AI Integration Programming Quiz

1. What does AI stand for?

• Artificial Intelligence
• Artificial Insight
• Automated Interaction
• Advanced Integration

2. Which AI programming language is renowned for libraries like TensorFlow and PyTorch?

• Java
• C++
• Python
• Ruby

3. What is machine learning?

• Programs designed exclusively for data storage
• Machines that operate only with pre-set instructions
• Programs or systems that learn from data instead of being explicitly programmed
• Software that does not adapt to new input

4. Which type of machine learning model should you use to organize documents into distinct groups without predefining the groups?

• Unsupervised learning model
• Reinforcement learning model
• Supervised learning model
• Semi-supervised learning model

5. How does generative AI work?

• It relies solely on user input without any learning.
• It only works with structured data from databases.
• It stores data on personal devices to generate content.
• It uses a neural network to learn from a large dataset.

6. What is prompt tuning?

• Improving the output quality of large language models.
• Training AI systems to interpret visual data.
• Simplifying the coding process for AI applications.
• Enhancing the speed of data collection methods.

7. What is a prompt?

• A command to execute a system function without explanation.
• A type of programming language for web development.
• A text to query or instruct a large language model (LLM) to generate desired output.
• A complex algorithm for data analysis in AI.

8. Which type of machine learning should you use to discover the underlying pattern and group a collection of unlabeled photos into different sets?

• Semi-supervised learning
• Unsupervised learning
• Reinforcement learning
• Supervised learning

9. What is the ε-greedy approach to action selection in reinforcement learning?

• The approach that discards exploration and focuses solely on exploitation.
• The approach that only chooses the best known action.
• The approach where ε = 0 makes it identical to a purely greedy approach.
• The approach that selects random actions with equal probability.

10. What is the purpose of using libraries like TensorFlow and PyTorch in AI programming?

• To enhance the development of tasks such as speech recognition, data interpretation, and autonomous driving.
• To manage databases and cloud storage solutions efficiently.
• To create video games and entertainment applications effortlessly.
• To design user interfaces and improve website aesthetics.

11. What is the difference between supervised and unsupervised learning?

• Supervised learning is only for image recognition, while unsupervised learning is for text analysis.
• Supervised learning uses random data, while unsupervised learning uses sorted data.
• Supervised learning focuses solely on regression, while unsupervised learning focuses on classification.
• Supervised learning involves labeled data, while unsupervised learning involves unlabeled data.

12. How does a social network’s AI use existing tagged photos of people to identify when those people appear in new photos?

• This is an example of unsupervised learning.
• This is an example of supervised learning.
• This is an example of reinforcement learning.
• This is an example of deep learning.

13. What is L2 loss in regression AI?

• The product of all individual L2 losses for each data point.
• The sum of all individual L2 losses for each data point.
• The maximum L2 loss recorded among all data points.
• The average of absolute errors across all data points.

14. Why might Hypothesis 2 still be preferable to Hypothesis 1 if Hypothesis 1 has a lower L1 and L2 loss?

• Hypothesis 2 is simpler to understand.
• Hypothesis 2 has better accuracy overall.
• Hypothesis 1 is based on stronger assumptions.
• Hypothesis 1 might be the result of overfitting.

15. What is the role of regularization in AI programming?

• To speed up the training process of the model.
• To make the model less interpretable and more opaque.
• To prevent overfitting by adding a penalty term to the loss function.
• To increase the complexity of the model for better accuracy.

16. What is cross-validation in AI programming?

• A technique to select the best features for a machine learning model.
• A technique to evaluate the performance of a model by training and testing it on multiple subsets of the data.
• A method to randomly shuffle the dataset for any programming task.
• A way to combine different algorithms into a single model.

17. What is regression in AI programming?

• A technique used for image processing.
• A type of supervised learning where the model predicts continuous values.
• A method for clustering data into sets.
• An algorithm for classifying categorical outcomes.

18. What is discriminative deep learning?

• A type of algorithm used for clustering similar items.
• A method for generating random data from a structured dataset.
• A process in which AI generates new ideas without prior input.
• A type of machine learning where the model learns to classify data based on specific features.

19. What is natural language processing (NLP)?

• The ability of AI systems to understand, interpret, and generate human language.
• A system for managing data storage in computer systems.
• A method for programming AI to perform calculations efficiently.
• A technique for creating visual content using machine learning algorithms.

20. What is the ε-greedy approach used for in reinforcement learning?

• To balance exploration and exploitation in decision-making processes.
• To optimize network weights before training.
• To minimize loss functions during training.
• To increase the learning rate of the algorithm.

21. How do large language models (LLMs) work?

• They require human input for every decision made.
• They function by storing and retrieving fixed responses only.
• They operate solely on predefined rules without data learning.
• They use neural networks to learn from large datasets and generate text based on input prompts.

22. What is the purpose of prompt tuning in LLMs?

• To eliminate the need for data during training.
• To reduce the size of language models significantly.
• To make LLMs more versatile and improve their output quality.
• To create entirely new language models from scratch.

23. What is the difference between a pre-trained AI model and a prompt?

• A pre-trained AI model requires human input only once, whereas a prompt is used multiple times.
• A pre-trained AI model generates data while a prompt always outputs text formats.
• A pre-trained AI model performs various tasks, while a prompt is a guide to instruct the model to generate specific output.
• A pre-trained AI model is a type of prompt for data input during training.

24. How does generative AI generate content?

• It generates content solely by following pre-defined rules and algorithms.
• It uses neural networks to learn from large datasets and generate new content based on patterns learned from the data.
• It produces content by copying existing works without any learning involved.
• It relies on random word generation to create content without guidance.

25. What is the role of data analytics in AI programming?

• To ensure data privacy and security in all applications.
• To enhance creativity by generating new ideas based on trends.
• To track student performance over time and provide insights into common areas of struggle.
• To automate tasks by replacing human input and decisions.

26. How do AI quizzes enhance developer education?

• They hinder knowledge retention by repeating the same questions.
• They focus solely on theoretical concepts with no practical application.
• They rigidly assess knowledge with only true/false questions.
• They provide interactive learning and assessment, incorporating diverse question types like multiple-choice, coding challenges, and scenario-based questions.

27. What are some strategies for integrating AI quizzes into web development courses?

• Use traditional teaching methods without any technology integration.
• Focus only on multiple-choice questions and static content updates.
• Avoid collaboration with other educational tools and resources.
• Utilize existing platforms like Kahoot or Quizlet, incorporate diverse question types, and ensure regular updates to reflect the latest trends and technologies.

28. What is the importance of using AI programming languages like Python?

• They are only used in academic research and have no practical application.
• They are exclusively used for developing video games and virtual reality applications.
• They require advanced mathematical skills to write any functional program.
• These languages simplify coding and offer libraries tailored for tasks like machine learning and data analysis.

29. What is the purpose of using frameworks like TensorFlow.js in AI programming?

• To create graphical user interfaces for mobile applications easily.
• To enhance the development of tasks such as speech recognition, data interpretation, and autonomous driving.
• To teach programming languages to beginners efficiently and quickly.
• To write business reports and documents automatically without input.

30. How does a social network’s AI use existing tagged photos to identify people in new photos?

• The AI identifies people by comparing their hair colors and heights in photos.
• AI analyzes the background of the photo to determine identities.
• The AI uses random sampling to guess the identities of people.
• This is an example of supervised learning where the AI uses labeled data to make predictions.