470 Final Exam Flashcards

(59 cards)

1
Q

Q: Generative AI can only create text, but not images or audio. (True/False)

A

False

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2
Q

Q: Which of the following is NOT a characteristic of human intelligence simulated by AI? a) Learning and Adaptation, b) Perception and Pattern Recognition, c) Superhuman Strength, d) Reasoning and Problem-Solving.

A

Superhuman Strength

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3
Q

Q: Superintelligent AI refers to an AI that surpasses human intelligence, including creativity and problem-solving abilities. (True/False)

A

True

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4
Q

Q: Of the 3 Types of AI, ___________ AI is capable of understanding, learning, and applying knowledge across a wide range of tasks, but it remains largely theoretical.

A

General AI or AGI

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5
Q

Q: Deep learning reduces the need for manual feature engineering because it can automatically learn features from large datasets. (True/False)

A

True

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6
Q

Q: Which of the following is a type of deep learning architecture/model? a) Decision Trees, b) Convolutional Neural Networks (CNNs), c) Support Vector Machines (SVMs), d) K-Nearest Neighbors (KNN).

A

Convolutional Neural Networks (CNNs)

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7
Q

Q: Which of the following is a common use case for traditional machine learning? a) Spam Detection, b) Image Generation, c) 3D Model Creation, d) Video Editing.

A

Spam Detection

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8
Q

Q: Arthur Samuel’s checkers program learned by playing against itself and improved over time without human intervention. (True/False)

A

True

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9
Q

Q: Discriminative models are used to generate new content, such as text or images. (True/False)

A

False

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10
Q

Q: Of the 3 types of AI, ___________ AI is where we currently are, focusing on AI that performs specific tasks.

A

Narrow or Weak AI

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11
Q

Q: Generative AI models are primarily used for classification tasks, like spam detection. (True/False)

A

False

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12
Q

Q: Which of the following tasks is NOT typically associated with Generative AI? a) Text Generation, b) Object/Image Classification, c) Video Generation, d) Music Creation.

A

Object/Image Classification

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13
Q

Q: Alan Turing introduced a famous test known as the ___________, which assesses a machine’s ability to imitate human conversation.

A

Turing Test

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14
Q

Q: The first AI Winter occurred in the 1990s due to unmet expectations and the limitations of expert systems. (True/False)

A

False

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15
Q

Q: Which of the following was one of the earliest AI systems that improved its strategy by playing against itself? a) Deep Blue, b) AlphaGo, c) Arthur Samuel’s Checkers Program, d) ELIZA.

A

Arthur Samuel’s Checkers Program

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16
Q

Q: The backpropagation algorithm is used to adjust weights in neural networks to minimize errors during training. (True/False)

A

True

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17
Q

Q: ___________ networks/models are designed to overcome the vanishing gradient problem by maintaining information over long sequences in tasks like language processing and are the successor to RNNs.

A

Long Short-Term Memory (LSTM)

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18
Q

Q: Alan Turing introduced the idea of genetic algorithms in his 1948 paper ‘Intelligent Machinery’. (True/False)

A

True

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19
Q

Q: Machine learning involves computers learning from data without being explicitly programmed. (True/False)

A

True

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20
Q

Q: What is the key innovation in transformer models, which has led to our recent explosion in LLMs such as ChatGPT? a) Recurrent processing, b) Self-attention mechanism, c) Gradient descent, d) Convolution layers.

A

Self attention mechanism

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21
Q

Q: The perceptron, developed by Frank Rosenblatt, used a simplified model of a biological neuron to make classification decisions. (True/False)

A

True

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22
Q

Q: The perceptron used a ___________ decision boundary to classify input data based on weights and inputs.

A

Linear

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23
Q

Q: Which neural network architecture is widely used for image recognition and classification? a) Convolutional Neural Networks (CNNs), b) Recurrent Neural Networks (RNNs), c) Perceptron, d) Generative Adversarial Networks (GANs).

A

Convolutional Neural Networks (CNNs)

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24
Q

Q: The Dartmouth Conference in 1956 is known as the birthplace of this particular academic field of computer science?

A

Artificial Intelligence

25
Q: The __________ algorithm, developed in the 1980s, allowed deep learning models to improve by adjusting for errors backward from the output layer.
Backpropagation
26
Q: The first artificial neural network capable of learning from examples was: a) The General Problem Solver, b) ELIZA, c) The Perceptron, d) AlphaGo.
The Perceptron
27
Q: The Chinese Room thought experiment argues that AI systems truly understand the languages they generate responses in. (True/False)
False
28
Q: _________ prompting asks the model to perform a task without giving it any examples.
Zero-Shot Prompting
29
Q: In regard to AGI, AI has already fully accomplished commonsense reasoning and self-awareness. (True/False)
False
30
Q: What does the Persona Pattern in prompt engineering mean?
Telling the AI to act in a specific role while performing a task.
31
Q: Prompt specificity and clarity are essential for achieving accurate and detailed responses from a model. (True/False)
True
32
Q: What is one-shot prompting?
Providing one example to guide the model
33
Q: What does Embodiment in AI refer to?
The extent to which physical interaction with the world produces intelligence.
34
Q: Providing more context in a prompt can help improve the accuracy of the AI's response. (True/False)
True
35
Q: Which of the following best describes the purpose of the Flipped Interaction Pattern?
When the AI asks the user questions to achieve a goal.
36
Q: AI can generate creative works like music and art, but this is based on pattern recognition, not true creativity. (True/False)
True
37
Q: Which of the following has AI mostly accomplished on the road to AGI?
Learning from data and natural language processing.
38
Q: Iterating/refining your prompt is a bad idea because it gives the AI too much information to work from. (True/False)
False
39
Q: Which of the following is an example of the Cognitive Verifier Pattern?
The AI breaks down a question into smaller steps and asks clarifying questions.
40
Q: By providing the AI with a template or structure, what can you achieve?
Having the information produced shown in a particular format, such as a recipe or outline.
41
Q: Transformers can process inputs in parallel and capture global context using self-attention mechanisms. (True/False)
True
42
Q: Causal Language Modeling (CLM) uses the context within a sentence to predict the 'missing' token. (True/False)
False
43
Q: Quantization is a technique to reduce the memory requirements of a model by lowering the precision or number of bits for model parameters. (True/False)
True
44
Q: What is the main function of the Softmax function in Transformers?
To convert attention scores into probabilities.
45
Q: What does Masked Language Modeling (MLM) aim to achieve?
Predict masked words in a sentence based on surrounding context.
46
Q: Describe how biases have been revealed in Word2Vec embeddings.
Word2Vec embeddings reflect societal stereotypes, revealing biases such as gender and racial biases
47
Q: What is the purpose of positional encoding in Transformers?
To capture the order of tokens in a sequence.
48
Q: In Word2Vec, what does the operation 'Paris - France + Italy' result in?
Rome
49
Q: Which attention mechanism allows each token to focus on others in the input sequence?
Self-attention
50
Q: Explain the vanishing gradient problem in RNNs.
Gradients become too small during backpropagation, leading to difficulty learning long-range dependencies.
51
Q: What does the learning rate control during the training of a neural network?
The adjustment of weights after each prediction.
52
In unsupervised learning, the model discovers patterns and relationships in what type of data?
Unlabeled data
53
An AI model can learn non-linear relationships effectively without using an activation function. (True/False)
False
54
What is the primary role of the activation function in a neural network?
To introduce non-linearity to the model.
55
Q: Which of the following best describes the role of the loss function?
the difference between the predicted and actual outputs.
56
Q: A lower temperature in AI models leads to more deterministic and predictable output generation. (True/False)
True
57
Q: Temperature is the only parameter that affects the randomness of the model's output. (True/False)
False
58
Q: What does Top-P (nucleus sampling) for a model?
It allows the model to choose from a broader or narrower pool of probable words.
59
Q: What is the purpose of using multiple attention heads in a Transformer?
To learn different relationships and dependencies in the input sequence, leading to richer representations.