Artificial Intelligence Interview Questions

Q1. What is Artificial Intelligence?

Ans: Artificial Intelligence is an area of computer science that emphasizes the creation of intelligent machine that work and reacts like humans.

Q2.  What is the difference between strong AI and weak AI?

Ans: Strong AI makes the bold claim that computers can be made to think on a level (at least) equal to humans. Weak AI simply states that some "thinking-like" features can be added to computers to make them more useful tools... and this has already started to happen (witness expert systems, drive-by-wire cars and speech recognition software). What does 'think' and 'thinking-like' mean? That's a matter of much debate.

Q3.  What is an artificial intelligence Neural Networks?

Ans: Artificial intelligence Neural Networks can model mathematically the way biological brain works, allowing the machine to think and learn the same way the humans do- making them capable of recognizing things like speech, objects and animals like we do.

Q4. What are the various areas where AI (Artificial Intelligence) can be used?

Ans: Artificial Intelligence can be used in many areas like Computing, Speech recognition, Bio-informatics, Humanoid robot, Computer software, Space and Aeronautics’ etc.

Q5.  What is a top-down parser?

Ans: A top-down parser begins by hypothesizing a sentence and successively predicting lower level constituents until individual pre-terminal symbols are written.

Q6.  Where can I find conference information?

Ans: Georg Thimm maintains a webpage that lets you search for upcoming or past conferences in a variety of AI disciplines.

Q7.  Which is not commonly used programming language for AI?

Ans: Perl language is not commonly used programming language for AI

Q8.  What is Prolog in AI?

Ans: In AI, Prolog is a programming language based on logic.

Q9.  Give an explanation on the difference between strong AI and weak AI?

Ans: Strong AI makes strong claims that computers can be made to think on a level equal to humans while weak AI simply predicts that some features that are resembling to human intelligence can be incorporated to computer to make it more useful tools.

Q10.  What are the various areas where AI (Artificial Intelligence) can be used?

Ans: Artificial Intelligence can be used in many areas like Computing, Speech recognition, Bio-informatics, Humanoid robot, Computer software, Space and Aeronautics’ etc.

Q11.  Which is not commonly used programming language for AI?

Ans: Perl language is not commonly used programming language for AI

Q12.  Mention the difference between statistical AI and Classical AI?

Ans: Statistical AI is more concerned with “inductive” thought like given a set of pattern, induce the trend etc.  While, classical AI, on the other hand, is more concerned with “deductive” thought given as a set of constraints, deduce a conclusion etc.

Q13.  A* algorithm is based on which search method?

Ans: A* algorithm is based on best first search method, as it gives an idea of optimization and quick choose of path, and all characteristics lie in A* algorithm.

Q14.  What does a hybrid Bayesian network contain?

Ans: A hybrid Bayesian network contains both a discrete and continuous variables.

Q15.  What is agent in artificial intelligence?

Ans: Anything perceives its environment by sensors and acts upon an environment by effectors are known as Agent. Agent includes Robots, Programs, and Humans etc.

Q16.  What is Prolog in AI?

Ans: In AI, Prolog is a programming language based on logic.

Q17.  What are the branches of AI?

Ans: There are many, some are 'problems' and some are 'techniques'.

Automatic Programming - The task of describing what a program should do and having the AI system 'write' the program.

Bayesian Networks - A technique of structuring and inference with probabilistic information. (Part of the "machine learning" problem).

Constraint Satisfaction - solving NP-complete problems, using a variety of techniques.

Knowledge Engineering/Representation - turning what we know about particular domain into a form in which a computer can understand it.

Machine Learning - Programs that learn from experience or data.

Natural Language Processing (NLP) - Processing and (perhaps) understanding human ("natural") language also known as computational linguistics.

Neural Networks (NN) - The study of programs that function in a manner similar to how animal brains do.

Planning - given a set of actions, a goal state, and a present state, decide which actions must be taken so that the present state is turned into the goal state

Robotics - The intersection of AI and robotics, this field tries to get (usually mobile) robots to act intelligently.

Speech Recognition - Conversion of speech into text.

Q18.  Give an explanation on the difference between strong AI and weak AI?

Ans: Strong AI makes strong claims that computers can be made to think on a level equal to humans while weak AI simply predicts that some features that are resembling to human intelligence can be incorporated to computer to make it more useful tools.

Q19.  In Inductive Logic Programming what needed to be satisfied?

Ans: The objective of an Inductive Logic Programming is to come up with a set of sentences for the hypothesis such that the entailment constraint is satisfied.

Q20. In top-down inductive learning methods how many literals are available? What are they?

Ans: There are three literals available in top-down inductive learning methods they are

1. Predicates
2. Equality and Inequality
3. Arithmetic Literals

Q21.  What is Hidden Markov Model (HMMs) is used?

Ans: Hidden Markov Models are a ubiquitous tool for modeling time series data or to model sequence behavior.  They are used in almost all current speech recognition systems.

Q22.  In Hidden Markov Model, how does the state of the process is described?

Ans: The state of the process in HMM’s model is described by a ‘Single Discrete Random Variable’.

Q23.  In HMM’s, what are the possible values of the variable?

Ans: ‘Possible States of the World’ is the possible values of the variable in HMM’s.

Q24.  In HMM, where does the additional variable is added?

Ans: While staying within the HMM network, the additional state variables can be added to a temporal model.

Q25.  In Artificial Intelligence, what do semantic analyses used for?

Ans: In Artificial Intelligence, to extract the meaning from the group of sentences semantic analysis is used.