Artificial Intelligence MCQ
Total Questions: 100
a) Artificial Intelligence
b) Automated Instruction
c) Artificial Interaction
d) Adaptive Intelligence
a) Supervised learning
b) Social learning
c) Biological learning
d) Contextual learning
a) To enable computers to understand human language
b) To create graphics
c) To improve database management
d) To enhance hardware performance
a) Speech recognition
b) File compression
c) Data storage
d) Web browsing
a) A computational model inspired by the human brain
b) A social network platform
c) A type of software
d) A hardware device
a) Convolutional Neural Networks (CNN)
b) Reinforcement learning
c) Genetic algorithms
d) Decision trees
a) To determine if a machine exhibits human-like intelligence
b) To measure computer performance
c) To test network security
d) To evaluate software quality
a) It is designed for a specific task
b) It can perform any intellectual task
c) It has self-awareness
d) It can think independently
a) A subset of machine learning involving neural networks with many layers
b) A type of unsupervised learning
c) A method for data encryption
d) A hardware requirement for AI
a) Learning based on rewards and punishments
b) Learning from examples
c) Learning by imitation
d) Learning from mistakes
a) To simulate conversation with users
b) To store data
c) To analyze data
d) To improve graphics
a) Python
b) JavaScript
c) HTML
d) CSS
a) When a model learns too much detail and noise from the training data
b) When a model is too simple
c) When a model is too complex
d) When a model is not trained enough
a) Predicting patient outcomes
b) Storing patient data
c) Managing hospital finances
d) Scheduling appointments
a) To enable computers to interpret and understand visual information
b) To enhance audio quality
c) To improve text recognition
d) To create animations
a) Weak AI
b) Strong AI
c) Super AI
d) Narrow AI
a) A computer program that mimics the decision-making ability of a human expert
b) A type of database
c) A software for programming
d) A hardware device
a) To reduce the number of input variables for a model
b) To increase data storage
c) To improve user interface
d) To analyze network traffic
a) Large volumes of data that can be analyzed for insights
b) Small amounts of data
c) Data stored on a single device
d) Data without analysis
a) Ethical considerations
b) Increased processing power
c) Improved algorithms
d) Better data storage
a) The process of creating human-like text from data
b) The process of understanding human language
c) The process of analyzing audio
d) The process of encoding data
a) To train a model using labeled data
b) To classify unlabelled data
c) To analyze data without supervision
d) To improve user experience
a) To clean and prepare data for modeling
b) To increase data size
c) To encrypt data
d) To improve graphics
a) Clustering
b) Classification
c) Regression
d) Prediction
a) It is used to teach the model to make predictions
b) It is used to test the model
c) It is used to store results
d) It is not significant
a) Naive Bayes
b) K-means clustering
c) Random forest
d) Convolutional Neural Networks
a) Fraud detection
b) Data entry
c) Expense reporting
d) Customer service
a) Machine learning
b) Data visualization
c) Web development
d) Cloud storage
a) An AI program that simulates conversation with users
b) A program for video calls
c) A type of search engine
d) A data storage tool
a) To determine the emotional tone behind words
b) To analyze data structures
c) To manage databases
d) To create user interfaces
a) TensorFlow
b) HTML
c) PHP
d) CSS
a) To suggest products or content to users
b) To analyze user data
c) To create websites
d) To manage databases
a) Bias in algorithms
b) Improved efficiency
c) Lower costs
d) Faster processing
a) An optimization algorithm inspired by natural selection
b) A social media algorithm
c) A marketing strategy
d) A data encryption method
a) The process of increasing the size of the training dataset
b) The process of cleaning data
c) The process of analyzing data
d) The process of compressing data
a) Algorithmic bias
b) Data bias
c) Human bias
d) All of the above
a) To group similar data points together
b) To separate data into distinct classes
c) To increase data storage
d) To improve processing speed
a) Autonomous vehicles
b) Traffic management
c) Route optimization
d) All of the above
a) Recurrent Neural Network (RNN)
b) Cloud Neural Network
c) Distributed Neural Network
d) Linear Neural Network
a) To leverage knowledge from one domain to improve learning in another
b) To increase data storage
c) To clean data
d) To compress data
a) A mathematical representation of a process
b) A physical robot
c) A software application
d) A data storage system
a) To optimize the weights of the network
b) To clean data
c) To increase data size
d) To store results
a) Expert systems
b) Neural networks
c) Genetic algorithms
d) Deep learning
a) Operating independently without human intervention
b) Requiring constant human input
c) Being controlled by a central system
d) Having limited capabilities
a) To identify outliers in data
b) To create visualizations
c) To manage databases
d) To encrypt data
a) Understanding context
b) Translating text accurately
c) Detecting sarcasm
d) All of the above
a) Deep learning and reinforcement learning
b) Unsupervised learning and supervised learning
c) Biological learning and social learning
d) Data analysis and visualization
a) Predictive analytics
b) Data entry
c) Customer support
d) Web development
a) The balance between a model's ability to minimize bias and variance
b) The amount of data used for training
c) The processing speed of a model
d) The cost of implementing AI
a) Siri
b) Excel
c) Photoshop
d) PowerPoint