Artificial Intelligence Interview Questions And Answers
1. What Is Artificial Intelligence?
Answer: Artificial Intelligence is an area of computer science that emphasizes the creation of an intelligent machine that works and reacts like humans.
2. What are common uses and/or applications for AI1? What Is Artificial Intelligence?
Answer: Artificial Intelligence is an area of computer science that emphasizes the creation of an intelligent machine that works and reacts like humans.
Your answer here should show that you recognize the far-reaching and practical applications of AI, but your answer is up to you because your understanding of the AI field is what the interviewer is trying to ascertain. If possible, mention those uses most relevant to the potential employer. Possibilities include contract analysis, object detection, and classification for avoidance and/or navigation, image recognition, content distribution, predictive maintenance, data processing, automation of manual tasks or data-driven reporting.
3. What Are The Branches Of Ai1? What Is Artificial Intelligence?
Answer: Artificial Intelligence is an area of computer science that emphasizes the creation of an intelligent machine that works and reacts like humans.
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 conferencing 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 the 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 like 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.
4. What is supervised versus unsupervised learning?
Answer: Supervised learning is a machine learning process in which outputs are fed back into a computer for the software to learn from, for more accurate results the next time. With supervised learning, the “machine” receives initial training to start. In contrast, unsupervised learning means a computer will learn without initial training to base its learning on.
5. Where Can I Find Conference Information?
Answer: Georg Thimm maintains a webpage that lets you search for upcoming or past conferences in a variety of AI disciplines.
6. What Is Inheritable Knowledge?
Answer: It is a knowledge representation scheme in which knowledge is represented using objects, their attributes and the corresponding value of the attributes. The relation between different objects is defined using an “is a” property.
For example, if two entities “Adult male” and “Person” are represented as objects then the relation between the two is that Adult male “is a” person.
7. In speech recognition which model gives the probability of each word following each word?
Answer: The diagram model gives the probability of each word following each other word in speech recognition.
8. Which is the best way to go for the Game playing problem?
Answer: A heuristic approach is the best way to go for game playing problems, as it will use the technique based on intelligent guesswork. For example, Chess between humans and computers it will use brute force computation, looking at hundreds of thousands of positions.
9. I Am A Programmer Interested In Ai. I Am Writing A Game That Needs Ai. Where Do I Start?
Answer: It depends on what the game does. If it’s a two-player board game, look into the “Mini-max” search algorithm for games. In most commercial games, the AI is a combination of high-level scripts and low-level efficiently-coded, real-time, rule-based systems. Often, commercial games tend to use finite state machines for computer players. Recently, discrete Markov models have been used to simulate unpredictible human players (the buzzword compliant name being “fuzzy” finite state machines).
A recent popular game, “Black and White”, used machine learning techniques for the non-human controlled characters. Basic reinforcement learning, perceptrons, and decision trees were all parts of the learning system.
10. What Is An Agent?
Answer: A very misused term. Today, an agent seems to mean a stand-alone piece of AI-ish software that scours across the internet doing something “intelligent.” Russell and Norvig define it as “anything that can be viewed a perceiving its environment through sensors and acting upon that environment through effectors.” Several papers I’ve read treat it as ‘any program that operates on behalf of a human,’ similar to its use in the phrase ‘travel agent’. Marvin Minsky has yet another definition in the book “Society of Mind.” Minsky hypothesizes that a large number of seemingly-mindless agents can work together in a society to create an intelligent society of mind. Minsky theorizes that not only will this be the basis of computer intelligence, but it is also an explanation of how human intelligence works. Andrew Moore at Carnegie Mellon University once remarked that “The only proper use of the word ‘agent’ is when preceded by the words ‘travel’, ‘secret’, or ‘double’.”
11. Explain the difference between strong AI and weak AI?
Answer: 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 human intelligence can be incorporated into computers to make it more useful tools.
12. How Should Knowledge Be Represented To Be Used For An Ai Technique?
Answer:
Following are the requirements for knowledge to be used for an AI technique:
When two individual situations are represented, knowledge should provide generalization such that only common properties of both situations are represented rather than representing both situations individually
Knowledge should be represented such that it should be understood by the people who have provided it
Knowledge should be represented in a way that it can be easily modified
Knowledge should be represented such that it should still apply to one or more situations even if it is inaccurate or incomplete.
13. What Are The Techniques To Represent Knowledge?
Answer:
There are four techniques to represent knowledge:
Relational knowledge: In this representation, knowledge is represented as a set of relations, similar to relations that are used in the database
Inheritable knowledge: In this representation, knowledge is represented using objects, their attributes and the values of the attributes
Inferential knowledge: In this representation, knowledge is represented in the form of first-order predicate logic
Procedural knowledge: In this representation, knowledge is represented as a set of rules and a rule describes an action to be performed when a condition is met.
14. Give some disadvantages of Artificial Intelligence?
Answer:
a. High Cost Its creation requires huge costs as they are very complex machines. Also, repair and maintenance require huge costs.
b. No Replicating Humans As intelligence is believed to be a gift of nature. An ethical argument continues, whether human intelligence is to be replicated or not.
c. Lesser Jobs As we are aware that machines do routine and repeatable tasks much better than humans. Moreover, we use machines instead of humans. As to increase their profitability in businesses.
d. Lack of Personal Connections We can’t rely too much on these machines for educational oversights. That hurt learners more than help.
15. What are Educational Requirements for Career in Artificial Intelligence?
Answer: Various levels of math, including probability, statistics, algebra, calculus, logic, and algorithms.
Bayesian networking or graphical modeling, including neural nets.
Physics, engineering, and robotics.
Computer science, programming languages, and coding.
Cognitive science theory.
16. What are the applications of A.I?
Answer:
a. Natural Language Processing
It is possible to interact with the computer. Also, they understand only natural language which human use to spoke.
b. Gaming
In strategic games, AI plays a crucial role. Such as chess, poker, tic-tac-toe, etc., As applications present which integrate machine, software to impart reasoning and advising. They provide explanations and advice to the users.
c. Speech Recognition
Systems capable of hearing the language. And also their meanings while human talks to it.
17. Explain the Goal of Artificial Intelligence?
Answer: To Create Expert Systems it is the type of system in which the system exhibits intelligent behavior, and advice its users. b. To Implement Human Intelligence in Machines It is the way of creating systems that understand, think, learn, and behave like humans.
18. Explain types of Artificial Intelligence?
Answer:
There are two types of artificial intelligence such as:
a. Strong artificial intelligence
It deals with the creation of real intelligence artificially. Also, strong AI believes that machines can be made sentient.
There are two types of strong AI: Human-like AI In this computer program thinks and reasons for the level of a human being. Non-human-like AI In this computer program develops a non-human way of thinking and reasoning.
b. Weak artificial intelligence
As a result, it doesn’t believe creating human-level intelligence in machines is possible. Although, AI techniques can be developed to solve many real-life problems.
19. What is the Breadth-First Search Algorithm?
Answer: Basically, we have to start searching for the root node. And continue through neighboring nodes first. Further, it moves towards the next level of nodes. Moreover, the solution is found, it generates one tree at a time. This search can be implemented using a FIFO queue data structure. This method provides the shortest path to the solution. FIFO(First in First Out). If the branching factor (average number of child nodes for a given node) = b and depth = d, the number of nodes at level d = bd. The total no of nodes created in the worst case is b + b2 + b3 + … + bd.
20. What is the future of Artificial intelligence?
Answer: Artificial Intelligence is used by one another after the company for its benefits. Also, it’s a fact that artificial intelligence is reached in our day-to-day life. Moreover, with breakneck speed. Based on this information, arises a new question: Is it possible that artificial Intelligence outperforms human performance? If yes, then is it happens and how much does it take? Only when Artificial Intelligence can do a job better than humans.
21. What is AI according to the survey results?
Answer:
machines are predicted to be better than humans in translating languages;
working in the retail sector, and can completely outperform humans by 2060.
As a result, MI researchers believed that AI will become better than humans in the next 40-year time frame.
To build AI smarter, companies have already acquired around 34 AI startups. These companies are reinforcing their leads in the world of Artificial Intelligence.
In every sphere of life, AI is present. We use AI to organize big data into different patterns and structures. Also, patterns help in a neural network, machine learning, and data analytics.
From the 80’s to now, Artificial intelligence is now part of our everyday lives, it’s very hard to believe. Moreover, it is becoming more intelligent and accepted every day. Also, with lots of opportunities for business.
22. What Does Partial Order Or Planning Involve?
Answer:
In partial-order planning, rather than searching over the possible situation it involves searching over the space of possible plans. The idea is to construct a planned piece by piece.
23. What is artificial intelligence Neural Networks?
Answer: Artificial intelligence Neural Networks can model mathematically the way the biological brain works, allowing the machine to think and learn the same way humans do- making them capable of recognizing things like speech, objects and animals like we do.
24. What Is Alternate, Artificial, Compound And Natural Key?
Answer:
Alternate Key: Excluding primary keys, all candidate keys are known as Alternate Keys.
Artificial Key: If no obvious key either stands alone or compound is available, then the last resort is to, simply create a key, by assigning a number to each record or occurrence. This is known as an artificial key.
Compound Key: When there is no single data element that uniquely defines the occurrence within a construct, then integrating multiple elements to create a unique identifier for the construct is known as Compound Key. (company)
Natural Key: Natural key is one of the data element that is stored within a construct, and which is utilized as the primary key.
25. Mention the difference between statistical AI and Classical AI?
Answer:
Statistical AI is more concerned with “inductive” thought like given a set of patterns, 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.
26. Mention the difference between breadth first search and best first search in artificial intelligence?
Answer: These are the two strategies that are quite similar. In the best first search, we expand the nodes following the evaluation function. While in breadth first search a node is expanded following the cost function of the parent node.
27. What are the steps to ensure the business stays relevant to the AI revolution?
Answer: a. A finger on the pulse Maybe the time is going on it’s not right for your business to harness the value of AI. Although, it doesn’t mean you should stop keeping up like others are using AI. Only reading IT journal trade is a good place to start. Rather start focusing on how businesses are leveraging AI.
b. Piggyback on the innovators To implement AI, there are so many resources present from an industry that will help you. For example, Google has developed a machine learning system, TensorFlow. That was released as open source software.
c. Brainstorm potential uses with your team If you want, a team must be engaged in encouraging in the areas of business, AI could be deployed. Data-heavy, inefficient are processes that are likely to benefit. Moreover, find where these exist.
d. Start small and focus on creating real value It’s not mandatory to move forward for the sake only. Rather, it’s necessary to focus on objectives and start finding the best solution for it. Moreover, it means finding a specific process to run an AI pilot. Also, see how it goes, learn and build from there.
e. Prepare the ground Before, to maximize the value of AI, its good to ensure your current process. I.e working in the best possible way.
28. What is the Bidirectional Search Algorithm?
Answer: Basically, starts searches forward from an initial state and backward from the goal state. As till both meet to identify a common state. Moreover, the initial state path is concatenated with the goal state inverse path. Each search is done only up to half of the total path.
29. While creating Bayesian Network what is the consequence between a node and its predecessor?
Answer: While creating Bayesian Network, the consequence between a node and its predecessors is that a node can be conditionally independent of its predecessors.
30. What are frames and scripts in “Artificial Intelligence”?
Answer: Frames are a variant of semantic networks which is one of the popular ways of presenting non-procedural knowledge in an expert system. A frame which is an artificial data structure is used to divide knowledge into substructure by representing “stereotyped situations’. Scripts are similar to frames, except the values that fill the slots must be ordered. Scripts are used in natural language understanding systems to organize a knowledge base in terms of the situation that the system should understand.
31. Which process makes different logical expression looks identical?
Answer: ‘Unification’ process makes different logical expressions identical. Lifted inferences require finding a substitute that can make a different expression looks identical. This process is called unification.
32. What Has Ai Accomplished?
Answer: Quite a bit. In ‘Computing machinery and intelligence.’, Alan Turing, one of the founders of computer science, made the claim that by the year 2000, computers would be able to pass the Turing test at a reasonably sophisticated level, in particular, that the average interrogator would not be able to identify the computer correctly more than 70 percent of the time after a five minute conversation. AI hasn’t quite lived upto Turing’s claims, but quite a bit of progress has been made, including:
Deployed speech dialog systems by firms like IBM, Dragon and Lernout & Hauspie
Financial software, which is used by banks to scan credit card transactions for unusual patterns that might signal fraud. One piece of software is estimated to save banks $500 million annually.
Applications of expert systems/case-based reasoning: a computerized Leukemia diagnosis system did a better job checking for blood disorders than human experts.
Machine translation for Environment Canada: software developed in the 1970s translated natural language weather forecasts between English and French. Purportedly stil in use.
33. What Are The Various Areas Where Ai (artificial Intelligence) Can Be Used?
Answer: Artificial Intelligence can be used in many areas like Computing, Speech recognition, Bio-informatics, Humanoid robot, Computer software, Space and Aeronautics, etc.
34. In Artificial Intelligence, what do semantic analyses used for?
Answer:
In Artificial Intelligence, to extract the meaning from the group of sentences semantic analysis is used.
35. What is the Iterative Deepening Depth-First Search Algorithm?
Answer: 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 the searching process until we find a solution. We have to generate nodes to single nodes are created. Also, it saves only a 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.
36. What Is Neural Network In Artificial Intelligence?
Answer: In artificial intelligence, the neural network is an emulation of a biological neural system, which receives the data, processes the data and gives the output based on the algorithm and empirical data.
37. What are jobs in artificial intelligence?
Answer:
Computational philosopher: To ensure human-aligned ethics are embedded in AI algorithms
Robot personality designer
Robot obedience trainer
Autonomous vehicle infrastructure designer: New road and traffic signs to be read by computer
Algorithm trainers include the growing army of so-called “click workers”. That, helps algorithms learn to recognize images or analyze sentiment, for instance.
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