Artificial Intelligence Interview Questions-Answers – Grab the Knowledge
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1. Artificial Intelligence Interview Questions-Answers
Through this blog, you will get best Artificial Intelligence Interview Questions-Answers. As we have discussed Artificial Intelligence Interview Questions-Answers in our previous blog also. Although, in this blog, we will provide you Artificial Intelligence Interview Questions – Answers for both freshers as well as experienced peoples. In this blog, we have covered every type of Artificial Intelligence Interview Questions-Answers.
Mostly asked Artificial Intelligence Interview Questions-Answers
2. Best Artificial Intelligence Interview Questions-Answers
Q.1. What are the disadvantages of breadth-First Search Algorithm?
- It consumes a lot of memory space. As each level of nodes is saved for creating the next one.
- Its complexity depends on the number of nodes. It can check duplicate nodes.
Q.2. What are the disadvantages of Depth-First Search Algorithm?
- As the algorithm may not terminate and go on infinitely on one path. Hence, a solution to this issue is to choose a cut-off depth.
- If the ideal cut-off is d, and if the chosen cut-off is lesser than d, then this algorithm may fail.
- If the chosen cut-off is more than d, then execution time increases.
- Its complexity depends on the number of paths. It cannot check duplicate nodes.
Q.3. What is iterative Deepening Depth-First Search Algorithm?
To perform this search we need to follow steps. As it performs the DFS starting to level 1, starts and then executes a complete depth-first search to level 2. Moreover, we have to continue searching process till we find the solution. We have to generate nodes till single nodes are created. Also, it saves the only stack of nodes.
As soon as he finds a solution at depth d, the algorithm ends, The number of nodes created at depth d is bd and at depth d-1 is bd-1.
Q.4. What is informed (Heuristic) Search Strategies Algorithm?
To increase the efficiency of search algorithm we need to add problem-specific knowledge. We use this to solve large problems with a large number of possible states
a. Heuristic Evaluation Functions
We use this function to calculate the path between two states that a function takes for sliding-tiles games. which we have to calculate by computing number of rows. Also, moves of each tile make from its goal state. Further, adding these number of moves for all tiles.
b. Pure Heuristic Search
In order, if heuristic value nodes will expand. Also, creates two lists:
- First, a closed list of the already expanded nodes;
- Secondly, an open list created. Although, unexpected nodes.
A node with a minimum heuristic value is expanded, In each iteration. Also, all its child nodes are created and placed on the closed list. Further, we apply this heuristic function to child nodes. Thus, at last, we have to place it in the open list, as per the heuristic value. Although, we have to save the shortest path while to dispose of the longer ones.
Q.5. What is meant by A * Search Algorithm?
We can say that A * Search is the best form of Best First Search. Also, avoids expensive expanding path. Although, first expands most promising path.
f(n) = g(n) + h(n), where
g(n) is the cost to reach the node
h(n), it is estimated cost to get from the node to the goal
f(n) it is defined as the estimated total cost of path through n to goal. Also, we will use priority queue by increasing f(n) to implement it.
Q.6. What is Greedy Best First Search Algorithm?
The node which is closest to goal will be expanded first. Although, explanation of nodes depends upon f(n) = h(n). Further, using priority queue we implement it.
Disadvantage
- It can get stuck in loops. It is not optimal.
Q.7. What is Local Search Algorithms?
Basically, it’s Popular Search Algorithms. Also, a prospective solution. Further, moves to a neighboring solution. Moreover, returns a valid solution.
a. Hill-Climbing Search Algorithm
We can start this algorithm with an arbitrary solution to a problem. Also, it’s an iterative algorithm. Hence, the algorithm attempts to better solution by a single element of the solution. Although, we take an incremental change as a new solution. As if the change produces a better solution. Moreover, we have to repeat until there are no further improvements.
b. Local Beam Search Algorithm
In this algorithm, we have to hold k number of states at any given time. In the beginning, we have to generate states randomly.
Moreover, with the objective function, we have to compute successors of these k states. Also, this stop, if any of these successors is the maximum value of the objective function.
Otherwise, we have to put the (initial k states and k number of successors of the states = 2k) states in a pool. Also, a pool is then sorted numerically. Further, we have to select highest k states as new initial states. This process continues until a maximum value is reached.
Q.8. What is simulated annealing Algorithm?
The process is of heating and cooling a metal to change its internal structure. Although, for modifying its physical properties is known as annealing. As soon as the metal cools, it forms a new structure. Also, metal is going to retain its newly obtained properties. Although, we have to keep the variable temperature in a simulated annealing process.
First, we have to set high temperature. Then, left it to allow “cool” slowly with the proceeding algorithm. Further, if there is high temperature, algorithm accepts worse solutions with high frequency.
Start
Initialize k = 0; L = integer number of variables;
From i → j, search the performance difference Δ.
If Δ <= 0 then accept else if exp(-Δ/T(k)) > random(0,1) then accept;
Repeat steps 1 and 2 for L(k) steps.
k = k + 1;
Repeat steps 1 through 4 till the criteria matches.
End
Artificial Intelligence Interview Questions-Answers for freshers- Q. 1,2,3,5,6
Artificial Intelligence Interview Questions-Answers for Experienced- Q. 4,7,8
Q.9. What is Travelling Salesman Problem?
The main goal of this problem is to find a low-cost tour. That starts from a city, visits all cities en-route exactly once and ends at the same starting city.
Start
Find out all (n -1)! Possible solutions, where n is the total number of cities.
Further, determine the minimum cost by finding out the cost of each of these (n -1)! solutions.
Finally, keep the one with the minimum cost.
End
Q.10. What is Natural Language Processing?
We use English language to communicate between an intelligent system and N.L.P. Processing of Natural Language plays an important role in various systems.
For Example:
A robot, it is used to perform as per your instructions. The input and output of an N.L.P system can be −
- Speech
- Written Text
Q.11.What are components of N.L.P?
Basically, there are two components of Natural Language Processing systems:
a. Natural Language Understanding (NLU)
In this, we have to understand the basic tasks −
- Basically, the mapping to given input in natural language into useful representations.
- Analyzing different aspects of the language.
b. Natural Language Generation (NLG)
We have to produce meaningful phrases and sentences. That is in the form of natural language from internal representation.
As this process involves:
a. Text planning
In this process, we have to retrieve the relevant content from a knowledge base.
b. Sentence planning
We have to choose required words for setting a tone of the sentence.
c. Text Realization
Basically, it’s process of mapping sentence plan into sentence structure.
Although, the NLU is harder than NLG.
Q.12. What are difficulties in NLU?
a. Lexical ambiguity
It’s predefined at a very primitive level such as word-level.
b. Syntax Level ambiguity
Basically, in this, we can define a sentence in a parsed way in different ways.
c. Referential ambiguity
Generally, referential ambiguity says that we have to refer something using pronouns only.
Q.13. Name some NLP Terminologies?
a. Phonology
It’s study of organizing sound.
b. Morphology
Basically, it’s study of the construction of words from primitive meaningful units.
c. Morpheme
As we can say that it’s primitive unit of meaning in a language:
a. Syntax
In this, we have to arrange words to make a sentence. Also, involves determining the structural role of words. That is in the sentence and in phrases.
b. Semantics
It defines the meaning of words. Moreover, how to combine words into meaningful phrases and sentences
c. Pragmatics
It deals with use and understanding sentences in different situations. Also, defines how the interpretation of the sentence is affected.
d. World Knowledge
It includes the general knowledge about the world.
Q.14. Explain Steps in N.L.P?
There are generally five steps:
a. Lexical Analysis
We have to analyze the structure of words. The collection of words and phrases in a language is a lexicon of a language.
b. Syntactic Analysis (Parsing)
We use parsing for the analysis of the word. Although, have to arrange words in a particular manner. That shows the relationship of words.
c. Semantic Analysis
It describes dictionary meaning which is meaningful. In task domain, mapping syntactic structures and objects.
d. Discourse Integration
In this step, the meaning of any sentence depends upon the meaning of the previous sentence. In addition. Also brings the meaning to immediately succeeding sentence.
e. Pragmatic Analysis
In this step, data is interpreted on what it actually meant. Although, we have to derive aspects of language which require real-world knowledge.
Q.15. Give examples of NLP systems?
a. Customer Review
- As it’s a most important factor that helps companies to discover relevant information for their business. Further, helps in improving customer satisfaction.
- As more suggestion comes, it’s more relevant services are better. Also, helps in understanding the customer’s needs.
b. Virtual digital assistants
Virtual digital assistant technologies are currently the most well-known type of artificial intelligence.
Q.16. Why Do We Need N.L.P?
With this, we can perform certain tasks such as Automated speech and automated text writing in less time.
Moreover, these tasks include too many NLP applications.
For Example:
Automatic Summarization (to generate summary of given text)
Machine Translation (translation of one language into another)
Artificial Intelligence Interview Questions-Answers for freshers- Q. 9,10,11,13,15,16
Artificial Intelligence Interview Questions-Answers for Experienced- Q. 12.14
Q.17. What is N.L.P Process?
In this process, a text is composed of speech, speech-to-text conversion is performed.
In this mechanism, it involves two processes:
- Natural Language Understanding
- Natural Language Generation
a. Natural Language Understanding
We use natural language understanding to learn the meaning of given text. For NLU, we must understand nature and structure of each word.
i. Lexical Ambiguity
In this, words have multiple meanings
ii. Syntactic Ambiguity
Basically, in this syntactic ambiguity, the sentence having multiple parse trees.
iii. Semantic Ambiguity
Generally, in this, sentence having multiple meaning
iv. Anaphoric Ambiguity
Basically, in this phrase or word are presents. That is previously mentioned but has a different meaning.
b. Natural Language Generation
Basically, automatic text produced from structured data. That is in a readable format with meaningful phrases and sentences. Although, the problem of natural language generation is hard to deal with. It is a subset of NLP.
Natural language generation divided into three proposed stages:
i. Text Planning
Basically, it’s ordering of content in structure data.
ii. Sentence Planning
Generally, from structured data, we have to combine sentences to represent the flow of information.
iii. Realization
Basically, to represent text we use a grammatically correct sentence.
Q.18. Explain applications of N.L.P?
a. Communication
- Basically, a computer is a medium to communicate with users. Also, to learn a new language we can’t force users. Although, for casual users, it’s most important. Such as Managers and children. As they don’t have time and inclination to learn new skills to learn new interaction skills.
- Basically, in natural language, it’s having a vast store of information. Also, we have to access via computers. Although, we have to generate information constantly. Also, it’s in the form of books, business, and government report.
- Generally, in natural language processing, problems of AI arise in a very clear and explicit form.
- Moreover, there are three major aspects of any natural language understanding theory:
b. Syntax
Basically, we use it to describe the form of the language. Also, grammar is used to specify it. further, we use natural language for the A.I languages of logic and computer programs. Also, these language is more complicated than other formal languages.
c. Semantics
Generally, utterances meaning provided with the of semantics. Although, if we want to build this understanding, general semantic theories exist for it.
d. Pragmatics
Basically, we use this component to explain how the utterances relate to the world.
Q.19. What is the importance of N.L.P?
We can understand the advantage of natural language programming in an easy way as we consider two statements:
“Cloud computing insurance should be part of every service level agreement”
“A good S.L.A ensures an easier night’s sleep — even in the cloud.”
Generally, if an individual is used to of NLP, in an entity, a person will recognize cloud computing program. Also, a cloud is an abbreviated form of cloud computing.
Basically, in human language, these type of vague elements appears frequently. Although, machine learning algorithms are historically bad at interpreting. Moreover, many improvements take place in deep learning and artificial intelligence. And interpret them effectively.
Q.20. What is Fuzzy Logic?
Generally, it’s a method of reasoning. Although, resembles human reasoning. Also, it has an approach to decision making in humans. As they involve all intermediate possibilities between digital values YES and NO.
Fuzzy Logic was invented by Lotfi Zadeh. Also, he observed, unlike other computers, it includes a range of possibilities between YES and NO, in a human decision.
Q.21. What is Fuzzy Logic Implementation?
Basically, it can be implemented in systems with various sizes and capabilities. That should be range from mall micro-controllers to large. Also, it can be implemented in hardware, software, or a combination of both in artificial intelligence.
Q.22. Why Fuzzy Logic?
Generally, we use it for the practical as well as commercial purposes.
- Basically, we can use it to consumer products and control machines.
- Although, not give accurate reasoning, but acceptable reasoning.
- Also, this logic helps to deal with the uncertainty in engineering.
Q.23. What is Fuzzy Logic Systems Architecture?
Basically, four parts are shown in this-
a. Fuzzification Module
We use this module to transform the system inputs. As this is a crisp number. Also, helps in splitting the input signal into various five steps.
LP
x is Large Positive
MP
x is Medium Positive
S
x is Small
MN
x is Medium Negative
LN
x is Large Negative
b. Knowledge Base
In this, we have to store it in IF-THEN rules that were provided by experts.
c. Inference Engine
Generally, it helps in simulating the human reasoning process. That is by making fuzzy inference on the inputs and IF-THEN rules.
d. Defuzzification Module
In this module, we have to transform fuzzy set into a crisp value. That set was obtained by an inference engine.
Although, the membership functions always work on a same concept i.e fuzzy sets of variables.
Q.24. What are applications of Fuzzy Logic?
There are some areas of fuzzy logic applications. These are-
a. Automotive Systems
- Automatic Gearboxes
- Four-Wheel Steering
- Vehicle environment control
b. Consumer Electronic Goods
- Hi-Fi Systems
- Photocopiers
- Still and Video Cameras
- Television
c. Domestic Goods
- Microwave Ovens
- Refrigerators
- Toasters
- Vacuum Cleaners
- Washing Machines
d. Environment Control
- Air Conditioners/Dryers/Heaters
- Humidifiers
Q.25. What are advantages of Fuzzy Logic Systems?
- Generally, in this system, we can take imprecise, distorted, noisy input information.
- Also, these logics are easy to construct and understand.
- Basically, it’s solution to complex problems. Such as medicine.
- Also, we can relate math in concept within fuzzy logic. Also, these concepts are very simple.
- Due to the flexibility of fuzzy logic, we can add and delete rules in FLS system.
Artificial Intelligence Interview Questions-Answers for freshers- Q. 17,18,19,21,23,24
Artificial Intelligence Interview Questions-Answers for Experienced- Q. 20,22,25
Q.26. What are disadvantages of Fuzzy Logic Systems?
- Till no designing approach to this fuzzy logic.
- Basically, if logics are simple, then one can understand it.
- Also, suitable for problems which do not have high accuracy.
Q.27. What are Expert Systems in AI?
We can say these are computer applications. Also, with the help of this development, we can solve complex problems. It has level of human intelligence and expertise.
Q.28. Characteristics of AI Expert Systems
- High performance
- Reliable
- Highly responsive
- Understandable
Q.29. Capabilities of Expert Systems
The expert systems are capable of −
- Advising
- Instructing and assisting human in decision making
- Demonstrating
- Deriving a solution
- Diagnosing
- Explaining
- Interpreting input
- Predicting results
- Justifying the conclusion
Suggesting alternative options to a problem. They are incapable of −
- Substituting human decision makers
- Possessing human capabilities
- Producing accurate output for inadequate knowledge base
- Refining their own knowledge
Q.30. What are components of Expert Systems in Artificial Intelligence?
The components of AI expert systems include −
- Knowledge Base
- Inference Engine
- User Interface
Q.31. What is user Interface?
Generally, ES users and ES itself uses User interface as a medium of interaction between users. Also, the user of the ES need not be necessarily an expert in Artificial Intelligence.
Although, at a particular recommendation, it explains how the ES has arrived. Hence, the explanation may appear in the following forms −
- Basically, the natural language displayed on a screen.
- Also, verbal narrations in natural language.
Further, listing of rule numbers displayed on the screen. The user interface makes it easy to trace the credibility of the deductions.
Q.32. What are expert Systems Limitations?
Basically, we have noticed that no technology can offer an easy and complete solution. Also, large systems are too costly. Although, they require significant development time and computer resources.
Also, ESs have their limitations which include −
- Limitations of the technology
- Difficult knowledge acquisition
- ES are difficult to maintain
- High development costs
Q.33. Name some expert System Technology?
It includes:
a. Expert System Development Environment
Basically, hardware and tools are included in it. They are −
- Minicomputers, workstations, mainframes.
- LISt Programming (LISP) and PROgrammation en LOGique (PROLOG).
- Large databases.
b. Tools
Generally, tools are used to reduce the effort and cost.
- Powerful editors and debugging tools with multi-windows.
- They provide rapid prototyping.
- Have Inbuilt definitions of a model, knowledge representation, and inference design.
Artificial Intelligence Interview Questions-Answers for freshers- Q. 25,26,27,29,30,31,32
Artificial Intelligence Interview Questions-Answers for Experienced- Q. 28,33
Q.34. What are benefits of Expert Systems?
a. Availability
Due to mass production of software, expert systems are easily available.
b. Less Production Cost
As production cost of an expert system is reasonable. Thus, it makes them affordable.
c. Speed
Generally, expert systems offer great speed. Also, reduce the amount of work that an individual puts in.
d. Less Error Rate
Generally, an error rate of the expert system is low in comparison to human errors.
e. Reduced danger
They can be used in any risky environments where humans cannot work with.
f. Permanence
The knowledge will last long indefinitely.
g. Multiple expertise
Generally, it can be designed to have knowledge of many experts.
h. Explanation
They are capable of explaining in detail the reasoning that led to a conclusion.
Q.35. What are applications of Expert System?
a. Design Domain
Basically, we use expert systems in designing of camera lens and automobile.
b. Monitoring Systems
Generally, in this data is compared with observed system
c. Process Control Systems
We have to control physical process based on monitoring
d. Knowledge Domain
Finding out faults in vehicles, computers
e. Finance Commerce
Also, an expert system is used to detect possible fraud.
Q.36. Give a brief introduction to robotics?
Basically, robots have their specific aim. As they manipulate the objects. For Example- by perceiving, picking, moving, modifying the physical properties of an object.
What are Robots?
Generally, robots are the artificial agents acting in the real world environment. Robotics is a branch of Artificial Intelligence. That is composed of Electrical, and Mechanical Engineering. Also, Computer Science for designing, construction, and application of robots.
Q.37. What are aspects of robotics?
- Basically, robots have mechanical construction. That is to form or shape designed to accomplish a particular task.
- Also, it contains electrical components. That is a use of power and control the machinery.
- Basically, it contains some level of a computer program. Also, it determines what, when and how a robot does something.
Q.38. What are components of robotics?
To construct a robot we need following parts−
a. Power Supply
Generally, robots are powered by batteries, solar power, hydraulic.
b. Actuators
Basically, we use this to convert energy into movement.
c. Electric motors (AC/DC)
Generally, we need this for the rotational movement.
d. Pneumatic Air Muscles
Basically, we can say that they contract almost 40% when the air is sucked in them.
e. Muscle Wires
Although, we have noticed that it contract by 5% when an electric current is passed through them.
f. Piezo Motors and Ultrasonic Motors
Basically, we use it for industrial robots.
g. Sensors
Generally, we use it in task environment as it provides information of real-time knowledge.
Q.39. What is a difference in Robot System and AI Programs?
Here is the difference between Artificial Intelligence and Robotics:
AI Programs
- Usually, we use to operate them in computer-simulated worlds.
- Generally, an input is given in the form of symbols and rules.
- Basically, to operate this we need general purpose computers.
Read about AI Applications.
Robots
- Generally, we use robots to operate in the real physical world.
- Basically, inputs are given in the form of the analog signal in the form of the speech waveform.
- Also, to operate this, special hardware with sensors and effectors are needed.
Q.40. What is computer vision?
Generally, it’s an A.I technology which robots can see. Also, play an important role in security, safety, and entertainment. Moreover, we use it to extract useful information from an array of images.
a. Hardware of Computer Vision System
This involves −
- Power supply
- Image acquisition device such as camera
- a processor
- a software
- A display device for monitoring the system
- Accessories such as camera stands, cables, and connectors
Q.41. What are Application Domains of Computer Vision?
Generally, there are various applications of computer vision:
- Agriculture
- Autonomous vehicles
- Biometrics
- Character recognition
- Forensics, security, and surveillance
- Industrial quality inspection
- Face recognition
- Gesture analysis
- Geoscience
- Medical imagery
- Pollution monitoring
- Process control
- Remote sensing
- Robotics
- Transport
Artificial Intelligence Interview Questions-Answers for freshers- Q. 33,34,35,37
Artificial Intelligence Interview Questions-Answers for Experienced- Q. 36,38,39,40,41
3. Conclusion
As a result, we have studied Artificial Intelligence Interview Questions-Answers. Also, we have covered all types of Artificial Intelligence Interview Questions-Answers. which are required for freshers as well as experienced. Furthermore, if you feel any query, feel free to ask in a comment section.
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