All Interviews

Top 23 Artificial Intelligence Interview Questions and Answers

26/Aug/2021 | 8 minutes to read

ai-ml

Here is a List of essential Artificial Intelligence Interview Questions and Answers for Freshers and mid level of Experienced Professionals. All answers for these Artificial Intelligence questions are explained in a simple and easiest way. These basic, advanced and latest Artificial Intelligence questions will help you to clear your next Job interview.

---

Artificial Intelligence Interview Questions and Answers

These questions are targeted for AI (Artificial Intelligence) professionals. You must know the answers of these frequently asked Artificial Intelligence interview questions to clear an interview. We have also a separate document for Machine Learning interview questions.

---

1. What is Artificial Intelligence(AI)?

Artificial Intelligence or AI is the field or branch of computer science that aims to create intelligent machines that behave or work and react like humans. AI is the study of cognitive functions of the human brain and tries to implement the same on machines.
Artificial Intelligence allows you to build such systems, computers, computer controlled robots and softwares which can mimic the problem solving and decision making capabilities of the human mind. For more visit What is AI?

2. List some common Applications of AI? Or give some examples of AI.

Artificial Intelligence or AI is used in many fields as below.

• Speech Recognition
• Sentiment Analysis
• NLP or Natural Language Processing
• Chatbots
• Computing
• Robotics
• Machine Perception
• Many others

3. What are the latest technologies used in Artificial Intelligence AI?

There are many Artificial intelligence technologies, some of them we are listing here.

• NLP or Natural Language Processing
• Machine Learning
• Speech Recognition
• RPA (Robotic Process Automation)
• Image Recognition
• Virtual Agents
• Biometrics
• Decision Management
• Deep Learning Platforms
• Content Creation
• Emotion Recognition
• There are many others also.

4. What are the most popular AI programming Languages?

These below are the most popular AI programming Languages used by developers to satisfy different needs.

• Python
• C++
• Java
• LISP
• Prolog

5. What is the difference between Strong AI and Weak AI?

AI is the capability of machines to perform the tasks just like humans.

• Weak AI is the artificial intelligence which implements a limited part of mind. Machines can not carry the tasks on their own, they need human interference. iPhone's Siri and Amazon's Alexa are examples of weak AI.
  Weak AI has less complex algorithms and all actions in this are preprogrammed by humans like in Siri.
• Strong AI is the artificial intelligence that can perform the tasks on their own just like humans do. AI in gamings like Poker AI is an example of strong AI that can teach itself to adapt the skills of a human opponent.
  Strong AI has complex algorithms that help it to act in different situations. Strong AI has unpredictable responses just like humans as you can not judge the response of a person when you talk to him.

6. What are the subfields of AI? Or how AI, Machine learning and deep learning are related?

Machine learning and deep learning are the subfields of AI. Artificial Intelligence (AI) contains many subfields as below.

• Machine Learning is a subfield of AI that trains the machines how to learn. Machine learning is the study of data models and algorithms that software systems use to perform some tasks without explicit instructions relying on the idea that systems can learn from data, identify patterns and make decisions without human intervention or minimal human intervention.
• A neural network - An interconnected system or circuit of neurons makes a neural network. It could be either organic or artificial in nature. A neural network is a software or hardware that performs the tasks similar to human brain neurons. A neural network is a series of algorithms to solve various business problems such as risk management, customer forecasting and data validation in a similar way as human brain neurons do.
• Deep learning is the subset of machine learning or is a vast family of machine learning methods that has capability of unsupervised learning from unstructured data. Deep learning is well suited for big data for knowledge discovery and knowledge based applications.
• Computer vision is the subfield of artificial intelligence that deals with how computers or systems understand the information from images or videos for their proper understanding to predict the visual input similar to the human brain. It's AI technology that makes computers understand image or video inputs to perform other tasks automation, for example: driver less car testing, livestock etc.
• NLP (Natural Language Processing) is the subfield of AI, computer science or information engineering that deals with how to program computers to process, understand and analyze large amounts of natural language data. NLP is the automation process of manipulating natural languages by softwares.

7. How will you differentiate Artificial Intelligence, Machine learning and Deep learning?

AI is at a broader level and all others are the subfields of AI. Please refer to my above questions's (6th) answer.

• AI is the subset of Data Science or the branch of computer science with the aim to create intelligent machines that behave like humans.
• Machine learning is the subfield of AI that trains the machines how to learn and make decisions without programming so that they can solve the problems.
• Deep Learning is the subset of machine learning with the capability of unsupervised learning from unstructured data with the aim of building neural networks for automatic discovering patterns for feature detection.

8. What is the Expert System in AI? Explain its characteristics?

Expert System is a computer program or system that has the ability similar to human experts to make decisions and judgment. Expert system emulates the if-then pattern rather than procedural programming. Expert systems or programs are used to solve complex problems by capturing the knowledge from the knowledge base. All knowledge in the knowledge base is stored by human experts and Expert Systems are used by Non Expert humans to solve complex problems.
There are following characteristics of the Expert System.

• Expert Systems helps to spread the expertise of a human to many.
• Expert Systems provide more efficient solutions as the knowledge base contains the information from many human experts rather than single human.
• Cost is reduced with expert systems as less cost is involved as compared to consultants for problem solving.
• New facts can be reduced based on existing knowledge base facts so expert systems can solve complex problems.
• The Expert system is a permanent computer system as human experts are perishable or limited in life.

9. What are the limitations of an Expert System in AI?

Expert system is permanent and solves complex problems but it has some limitations as below.

• Expert system can not give correct results from less knowledge base data.
• An Expert system can not provide decision making like humans.
• It requires a lot of training to give correct results.

10. What are the advantages and disadvantages of an Expert System in AI?

Expert Systems in AI has certain advantages and disadvantages as follows.

• Expert System Advantage -
• It gives fast results with less chances of errors.
• The Expert system comes with reduced cost.
• Expert systems have no effect on emotions like humans.
• It's a permanent solution not perishable.

• Expert System Disadvantage -
• Expert system does not care about emotions and does not have any common sense.
• The Expert system makes decisions fast but is not able to explain the reason behind it.
• does not support self learning, you need to update manually.

11. What is a fuzzy logic in AI (Artificial Intelligence)?

Fuzzy logic can be defined as a concept of reasoning similar to that of humans making decisions based on imprecise and non-numerical values. Fuzzy logic is the capability of making decisions similar to humans and includes possible combinations of "YES" and "NO" while making decisions.

12. What are the different types of Artificial Intelligence?

AI provides the capability to develop machines that will act like humans. Based on the degree to which intelligent machines can be created is used as a criteria to determine the classification of AI. So based on this criteria AI has four types.

• Reactive Machines - These are the most basic AI systems with limited capability. These systems do not have past stored memories and perform actions based on the current set of inputs. Alpha Go is a program which is based on reactive machines.
• Limited Memory - These systems have the capability of reactive machines and addition to memory storage for a limited period of time. Self driving Cars are the example of this AI system. Self driving cars can store speed, distance from other cars etc.
• Theory of Mind - Above two types of AI have been found and in use but Theory of Mind AI is the next level of AI that is available as concept only. Researchers are engaged on this. Theory of mind AI will act like humans means capability of understanding beliefs, emotions and thought process.
• Self-aware - This AI concept is completely hypothetical. These AI systems will be much more intelligent then humans and will have their own consciousness, belief, emotions and thought process. These AI systems will come in the next decades.

An Alternate classification that is more generally used in Tech industries or based on capability AI has 3 types.

• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificial Super Intelligence (ASI)

For more you can refer AI Types

13. Explain the AI Neural Networks.

Artificial neurons are similar to human brain neurons which are called biological neural networks. Every artificial neuron is connected to another neuron, so when an artificial neuron receives the signals, processes it and passes it to the next connected neuron.
In fact Deep learning is the new name for the Neural Networks approach of AI. This Artificial Neural Networks is capable of learning unsupervised from unlabeled and unstructured data.

14. Describe the Intelligent Agents.

15. What is the Turing Test?

16. What's a Transfer Flow?

17. What is Game Theory in Artificial Intelligence?

18. What's Inverse Game Theory in AI?

19. Explain the AIOPs.

20. What are the Debunking Misconceptions About AI or AI Myths Debunked?

Some General Interview Questions for Artificial Intelligence

1. How much will you rate yourself in Artificial Intelligence?

When you attend an interview, Interviewer may ask you to rate yourself in a specific Technology like Artificial Intelligence, So It's depend on your knowledge and work experience in Artificial Intelligence.

2. What challenges did you face while working on Artificial Intelligence?

This question may be specific to your technology and completely depends on your past work experience. So you need to just explain the challenges you faced related to Artificial Intelligence in your Project.

3. What was your role in the last Project related to Artificial Intelligence?

It's based on your role and responsibilities assigned to you and what functionality you implemented using Artificial Intelligence in your project. This question is generally asked in every interview.

4. How much experience do you have in Artificial Intelligence?

Here you can tell about your overall work experience on Artificial Intelligence.

5. Have you done any Artificial Intelligence Certification or Training?

It depends on the candidate whether you have done any Artificial Intelligence training or certification. Certifications or training are not essential but good to have.

Conclusion

We have covered some frequently asked Artificial Intelligence Interview Questions and Answers to help you for your Interview. All these Essential Artificial Intelligence Interview Questions are targeted for mid level of experienced Professionals and freshers.
While attending any Artificial Intelligence Interview if you face any difficulty to answer any question please write to us at info@qfles.com. Our IT Expert team will find the best answer and will update on the portal. In case we find any new Artificial Intelligence questions, we will update the same here.