Lesson List
Section 1. Course Intro – Activity 1: FaceBoxes – Basic Face Detection
In this brief section, including Activity 1 we will discuss the various topics we will cover in this course, as well as some background on the concept of artificial intelligence vs natural intelligence.
0/4
Section 2. History of Computing & AI – Activity 2: What is AI?
In this section, we will discuss the early and recent history in AI technology development. We will also cover some background on semiconductors, CPU's, GPU's and other technology that make AI possible. We will also discuss the basics of AI model training, and go through some of today's most popular AI technologies.
0/1
Section 3. How is AI used in different applications? – Activity 3: Aligning real world AI with AI4K12
In this section, we will discuss several real world examples of AI robotics, and go through the exercise of aligning AI concepts with the AI4K12 5 Big Ideas in AI.
0/1
Section 4. AI in action: Teachable Machine – Activity 4: Training and testing an AI model
In this section, we will conduct a browser based activity, and will go through all the steps of developing training data, uploading it to a Google server, and training a real AI model, for object detection. We will then test our resulting model with different objects and record our results, to determine if the model is well-built and if there are any potential drawbacks or ways to improve the system.
0/2
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Lesson: Defining AI vs NI (Natural Intelligence)
Overview
Exercise Files
About Lesson

Activity 2: What is AI / What does AI mean to you?

  1. Download and use the worksheet for this activity, or, if you prefer (or are working with others), use a whiteboarding application like Miro, and make two columns labeled AI and NI, and add notes with ideas to each column.  
  2. Write your own definitions of AI and NI and we will revisit these definitions later on in the full course, to see if your conceptions have changed or if you feel you can better define these terms after the course.  
  3. What are the similarities and differences between NI and AI?  There are no right or wrong answers at this point.  

Reflect on the following concepts.  Do they align with your own definitions of AI/NI?

Artificial Intelligence (AI)

  • The ability to use an algorithm/program/machine/computer to learn new things
  • The ability to use an algorithm/program/machine/computer to apply knowledge to unknown circumstances.
  • A machine that can predict and classify things
  • A machine that can understand human language, and communicate effectively.
  • A machine that can think like, and communicate with, human beings.
  • A machine that can perceive its surroundings and react to them, in a logical way.

Intelligence / Natural Intelligence (NI)

  • Human ability to express themselves, to communicate
  • Apply gained knowledge to new circumstances
  • Ability to solve math problems and apply logic
  • Use knowledge to change your own environment
  • Communicate, teach and share ideas with others
  • The ability to learn complex things
Lesson List
Section 1. Course Intro – Activity 1: FaceBoxes – Basic Face Detection
In this brief section, including Activity 1 we will discuss the various topics we will cover in this course, as well as some background on the concept of artificial intelligence vs natural intelligence.
0/4
Section 2. History of Computing & AI – Activity 2: What is AI?
In this section, we will discuss the early and recent history in AI technology development. We will also cover some background on semiconductors, CPU's, GPU's and other technology that make AI possible. We will also discuss the basics of AI model training, and go through some of today's most popular AI technologies.
0/1
Section 3. How is AI used in different applications? – Activity 3: Aligning real world AI with AI4K12
In this section, we will discuss several real world examples of AI robotics, and go through the exercise of aligning AI concepts with the AI4K12 5 Big Ideas in AI.
0/1
Section 4. AI in action: Teachable Machine – Activity 4: Training and testing an AI model
In this section, we will conduct a browser based activity, and will go through all the steps of developing training data, uploading it to a Google server, and training a real AI model, for object detection. We will then test our resulting model with different objects and record our results, to determine if the model is well-built and if there are any potential drawbacks or ways to improve the system.
0/2
This feature has been disabled by the administrator
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