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Artificial Intelligence Interview Questions and Answers

Artificial Intelligence Interview Questions and Answers

Question - 1 : - What is Artificial Intelligence?

Answer - 1 : -

Artificial Intelligence is the field of computer science concerned with building intelligent machines or computer systems, capable of simulating human intelligence. The machines created using Artificial Intelligence can work and react like humans without human intervention. Speech Recognition, Customer service, Recommendation Engine, Natural Language Processing (NLP) are some of the applications of Artificial Intelligence.

Since its inception, AI research has explored and rejected a variety of methodologies, including mimicking the brain, modelling human problem-solving, formal logic, massive knowledge libraries, and imitating animal behavior. Highly mathematical-statistical machine learning dominated the subject in the first decades of the twenty-first century. The many sub-fields of AI research are based on specific aims and the application of certain techniques. Reasoning, knowledge representation, planning, learning, natural language processing, sensing, and the ability to move and manipulate objects are all conventional AI research aims. One of the field's long-term goals is general intelligence (the capacity to solve any problem).  AI researchers have adapted and integrated a wide range of problem-solving strategies to handle these issues, including search and mathematical optimization, formal logic, artificial neural networks, and statistics, probability, and economics methodologies. AI also makes use of various fields like psychology, linguistics, philosophy.

Question - 2 : - What are some real-life applications of Artificial Intelligence?

Answer - 2 : -

  • Social Media: The most common use of Artificial Intelligence in social media is facial detection and verification. Artificial Intelligence, along with machine learning, is also used to design your social media feed.
  • Personalized online shopping: Shopping sites use AI-powered algorithms to curate the list of buying recommendations for users. They use data like users' search history and recent orders to create a list of suggestions that users might like.
  • Agriculture: Technologies, especially Artificial Intelligence embedded systems, help farmers protect their crops from various adversities like weather, weeds, pests, and changing prices.
  • Smart cars: Smart cars are another one of the real-life applications of AI. Artificial intelligence collects data from a car’s radar, camera, and GPS to operate the vehicle when the autopilot mode is on.
  • Healthcare: Artificial Intelligence has come out as a reliable friend of doctors. From intelligent testing to medical recommendations, they assist medical professionals in every possible way.

Question - 3 : - What are different platforms for Artificial Intelligence (AI) development?

Answer - 3 : -

Some different software platforms for AI development are-

  • Amazon AI services
  • Tensorflow
  • Google AI services
  • Microsoft Azure AI platform
  • Infosys Nia
  • IBM Watson
  • H2O
  • Polyaxon
  • PredictionIO

Question - 4 : - What are the programming languages used for Artificial Intelligence?

Answer - 4 : -

Python, LISP, Java, C++, R are some of the programming languages used for Artificial Intelligence.

Question - 5 : - What is the future of Artificial Intelligence?

Answer - 5 : -

Artificial Intelligence has affected many humans and almost every industry, and it is expected to continue to do so. Artificial Intelligence has been the main driver of emerging technologies like the Internet of Things, big data, and robotics. AI can harness the power of a massive amount of data and make an optimal decision in a fraction of seconds, which is almost impossible for a normal human. AI is leading areas that are important for mankind such as cancer research, cutting-edge climate change technologies, smart cars, and space exploration. It has taken the center stage of innovation and development of computing, and it is not ceding the stage in the foreseeable future. Artificial Intelligence is going to impact the world more than anything in the history of mankind.

Question - 6 : - What is the difference between Strong Artificial Intelligence and Weak Artificial Intelligence?

Answer - 6 : -

Weak AI

Strong AI

Narrow application, with very limited scope

Widely applied, with vast scope

Good at specific tasks

Incredible human-level intelligence

Uses supervised and unsupervised learning to process data

Uses clustering and association to process data

E.g., Siri, Alexa, etc.

E.g., Advanced Robotics

Question - 7 : - List the programming languages used in AI.

Answer - 7 : -

  • Python
  • R
  • Lisp
  • Prolog
  • Java

Question - 8 : - What are the Examples of AI in real life?

Answer - 8 : -

Robo-readers for Grading:
Many schools, colleges, and institutions are now using AI applications to grade essay questions and assignments on Massive Open Online Courses(MOOCs). In the era of technology, where education is rapidly shifting towards online learning, MOOCs have become a new norm of education. Thousands of assignments are and essay questions are submitted on these platforms on the daily basis,  and grading them by hand is next to impossible. 

Robo-readers are used to grade essay questions and assignments based on certain parameters acquired from huge data sets. Thousands of hand-scored essays were fed into the deep Neural Networks of these AI systems to pick up the features of good writing assignments. So, the AI system uses previous results to evaluate the present data. 

Online Recommendation Systems
Online recommendations Systems study customer behavior by analyzing their keywords, websites, and the content they watch on the internet. From e-commerce to Social Media websites, everyone is using these recommendation systems to provide a better customer experience. 

There are two ways to produce a recommendation list for a customer, collaborative and content-based filtering. In collaborative filtering, the system analyzes the past decisions made by the customer and suggests items that he/she might find interesting. Whereas, content-based filtering finds discrete characteristics of the product or service and suggests similar products and deals that might excite the user. The same process goes for social media apps and other websites. 

Navigation and Travel
Google Maps, GPS, and Autopilot on Airplanes are some of the best examples of AI in Navigation and travel. Machine Learning algorithms like Dijkstra’s algorithm are used to find the shortest possible route between two points on the map. However, certain factors are also taken into account including traffic and road blockage to find an optimal route. 

Fraud Detection
Machine Learning models process large amounts of banking data and check if there is any suspicious activity or anomalies in the customer transactions. AI applications proved to be more effective than humans in recognizing fraud patterns as they were trained with historical data with millions of transactions. 

Autonomous Vehicles 
Human error is responsible for more than 90% of accidents happening on the road every year. A technical failure in a vehicle, Roads, and other factors has little contribution to fatal accidents. Autonomous vehicles can reduce these fatal accidents by 90%. Although Self-driving systems require a person to supervise the action and take control of the vehicle in case of emergency, they prove to be very effective when driving on an open highway or parking the vehicle. Also, advancement in technology will further improve the ability to drive in complex situations using high-end AI models and sensors like LIDAR. 

Question - 9 : - What is ANN?

Answer - 9 : -

Artificial Neural Network (ANN) is a computational model based on the structure of the Biological Neural Network(BNN). The human brain has billions of neurons that collect, process the information, and drive meaningful results out of it. The neurons use electro-chemical signals to communicate and pass the information to other neurons. Similarly, ANN consists of artificial neurons called nodes connected with other nodes forming a complex relationship between the output and the input. 

There are three layers in the Artificial Neural Network:

  • Input Layer:  The input layer has neurons that take the input from external sources like files, data sets, images, videos, and sensors. This part of the Neural Network doesn’t perform any computation.  It only transfers the data from the outside world to the Neural Network
  • Hidden Layer: The hidden layer receives the data from the input layer and uses it to derive results and train several Machine Learning models. The layer can be further divided into sub-layers that extract features, make decisions, connect with other sources, and predict future actions based on the events that happened. 
  • Output layer: After processing, the data is transferred to the output layer for delivering it to the outside environment. 

Question - 10 : - What is an expert system? What are the characteristics of an expert system?

Answer - 10 : -

An expert system is an Artificial Intelligence program that has expert-level knowledge about a specific area and how to utilize its information to react appropriately. These systems have the expertise to substitute a human expert. Their characteristics include:

  • High performance
  • Adequate response time
  • Reliability
  • Understandability

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