the term "artificial intelligence" was coined.

The AI can be categized into the following types:

• Reactive machines
• Limited memory
• Theory of mind
• Self-awareness

There are a lot of applications of AI. Some of these are:

• AI in Astronomy
• AI in Automotive Industry
• AI in Data Security
• AI in Finance
• AI in Healthcare
• AI in Automation

The various subsets of AI are Machine Learning, Deep Learning, Natural Language Processing, Robotics, Neural networks, Computer Vision, etc.

An intelligent agent is an autonomous entity or entity that makes a decision, that enables artificial intelligence to be put into action. Such that it could conduct operations in the place of users or programs after sensing the environment.

Augmented intelligence is the part of AI that is used for decision making.

Knowledge representation is the field of artificial intelligence or AI dedicated to representing real-world information in a form that a computer system can utilize to solve complex and real-life tasks.

Strong AI has a complex algorithm that helps it act in different situations such that the machines are consist of their own mind, whereas weak AIs are pre-programmed by a human and the machines can only simulate human behavior.

Statistical AI is a part of machine learning which is concerned with inductive thought i.e. given a set of patterns, induce the trend. Whereas Classical AI is concerned with deductive thought i.e. given a set of constraints, deduce a conclusion.

In Artificial intelligence, a neural network is an interconnected group of nodes, inspired by a simplification of neurons in a brain that is meant to simulate the functioning of a human brain.

Bayes rule is also known as Bayes' theorem determines the probability of an event with uncertain knowledge. In probability theory, it relates the conditional probability and marginal probabilities of two random events.

There are several areas where AI is used. Some of these are:

• Manufacturing and Production.
• Sports Analytics and Activities.
• Live Stock and Inventory Management.
• Agriculture and Farming.
• Security and Surveillance.