Many people get scared of interviews in the tech sector. But if you do sufficient preparation, you don’t have to be afraid of anything. How does one prepare for a technical interview?
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Top Artificial Intelligence Interview Questions and Answers
Q.1- What do you understand about Artificial Intelligence?
In Artificial Intelligence, you study the cognitive functions of the human brain and try to replicate them on a system (or machine). It’s a branch of computer science and has applications in many industries and areas. You can also say that Artificial Intelligence focuses on creating intelligent machines that perform functions like humans.
Q.2- Name some areas which can benefit from Artificial Intelligence (AI).
Artificial Intelligence is useful in many industries. Computer science, software, robotics, speech recognition, aeronautics, game development, bioinformatics, and many other areas are using Artificial Intelligence to make.
Q.3- Can you distinguish between Weak AI and Strong AI?
There are many differences between Weak Artificial Intelligence and Strong Artificial Intelligence. Weak AI has minimal application and doesn’t have much scope in comparison to strong AI. The former is useful for performing specific tasks, but the latter can match human-like Intelligence.
Another difference between the two is the method of processing data. Weak AI uses unsupervised and supervised learning for processing data. On the other hand, strong AI uses association and clustering for this purpose.
Q.4- What programming languages do you use in AI?
The prominent programming languages we use in AI are Lisp, Python, R, Java, and Prolog.
Q.5- What do you mean by an expert system? What are its qualities?
An expert system is an AI-based program that has a lot of knowledge (expert-level) of a particular field. This program can use its expertise to solve real problems as well. Expert systems are capable of replacing human experts in their areas.
The qualities of an AI expert system are:
Q.6- What is A* algorithm search?
When you want to find the best route between two nodes, you will use an A* algorithm search. Its purpose is to traverse a graph or find a path for this purpose.
Q.7- What is a Turing Test? Explain.
A Turing test allows you to check your machine’s Intelligence in comparison to human Intelligence. In a Turing test, a computer would challenge human Intelligence, and if it passes the test, only then can you term it as intelligent. Even a smart machine might not be able to replicate humans also though it passes the test.
Q.8- What are depth-first search algorithms?
A depth-first search is a kind of algorithm which searches graph or tree data structures. It starts at the root node and searches as far as possible along every branch before it performs backtracking. It is based on LIFO. And the order of nodes in DFS algorithms is different from that of BFS algorithms. The system stores the path in every iteration linearly and requires space for the same.
Q.9- What are iterative deepening depth-first search algorithms?
In iterative deepening DFS algorithms, the search process of level 1 and 2 takes place. It continues the exploration until it finds the solution. It generates nodes until it finds the goal node and saves the stack of nodes it had created.
Q.10- Explain a bidirectional search algorithm. What is it?
A bidirectional search algorithm runs two simultaneous searches. The first go forward from the initial state, and the second goes backward from the goal state. They both meet at a common point, and that’s when the search ends—the goal state links with the initial state in a reverse manner.
Q.11- How would you explain a uniform cost search algorithm?
In a uniform cost search algorithm, you start from the initial state and go to the neighbouring states to choose the ‘least costly’ state. From there, you’ll select the next least costly state from the unvisited neighbouring states and the visited states. You’d keep looking for the goal state in this manner, and even if you do, you’ll look for other potential states. If every iteration of a breadth-first search algorithm had the same cost, it would become a uniform cost search algorithm.
Q.12- What are breadth-first search algorithms?
A BFS (breadth-first search) algorithm starts its search from the root node, then to its adjacent nodes, and keeps going to the next group of nodes until it finds the arrangement. You can create a tree until you find the arrangement. You can use it through the FIFO data structure, so you’ll get to see the shortest solution as well.
Q.13- What is the difference between Classical Artificial Intelligence and Statistical Artificial Intelligence?
Classical AI focuses on deductive thought, such as a group of constraints. On the other hand, Statistical AI focuses on inductive thought like a pattern or trend.
Q.14- What do you understand by fuzzy logic?
Fuzzy logic is a method of encoding human learning for AI. It imitates the decision making process of humans through IF-THEN instances and the digital values of YES and NO. It is based on degrees of truth. Dr. Lotfi Zadeh of the University of California at Berkeley was the first person to put forth the idea of fuzzy logic.
Q.15- What do you know about FOPL?
It’s one of the critical AI interview questions, so be sure to prepare it. FOPL stands for First-Order Predicate Logic. It’s a collection of formal systems, and each statement has a subject and a predicate. A predicate can have only one subject, and it has the ability to modify the subject.
Q.16- What is the relationship between AI and game theory?
Game Theory is a specialized branch of mathematics that deals with opposing players trying to achieve a particular set of goals. It’s about choosing from a group of rational choices when you have multiple agents. Experts use this algorithm in AI when they have various agents in a problem.
Q.17- Can you state some applications of fuzzy logic?
Fuzzy logic finds applications in multiple industries. Subway systems, uncrewed vehicles, air conditioners, vacuum cleaners, project risk assessment, and facial pattern recognition are just some of the areas which use fuzzy logic.
Q.18- What is Machine Learning?
Machine learning (ML) is the study of algorithms and models, which computers use for performing specific tasks without having particular instructions. It is a subset of artificial Intelligence and enables a machine to learn from its experience. In ML, computers can access data and use it to advance their knowledge of the problem.
You will get more Familiar with this by going through Machine Learning Interview Questions.
Q.19- What is the difference between abductive, deductive, and inductive machine learning?
Abductive machine learning is when you derive conclusions according to different instances. Its basis is deep neural networks. In deductive machine learning, you first obtain the result and improve it according to your past results. The machine learning algorithm, in this case, uses a decision tree.
Inductive machine learning learns from a group of instances and draws its conclusion accordingly. It uses KNN, SVM, and other Statistical machine learning algorithms.
Q.20- What do you understand by Deep Learning?
Deep Learning is a subset of Machine Learning. It has neural networks that can perform unsupervised learning from unstructured data. They learn through representation learning, and it could be unsupervised, supervised, or semi-supervised.
In simple words, deep learning is a technique of machine learning that teaches computer systems to do activities which humans can do naturally. An example of deep learning is uncrewed cars and how they can recognize stop signs on the road.
Q.21- What is an agent in artificial Intelligence?
In Artificial Intelligence, you study the relationship between an agent and its environment. Those agents have sensors that allow them to understand (sense) their settings. They also have actuators for acting on the environment. They have specified goals, and they can learn and use their knowledge to achieve their goals.
Q.22- What is a Partial-Order Plan?
When a plan specifies all the actions you need to perform but specifies the order of the steps only when necessary, it’s called a partial-order plan.
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Preparing Artificial Intelligence interview questions can be exhaustive. With the help of this list, you shouldn’t have any problems with the preparation.
Make sure that you don’t stress too much about the interview. Go through your prepared notes, read these questionnaires, and have confidence in yourself.
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How can artificial intelligence help businesses in building better customer relations?
Businesses can develop personalized messaging for their clients by using artificial intelligence and natural language processing to better understand their problems and needs. Furthermore, AI-powered solutions assist in the rapid response to client enquiries and concerns, resulting in improved customer relations. AI solutions can also assist customer support representatives feel less stressed, resulting in increased productivity.
What are the requirements for getting an artificial intelligence job?
Artificial intelligence is essentially a research field that aids in the transmission of human behavior to computers. Thus, having good knowledge of computer science is a must. So, in terms of educational requirements, you should have a major in computer science, statistics, or engineering with a specialization in computers. In terms of skills, you should have a basic knowledge of programming languages and, most importantly, a keen interest in learning how different AI algorithms work.
Is mathematics required in artificial intelligence?
Linear algebra is used both in machine learning and artificial intelligence. Also, concepts of statistics are used for building statistical models and analyzing the data well. Basic calculus is also required to comprehend different AI approaches. Thus, basic knowledge of mathematical concepts is required if you want to do well in artificial intelligence. However, you do not have to be a pro at it; just understand the basics and you are good to go.