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AI QUIZ

Description

Challenge your knowledge with this Advanced Artificial Intelligence Quiz designed for AI enthusiasts, developers, and students! This quiz features difficult multiple-choice questions covering deep learning, reinforcement learning, neural networks, and theoretical foundations like the No Free Lunch Theorem and Markov processes. Test your understanding of cutting-edge AI techniques and concepts with questions that go beyond the basics.
Sumukh Hegde
Quiz by Sumukh Hegde, updated 5 months ago
Sumukh Hegde
Created by Sumukh Hegde 5 months ago
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Resource summary

Question 1

Question
Which of the following best describes the No Free Lunch Theorem in AI?
Answer
  • AI algorithms perform better when trained with more data
  • No single algorithm is best for all problems
  • AI algorithms cannot surpass human intelligence
  • Training AI models requires computational optimization

Question 2

Question
What is catastrophic forgetting in neural networks?
Answer
  • Overfitting to the training data
  • Deletion of weights during training
  • Loss of previously learned information when learning new tasks
  • Memory overflow during backpropagation

Question 3

Question
In Deep Q-Networks (DQN), what is the main purpose of the target network?
Answer
  • To reduce training time
  • To explore the environment
  • To stabilize learning by fixing the Q-value targets
  • To store policy gradients

Question 4

Question
Which activation function is most prone to the dying neuron problem?
Answer
  • Sigmoid
  • Tanh
  • ReLU
  • Swish

Question 5

Question
What does the attention mechanism do in Transformer models?
Answer
  • A. Reduces model parameters
  • B. Assigns weights to input tokens based on relevance
  • C. Prevents overfitting
  • D. Compresses the input sequence

Question 6

Question
Which technique is commonly used to deal with the vanishing gradient problem in RNNs?
Answer
  • Dropout
  • Gradient clipping
  • Batch normalization
  • Layer normalization

Question 7

Question
In game-playing AI, the Minimax algorithm assumes that:
Answer
  • Both players make optimal decisions
  • Only one player uses a rational strategy
  • Players take random actions
  • The game is stochastic in nature

Question 8

Question
Which of the following models does not use the Markov property explicitly?
Answer
  • Hidden Markov Model (HMM)
  • Q-learning
  • Recurrent Neural Network (RNN)
  • Markov Decision Process (MDP)

Question 9

Question
In transfer learning, which layer of a pre-trained network is most commonly replaced or fine-tuned for a new task?
Answer
  • Initial convolutional layers
  • All hidden layers
  • Output layer
  • Pooling layer

Question 10

Question
Which of the following is not a valid assumption in the Naive Bayes classifier?
Answer
  • Features are independent given the class
  • The model uses Bayes' theorem
  • Features are conditionally dependent on each other
  • The prior probabilities are used
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