What Generative AI actually is in Prompt Engineering / GenAI - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is Generative AI?

Generative AI is a type of artificial intelligence that can create new content like text, images, or music by learning patterns from existing data.

beginner

How does Generative AI learn to create new content?

It learns by studying lots of examples and finding patterns, then uses those patterns to make new, similar content.

intermediate

Name two common types of Generative AI models.

Two common types are Generative Adversarial Networks (GANs) and Transformer-based models like GPT.

beginner

Why is Generative AI compared to a creative friend?

Because it can imagine and produce new ideas or content, similar to how a friend might create a story or draw a picture.

beginner

What is a real-life example of Generative AI?

Chatbots that write stories or AI tools that create artwork are examples of Generative AI in action.

What does Generative AI primarily do?

A Creates new content based on learned patterns

B Only classifies existing data

C Deletes unwanted files

D Stores data securely

Generative AI creates new content by learning from existing data patterns.

Which of these is a type of Generative AI model?

A Decision Tree

B Generative Adversarial Network (GAN)

C K-Nearest Neighbors

D Linear Regression

GANs are a popular type of Generative AI model designed to create new data.

Generative AI learns by:

A Studying patterns in data

B Random guessing

C Copying data exactly

D Ignoring data

It studies patterns in data to generate new, similar content.

Which is NOT an example of Generative AI?

A AI that writes poems

B AI that composes music

C AI that creates images

D AI that recognizes faces

Face recognition AI classifies data but does not generate new content.

Why is Generative AI useful?

A It only stores data

B It deletes old files

C It helps create new ideas and content quickly

D It slows down computers

Generative AI helps by quickly producing new creative content.

Explain in your own words what Generative AI is and how it works.

Think about how a friend might learn from stories to tell a new one.

List some real-life uses of Generative AI you know or can imagine.

Consider tools that help create things automatically.

Practice

1. What is the main purpose of Generative AI?

easy

A. To store large amounts of data efficiently

B. To delete irrelevant information from datasets

C. To only classify existing data into categories

D. To create new content by learning from examples

Solution

1. Step 1: Understand the role of Generative AI

   Generative AI learns patterns from data and creates new content based on those patterns.

2. Step 2: Compare options with the definition

   Only To create new content by learning from examples describes creating new content by learning from examples, which matches the main purpose.

3. Final Answer:

   To create new content by learning from examples -> Option D

4. Quick Check:

   Generative AI = create new content [OK]

Hint: Generative AI makes new stuff from learned data [OK]

Common Mistakes:

• Confusing Generative AI with data storage
• Thinking it only classifies data
• Believing it deletes data

2. Which of the following is the correct way to describe Generative AI in simple code terms?

easy

A. Train a model, then generate new outputs

B. Only collect data without processing

C. Manually write all new content

D. Delete old models before training

Solution

1. Step 1: Identify the typical workflow of Generative AI

   Generative AI involves training a model on data and then using it to create new outputs.

2. Step 2: Match options to this workflow

   Train a model, then generate new outputs correctly states this process, while others describe unrelated or incorrect actions.

3. Final Answer:

   Train a model, then generate new outputs -> Option A

4. Quick Check:

   Train then generate = correct process [OK]

Hint: Generative AI = train model + create new data [OK]

Common Mistakes:

• Thinking Generative AI only collects data
• Assuming manual content creation is AI
• Confusing training with deleting models

3. Consider this Python-like pseudocode for a simple Generative AI process:

model = train(data)
new_content = model.generate()

What will new_content most likely contain?

medium

A. A new example similar to the training data

B. The original training data unchanged

C. An error message because generate() is undefined

D. An empty output with no content

Solution

1. Step 1: Understand the code steps

   The code trains a model on data, then calls generate() to create new content.

2. Step 2: Predict the output of generate()

   Generate() produces new content similar to what the model learned, not the original data or errors.

3. Final Answer:

   A new example similar to the training data -> Option A

4. Quick Check:

   generate() = new similar content [OK]

Hint: generate() creates new data like training examples [OK]

Common Mistakes:

• Thinking generate() returns original data
• Assuming generate() causes an error
• Expecting empty output

4. The following code is intended to train a Generative AI model and generate new content:

model = train(data)
new_content = model.generate(data)

What is the likely problem here?

medium

A. model should be a list, not a model object

B. train() should not take data as input

C. generate() should not take data as input after training

D. new_content should be assigned before training

Solution

1. Step 1: Review typical usage of generate()

   After training, generate() usually creates new content without needing input data again.

2. Step 2: Identify misuse in code

   Passing data to generate() is incorrect; it should generate based on learned patterns alone.

3. Final Answer:

   generate() should not take data as input after training -> Option C

4. Quick Check:

   generate() no input needed [OK]

Hint: generate() uses learned model, no extra data input [OK]

Common Mistakes:

• Thinking train() shouldn't take data
• Confusing model type
• Assigning new_content before training

5. You want to create a Generative AI that writes short poems. Which steps best describe the process?

hard

A. Write poems manually, then use AI to classify them

B. Collect poem examples, train model on them, generate new poems

C. Train model on random text, then delete training data

D. Generate poems first, then collect examples to train

Solution

1. Step 1: Understand the goal of Generative AI for poems

   The AI needs to learn from existing poems to create new ones.

2. Step 2: Identify the correct sequence of actions

   Collecting examples, training the model, then generating new poems is the correct order.

3. Final Answer:

   Collect poem examples, train model on them, generate new poems -> Option B

4. Quick Check:

   Learn from examples, then create new [OK]

Hint: Train on examples first, then generate new content [OK]

Common Mistakes:

• Trying to generate before training
• Confusing classification with generation
• Deleting training data too early