Types of AI (narrow AI vs general AI) in AI for Everyone - Hands-On Comparison

Types of AI: Narrow AI vs General AI

📖 Scenario: You are learning about different types of Artificial Intelligence (AI) to understand how they work in real life.Imagine you want to organize information about AI types to explain to a friend.

🎯 Goal: Create a simple data structure to hold examples of Narrow AI and General AI, then categorize them clearly.

📋 What You'll Learn

Create a dictionary named ai_types with two keys: 'Narrow AI' and 'General AI'

Assign a list of exactly three examples to each key as specified

Create a variable named example_count that counts total examples across both AI types

Use a loop with variables category and examples to iterate over ai_types.items()

Add a final statement that sets a variable summary to a string describing the total examples

💡 Why This Matters

🌍 Real World

Organizing and categorizing information clearly helps in teaching and understanding complex topics like AI.

💼 Career

Data organization and clear communication are key skills in many jobs, including AI research, education, and software development.

1

Create the AI types dictionary

Create a dictionary called ai_types with two keys: 'Narrow AI' and 'General AI'. Assign the list ['Voice assistants', 'Image recognition', 'Spam filters'] to 'Narrow AI' and the list ['Human-level reasoning', 'Self-aware systems', 'General problem solving'] to 'General AI'.

AI for Everyone

# Create the ai_types dictionary with specified keys and lists
# Your code here

Hint

Use a dictionary with two keys and assign the exact lists to each key.

2

Count total AI examples

Create a variable called example_count and set it to 0. Then add the total number of examples from both 'Narrow AI' and 'General AI' lists.

AI for Everyone

ai_types = {
    'Narrow AI': ['Voice assistants', 'Image recognition', 'Spam filters'],
    'General AI': ['Human-level reasoning', 'Self-aware systems', 'General problem solving']
}
# Create example_count and set it to 0
# Your code here

Hint

Start with zero and add the length of each list from the dictionary.

3

Iterate over AI types

Use a for loop with variables category and examples to iterate over ai_types.items(). Inside the loop, add a comment describing that you are processing each AI category.

AI for Everyone

ai_types = {
    'Narrow AI': ['Voice assistants', 'Image recognition', 'Spam filters'],
    'General AI': ['Human-level reasoning', 'Self-aware systems', 'General problem solving']
}
example_count = 0
example_count += len(ai_types['Narrow AI'])
example_count += len(ai_types['General AI'])

# Use a for loop to iterate over ai_types.items()
# Your code here

Hint

Use a for loop with the exact variable names to go through the dictionary items.

4

Create summary description

Add a variable called summary and set it to the string "There are X total AI examples." where X is the value of example_count using an f-string.

AI for Everyone

ai_types = {
    'Narrow AI': ['Voice assistants', 'Image recognition', 'Spam filters'],
    'General AI': ['Human-level reasoning', 'Self-aware systems', 'General problem solving']
}
example_count = 0
example_count += len(ai_types['Narrow AI'])
example_count += len(ai_types['General AI'])

for category, examples in ai_types.items():
    # Processing AI category and its examples
    pass

# Create summary string using example_count
# Your code here

Hint

Use an f-string to include the example_count variable inside the string.