Artificial Intelligence Flashcards
7 cards from real Artificial Intelligence practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Artificial Intelligence flashcards as text
Which technique helps prevent overfitting by randomly disabling neurons during training?
Answer: Dropout
Dropout randomly zeroes neuron outputs during training, forcing the network to learn redundant representations.
In natural language processing, what does tokenization do?
Answer: Splits text into smaller units like words or subwords
Tokenization breaks raw text into discrete units that models can process numerically.
A convolutional neural network (CNN) is most commonly associated with which type of data?
Answer: Images
CNNs exploit spatial locality with convolutional filters, making them ideal for image data.
What is the primary purpose of the minimax algorithm in game-playing AI?
Answer: To choose moves assuming an optimal opponent
Minimax selects moves that maximize the player's worst-case outcome against a perfectly playing adversary.
Which scenario best illustrates algorithmic bias in AI?
Answer: A hiring model penalizing resumes from certain demographics due to skewed training data
Bias arises when skewed training data causes systematically unfair outcomes for particular groups.
What does backpropagation compute during neural network training?
Answer: Gradients of the loss with respect to each weight
Backpropagation applies the chain rule to compute how each weight contributes to the loss, enabling gradient descent updates.
Which of the following describes narrow AI?
Answer: AI specialized in a single task like playing chess
Narrow (weak) AI excels at one specific task but cannot generalize beyond its designed domain.