Artificial Intelligence Interview Questions – Set 21

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What are roles in AI career?

  • Software analysts and developers.
  • Computer scientists and computer engineers.
  • Algorithm specialists.
  • Research scientists and engineering consultants.
  • Mechanical engineers and maintenance technicians.
  • Manufacturing and electrical engineers.
  • Surgical technicians working with robotic tools.
  • Military and aviation electricians working with flight simulators, drones, and armaments.

Explain the objective and related terminology used in the search algorithms of AI?

This is the most popular Artificial Intelligence Interview Questions asked in an interview. Searching is the universal techniques used in AI problem techniques. This algorithm is used to search a particular position. Every search terminology has some components.

Problem space: this is the environment in which the search takes place.
Problem Instance: it’s a result of the Initial State + Goal state.
Problem Space Graph: This is used to represent a problem state.
The depth of a problem: Here we can define the length of the shortest path.
Space Complexity: We can calculate this by the maximum number of nodes that are stored in memory.
Time Complexity: It is defined as the maximum number of nodes that are created.
Admissibility: This is the property of the algorithms that are used to find the optimal solutions.
Branching Factors: This can be calculated by the average number of child nodes in the problem space graph.
Depth: it is the length of the shortest path from inception to the goal state.
Here are some of the search algorithms

  • Breadth-first search
  • Depth-first search
  • Bidirectional search
  • Uniform cost search

What is the philosophy behind Artificial Intelligence?

As if we see the powers that are exploiting the power of computer system, the curiosity of human lead him to wonder, “Can a machine think and behave like humans do?” Thus, AI was started with the intention of creating similar intelligence in machines. Also, that we find and regard high in humans.

What are the different areas where AI has a great impact?

Following are some areas where AI has a great impact:

  • Autonomous Transportation
  • Education-system powered by AI.
  • Healthcare
  • Predictive Policing
  • Space Exploration
  • Entertainment, etc.

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.

What is the Uniform Cost Search Algorithm?

Basically, it performs sorting in increasing the cost of the path to a node. Also, always expands the least cost node. Although, it is identical to Breadth-First search if each transition has the same cost. It explores paths in the increasing order of cost.

List some AI Applications and Common uses.

AI-powered tools are applied in various spheres of the economy, including:
Natural Language Processing

  • Chatbots
  • Sentiment analysis
  • Sales prediction
  • Self-driving cars
  • Facial expression recognition
  • Image tagging

What are the different components of the Expert System?

An expert system mainly contains three components:

  • User Interface: It enables a user to interact or communicate with the expert system to find the solution for a problem.
  • Inference Engine: It is called the main processing unit or brain of the expert system. It applies different inference rules to the knowledge base to draw a conclusion from it. The system extracts the information from the KB with the help of an inference engine.
  • Knowledge Base: The knowledge base is a type of storage area that stores the domain-specific and high-quality knowledge.

How aware you think you are in terms of using AI enabled devices and services?

Like I said that AI is everywhere and currently has a deep impact on our surroundings, we can see AI touch in the below listed things

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.