artificial intelligence mcqs for lcc

Past Forces Tests of Artificial Intelligence MCQs

If you want to join Pakistan Army, Navy or Air Force as ICTO in IT branch then here you can find the best questions related to the past experiences of Army ICTO, LCC, PAF IT Branch, and Navy Information Technology branch. Moreover, these questions are also been collected from the tests of Education branch subject tests of computer sciences. Learn by heart the given questions of artificial intelligence mcqs;

  • Artificial Intelligence is                              .  (A field of computer science)
  • The goal of AI is to                              .  (Replicate human intelligence in machines)
  • Machine Learning is a subfield of AI that focuses on                              (Teaching machines to learn from data)
  • Deep Learning is a subset of Machine Learning that                              . (Uses neural networks with multiple layers)
  • Natural Language Processing (NLP) is concerned with                              . (Analyzing and understanding human language)
  • The Turing Test, proposed by Alan Turing, is used to                              . (Assess AI’s ability to imitate human conversation)
  • Expert Systems are AI systems that                              . (Simulate human decision-making in specific domains)
  • Reinforcement Learning is a type of Machine Learning that           . (Focuses on reward-based learning through interaction with an environment)
  • Computer Vision is a field of AI that                              .  (Enables machines to interpret and understand visual information)
  • Ethics in AI refers to                              .  (The moral and societal implications of AI technologies)
  • Logic is                               .   (The foundation of reasoning in AI systems)
  • In AI, logic is used for                               .  (Knowledge representation and inference)
  • Propositional logic deals with                               (Statements that are either true or false)
  • First-order logic (FOL) extends propositional logic by                               .  (Allowing for reasoning about objects and their properties)
  • In logic, a knowledge base is                               .  (A collection of facts and rules used for reasoning)
  • Inference in logic refers to                               .  (The process of reasoning based on given facts and rules)

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Questions of Artificial Intelligence MCQs

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  • The modus ponens rule in logic states that                               . (If A implies B and A is true, then B is true)
  • The resolution rule in logic is used for                               .  (Logical inference and proof by contradiction)
  • In logic, a truth table is used to                               .  ( Evaluate the validity of logical arguments)
  • In propositional logic, the logical operator “AND” is represented by                               .  (∧)
  • The logical operator “OR” in propositional logic is represented by                               . (∨)
  • The logical operator “NOT” in propositional logic is represented by                               . (¬)
  • In first-order logic, the symbol ∀ represents                               . (Universal quantification)
  • The logical connective “if and only if” is represented by                               . (↔)
  • In logic, a tautology refers to                                (A logical statement that is always true)
  • Perception is                               .   (The process of gathering sensory information from the environment)
  • In AI, perception involves                               .   (Analysis of textual data, Interpreting visual information, Recognizing speech and sounds)
  • Computer vision is a branch of AI that focuses on                               .   (Recognizing and understanding visual information)
  • Speech recognition is a form of perception that involves                               . (Analyzing and understanding spoken language)
  • The process of feature extraction in perception refers to                               . (Identifying and representing important characteristics in the data)
  • The term “sensor fusion” in perception refers to                               .  (Combining information from different sensory modalities)
  • Object recognition in computer vision involves                               . (Identifying and classifying objects in images or videos)

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Artificial Intelligence MCQs with Answers Free

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  • Depth perception in computer vision refers to the ability to                               . (Understand three-dimensional space from two-dimensional images)
  • The process of image segmentation in computer vision involves                               . (Dividing an image into meaningful regions or objects)
  • The term “perceptual reasoning” in AI refers to                               . (The ability to understand and reason about perceptual information)
  • In natural language processing, sentiment analysis involves                               . (Recognizing and understanding human emotions in text)
  • The concept of “ambient intelligence” in perception refers to                               .  (AI systems that adapt to users’ preferences and behaviors)
  • The term “haptic perception” refers to the ability to                               .   (Understand and interpret tactile information)
  • The process of data fusion in perception involves                               .   (Combining information from multiple sources to improve understanding)
  • The concept of “contextual perception” in AI refers to                               . (Considering the surrounding context to enhance understanding and interpretation of sensory information)
  • Machine learning is                              .  (A subfield of AI that focuses on algorithms that can learn from data)
  • In machine learning, the term “supervised learning” refers to                              . (Learning from examples where inputs and outputs are provided)
  • The process of training a machine learning model involves                              . (Providing labeled examples to the model and adjusting its parameters)
  • The term “feature engineering” in machine learning refers to                              . (Extracting and selecting relevant features from raw data)
  • Unsupervised learning in machine learning involves                              . (Analyzing unlabeled data to discover patterns and structures)
  • The term “reinforcement learning” in machine learning refers to                              . (Training models to make decisions based on rewards and punishments)
  • The loss function in machine learning is used to                              . (Measure the performance of a machine learning model)

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  • The bias-variance tradeoff in machine learning refers to                              .(Managing the tradeoff between underfitting and overfitting)
  • A decision tree is a machine learning algorithm that                              (Learns to make decisions by constructing a tree-like model)
  • The term “dimensionality reduction” refers to a technique used in AI to                              .  (Reduce the number of input features in a dataset)
  • The term “gradient descent” refers to an optimization algorithm used in AI to                              .  ( Adjust the weights in a neural network)
  • The term “ensemble learning” refers to a technique in AI that                              .(Combines the predictions of multiple models)
  • The k-nearest neighbors (KNN) algorithm in machine learning is used for                              .   (Classifying data based on the majority vote of its neighbors)
  • The term “overfitting” in machine learning refers to                              . (A model that performs poorly on unseen data)
  • The term “underfitting” in machine learning refers to                              . (A model that performs poorly on unseen data)
  • The term “gradient descent” in machine learning refers to                              . (The process of updating a model’s parameters to minimize the loss function)
  • The term “ensemble learning” in machine learning refers to                              . (Combining the predictions of multiple models to improve performance)
  • In deep learning, a neural network is composed of                              . (Multiple hidden layers)
  • The term “backpropagation” in deep learning refers to                              . (The process of computing the gradients of the loss function with respect to the weights)
  • The activation function in a neural network is responsible for                              . (Introducing non-linearity into the network’s computations)
  • Convolutional Neural Networks (CNNs) are commonly used in deep learning for                              ( Image classification tasks)
  • Recurrent Neural Networks (RNNs) are commonly used in deep learning for                              .  (Time series forecasting tasks)
  • The Long Short-Term Memory (LSTM) architecture is an extension of RNNs that                              (Handles the vanishing gradient problem in RNNs)

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Frequently Asked Artificial Intelligence MCQs with Answers

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  • Generative Adversarial Networks (GANs) are used in deep learning for                              .  (Image generation tasks)
  • The term “transfer learning” in deep learning refers to                              . (Transferring knowledge learned from one task to another related task)
  • The term “dropout” in deep learning refers to                              . (Randomly dropping out a fraction of neurons during training)
  • Transfer learning in machine learning refers to                              . (Transferring knowledge learned from one task to another related task)
  • Deep learning is                              .  (The process of training neural networks with multiple hidden layers)
  • The term “batch normalization” in deep learning refers to                              . (Normalizing the activations within a layer during training)
  • The term “early stopping” in deep learning refers to                              . (Stopping the training process when the model’s performance on a validation set starts to degrade)
  • The term “hyperparameters” in deep learning refers to                              . ( The learning rate and batch size of a neural network)
  • The term “vanishing gradient problem” in deep learning refers to                              . (The process of gradients vanishing during backpropagation)
  • The term “model checkpointing” in deep learning refers to                              . ( Saving the model’s architecture and weights during training)
  • An algorithm is a                               (Set of instructions for solving a specific problem)
  • The purpose of the A* algorithm in AI is to                              .   (Find the shortest path in a graph)
  • Genetic algorithms are a type of AI algorithm inspired by                              ( The principles of natural selection and genetics)
  • The k-nearest neighbors (k-NN) algorithm is used for                              .   (Classifying data based on labeled examples)
  • The Random Forest algorithm is an ensemble learning technique that combines                              .  (Decision trees)
  • The term “supervised learning” refers to a type of AI algorithm that                               (Learns from labeled data with input-output pairs)

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ICTO Tests of Artificial Intelligence MCQs Free Tests

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  • The term “unsupervised learning” refers to a type of AI algorithm that                              .  (Identifies patterns in datasets without prior labels)
  • The Naive Bayes algorithm is based on                              .  (Bayes’ theorem and probabilistic principles)
  • The term “reinforcement learning” refers to a type of AI algorithm that                              .   (Uses reinforcement signals to improve performance)
  • The term “deep learning” refers to a subset of AI algorithms that                              .(Use multiple layers of artificial neural networks)
  • The term “support vector machine” refers to a type of AI algorithm used for                              .  (Classifying data basedon labeled examples)
  • The term “natural language processing” (NLP) refers to a field of AI that focuses on                              .  ( Analyzing and understanding human language)
  • AI types are                              . (Strong AI and Weak AI)
  • Weak AI, also known as Narrow AI, refers to AI systems that                              . (Are designed to perform specific tasks or solve specific problems)
  • Strong AI, also known as Artificial General Intelligence (AGI), refers to AI systems that                              . ( Possess human-level intelligence and consciousness)
  • Machine Learning is a type of AI that                              . (Utilizes statistical techniques to enable computers to learn from data)
  • Deep Learning is a subset of Machine Learning that                              . (Mimics the human brain using artificial neural networks)
  • Natural Language Processing (NLP) is a type of AI that focuses on                              . (Analyzing and understanding human language)
  • Computer Vision is a type of AI that focuses on                              . (Processing and recognizing visual information)
  • Expert Systems are a type of AI that                              . (Mimic human decision-making and problem-solving in specific domains)
  • Robotics is a type of AI that focuses on                              . (Designing and building physical machines that can perform tasks autonomously)
  • Cognitive Computing is a type of AI that                              . (Aims to simulate human thought processes and reasoning abilities)
  • Swarm Intelligence is a type of AI that                              .  (Mimics the behavior of social insects like ants or bees)
  • Virtual Agents are a type of AI that                              . (Provide human-like conversational interactions)
  • Reinforcement Learning is a type of AI that                              . (Learns through trial and error by receiving feedback from its environment)
  • Process Mining is a technique used in automation to                              .  (Analyze and improve existing workflows in organizations)
  • Chatbot Automation involves                              .  (Using AI to automate the process of generating chatbot responses)

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