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Generic AI - 1

Total questions: 10

Worksheet time: 2mins

Name
Class
Date
1.

What is a "Transformer" in AI models?

a)

A deep learning architecture based on self-attention

b)

A mechanical robot that changes forms

c)

A traditional rule-based AI system

d)

A tool used for converting file formats

2.

Fine-tuning a pre-trained AI model involves:

a)

Rebuilding the model from scratch

b)

Training it on task-specific data to improve performance

c)

Only adjusting the UI of the model

d)

Compressing the model into a zip file

3.

Which of these is an example of a Generative AI model?

a)

ResNet-50

b)

Decision Trees

c)

Naive Bayes Classifier

d)

ChatGPT

4.

Which of these is a common application of Computer Vision AI models?

a)

Translating text between languages

b)

Detecting objects in images

c)

Predicting stock prices

d)

Compressing video files

5.

Which factor most affects an AI model’s generalization ability?

a)

The size and diversity of the training dataset

b)

The color scheme of the development environment

c)

The storage format of the dataset

d)

The number of developers on the team

6.

Which term describes an AI model's ability to handle tasks it wasn’t explicitly trained for?

a)

Supervised Learning

b)

Transfer Learning

c)

Overfitting

d)

Underfitting

7.

Which of these is a key benefit of Large Language Models (LLMs)?

a)

They work only with numerical datasets

b)

They require no training data

c)

They understand and generate human-like text

d)

They are only used for computer vision tasks

8.

What does "Prompt Engineering" refer to in AI?

a)

Optimizing data pipelines

b)

Designing efficient CPU architectures

c)

Building user interfaces for chatbots

d)

Crafting effective inputs to guide AI model outputs

9.

Which of these is an unsupervised learning task?

a)

Clustering customers by purchasing behavior

b)

Predicting house prices based on historical sales

c)

Classifying emails as spam or not spam

d)

Training a chatbot for customer queries

10.

Which metric is commonly used to evaluate the performance of a classification AI model?

a)

Mean Squared Error (MSE)

b)

Pixel Density

c)

F1 Score

d)

Hash Rate