Top 50 Artificial Intelligence Interview Questions & Answers


Artificial Intelligence is poised to reach unprecedented heights with its critical role in the modern economy. It is inherently capable of outdoing humans. In fact, AI is feared to become far more dangerous than nukes in the near future. With the growing importance and popularity of AI and its interference, there is a surging need for experts who can outlay the best practices and machinations to use AI in the best possible ways. 

In order to tread the path of an AI profession, one must qualify certain specified criteria, and Interview is a crucial step in landing an AI-based job. While learning about AI itself may be complicated, facing an interview may be nerve-wracking, especially for beginners. The best way is to take help from a good resource such as a guide to artificial intelligence interview questions & answers. To help prospective candidates have a seamless interview preparation and boost their confidence in facing interviews we have curated the top artificial intelligence questions & answers

Best Artificial Intelligence Interview Questions and Answers

1. Define Artificial Intelligence

Artificial Intelligence can be defined as the domain in computer science that focuses on the creation of intelligent machines that operate and react as humans do. 

2. What are neural networks used in artificial intelligence?

Neural Networks in artificial intelligence can theoretically simulate the functioning of the biological brains, by giving machines the ability to understand and learn in a similar way to humans, enabling them to recognize things like speech, object, and animals in the same ways that people do. 

3. What are the different applications of AI?

Numerous fields make use of AI some of them are: Bioinformatics, speech recognition, computer software, humanoid robots, computing, space and aeronautics, computer software, etc.

4. Which language is not typically used in AI?

Amongst the programming languages, Perl is not typically used in AI

5. Explain Prolog in AI

Prolog is a logic-based programming language that used AI.

6. Describe the distinction between strong and weak artificial intelligence?

While weak AI just forecasts that some aspects that are like human intellect can be added to computers to make them more effective tools, strong AI makes strong assertions that computers can be enabled to think on an equivalent level to humans. 

7. What distinguishes statistical AI from classical AI?

Statistical AI places more emphasis on "inductive" cognition, such as assuming a set of patterns and inferring a trend, etc. On the other hand, traditional AI is primarily focused on "deductive" cognition, where a set of constraints are used to infer a conclusion, etc.

8. What are alternate keys, artificial keys, compound keys, and natural keys?

Alternate Key: All candidate keys, excluding primary keys, are referred to as Alternate Keys.

Artificial Key: As a last resort, one might simply invent a key by giving a number to each record or occurrence if there isn't an evident key that exists either alone or in combination. Such keys are artificial key.

Compound Key: When a construct's occurrence cannot be defined by a single data element, a compound key is created by combining many elements to serve as the construct's only identifier.

Natural Key: A natural key is one of the data elements that is used as the primary key and is stored within a construct.

9. What are the components of a production rule?

A sequence of steps and a set of rules make up a production rule. 

10. Which search method takes less memory?

The “depth-first search” method takes less memory.

11. What is the best course of action for a game-playing issue?

For game-playing issues, the heuristic approach is the ideal course of action because it employs a method based on informed speculation. As an illustration, imagine playing chess against a computer using brute force calculation to look at millions of possible positions.

12. On what kind of search strategy is the  A* algorithm based?

The best initial search method is the foundation of the A* algorithm since it provides a quick and easy way to choose a path while also providing a notion of optimization.

13. What is a Hybrid Bayesian network composed of?

The variables in a hybrid Bayesian network might be discrete or continuous.

14. Define Agent in Artificial Intelligence

Anything that perceives its environment by sensors and acts upon an environment by effectors is referred to as an Agent in AI. They include Robots, Programs, Humans, etc. 

15. Name the two steps involved in constructing a plan

The two steps are

  • Add an operator (action)
  • Add an ordering constraint amid operators

16. What is involved in partial planning or order?

Instead of looking through potential scenarios, partial order planning looks through the space of potential plans. Building a plan incrementally is the idea.

17. Which attribute of a logical rule-based system is not seen as desirable?

"Attachment" is not regarded as a desirable characteristic of a system based on logical rules. 

18. Explain a neural network

A neural network in artificial intelligence is a simulation of a biological neural system that receives, processes, and outputs data based on an algorithm and empirical evidence.

19. When is an algorithm deemed finished?

When an algorithm concludes with a solution when one exists, it is said to be finished.

20. What does a Heuristic function entail?

In search algorithms, a heuristic function rates options according to the information at hand to determine which branch to take.

21. What purpose does the third part of the planning system serve?

The third component of a planning system's job is to determine when an issue has a solution.

22. Explain Generality in AI

The degree of generality indicates how easily a method can be applied to other application domains. 

23. Describe a top-down parser

A top-down parser starts by speculating on a sentence and then predicts each lower-level component one by one until individual pre-terminal symbols are written.

24. How do breadth-first search and best first search vary in artificial intelligence?

These two approaches are pretty similar to one another. We enlarge the nodes in the best-first search in line with the evaluation function. In contrast, a node in a breadth-first search is enlarged in accordance with the parent node's cost function. 

25. Explain Frames and Scripts in Artificial Intelligence.

Semantic networks, one of the common ways to communicate non-procedural knowledge in an expert system, have a variant known as frames. By describing "stereotyped circumstances", a frame, an artificial data structure, is utilized to segment knowledge into the substructure. With the exception of the requirement for ordered values, scripts are analogous to frames. In order to arrange a knowledge base that is reflective of the circumstance that the system should grasp, natural language understanding techniques use scripts.

26. Define FOPL and describe its function in Artificial Intelligence

FOPL simply means First Order Predicate Logic which is a type of logic in AI that offers the following:

  • A language used to make claims about a certain "World"
  • A method for inferring inferences from an assertion using a deductive apparatus.
  • A set theory-based semantic

27. What does FOPL language consist of?

FOPL language consists of the following components:

  • Set of constant symbols
  • Collection of variables
  • Set of symbols for the predicate
  • A group of function symbols
  • The logical connective
  • The Universal and Existential Qualifiers
  • A unique binary relation of equality (g)

28. Which search agent for "Artificial Intelligence" internet searches interleaves computation and action?

When conducting an online search, it will initially act before looking around.

29. Which online search algorithm will consume the least amount of memory?

With a finite amount of memory, RBFE and SMA* can solve any issue that A* cannot.

30. In what applications of "Artificial Intelligence" might the Bayes rule be used?

Bayes rule can be used in Artificial Intelligence to respond to probabilistic questions based on a single piece of data.

31. How many terms are needed to form a Bayes model?

Three terms are needed to form a Bayes model in AI: one conditional probability and two unconditional probabilities.

32. When building a Bayesian network, what effect do a node's predecessors have on it?

When building a Bayesian network, a node's relationship to its forebears has the effect that a node can be conditionally independent of them.

33. How can the Bayesian network be applied to resolve any issue?

A Bayesian Network may answer any question by adding up all the pertinent joint entries if it is representative of the joint distribution.

34. What harnesses the strength of first-order representations and inductive techniques?

Programming with inductive logic blends inductive techniques with the strength of first-order representations.

35. What conditions had to be met for inductive logic programming to work?

Finding a set of sentences for the hypothesis that satisfy the entailment requirement is the goal of inductive logic programming.

36. How many literals are available when using top-down inductive learning techniques? Describe them.

In top-down inductive learning approaches, three literals are available:

  • Predicates
  • Inequality and Diversity
  • Mathematical Literals

37. What algorithm reverses a full-resolution approach?

Since it is a complete procedure for learning first-order theories, "Inverse Resolution" inverts a complete resolution.

38. What kind of signal is employed in speech recognition?

A word sequence is recognized using an acoustic signal in speech recognition.

39. In voice recognition, which model provides the likelihood that each word will be followed by its counterpart?

The bigram model estimates the likelihood that each word will follow another in speech recognition.

40. Which method is applied to temporal probabilistic reasoning?

HMM (Hidden Markov Model), which is independent of the transition and sensor model, is used to resolve temporal probabilistic reasoning.

41. What is the Hidden Markov Model (HMM) used for?

Secret Markov Models are a common technique for simulating the behavior of sequences or time series data. Nearly all of the voice recognition systems in use today employ them.

42. How is the process state described in a hidden Markov model?

A "Single Discrete Random Variable" in the HMM model describes the state of the process. 

43. What are the variable's potential values in HMMs?

The conceivable values of the variable in HMMs are referred to as "Possible States of the World."

44. Where does the extra variable go in an HMM?

A temporal model can incorporate the additional state variables while remaining within the HMM network.

45. What are semantic analyses utilized for in artificial intelligence?

Semantic analysis is used in artificial intelligence to extract meaning from a group of sentences.

46. What does compositional semantics entail?

Compositional semantics is the process of inferring the meaning of P*Q given P, Q, and*.

47. How may propositional logic be used to resolve logical inference?

The Logical Inference Algorithm in Propositional Logic can be solved by

  • Logical equivalence
  • Reliability
  • Satisfactory aptitude

48. What procedure renders various logical expressions identical?

Different logical formulations are unified to become identical. Finding a replacement that can make a different phrase appear to be the same is necessary for lifted inferences. It is known as unification in this procedure.

49. In "Unification and Lifting," which method takes two sentences and produces a unifier?

The "Unify" method in "Unification and Lifting" takes two sentences and outputs a unifier.

50. Which planning algorithm strategy is the easiest to understand?

The most straightforward method for planning an algorithm is state space search because it considers every factor in order to find a solution.

The above artificial intelligence questions & answers will help you familiarize yourself with the interview pattern and the kind of questions one can expect in an interview.

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