CS, AI and ML: Connections

Think About It...

As we begin our next lesson, ask yourself a question:

Do you know what CS, AI and ML stand for?
Do you know how those three ideas are connected?

Within the past few years, you may have heard the terms Computer Science (CS), Artificial Intelligence (AI), and Machine Learning (ML). These three concepts are all related, yet they are still different. One thing the three fields have in common is the need for data. Let’s explore the three fields and how they are related.

Understanding CS, AI and ML

Computer Science (CS) is the foundational base for both Artificial Intelligence (AI) and Machine Learning. AI aims to simulate human intelligence, while ML is a part of AI that focuses on training systems to learn and improve from data. Another way to explain this concept is that:

CS gives us the tools to create machines
AI aims for machines to think like humans
ML teaches machines to learn from the information they receive

Here are examples of how CS, AI, and ML utilize data…differently:

Computer Science: data structure and algorithms are used to organize and manipulate data efficiently. For instance, CS helps create databases that store and retrieve information quickly. An example of this is how your computer saves and finds files, pictures, or your favorite game.
Artificial Intelligence: uses information to teach computers to do smart things like telling what’s in a picture or understanding what someone is saying. An example of this is teaching a robot, such as a smart vehicle, to recognize traffic signals, pedestrians, and objects when traveling.
Machine Learning: algorithms learn from data to make predictions or decisions without being explicitly programmed. Machine learning helps computers learn by looking at lots of examples, known as training data/sets. Fun fact: the more data the better in ML. Just like when you play a game, cook, or draw and get better each time, machines learn from lots of information to make better suggestions like those used in steaming platforms or online shopping sites to recommend new videos or items to purchase.

Video Lessons

The following two videos will help us better understand some fundamentals:

Video 1: How does AI work?
Video 2: What is Machine Learning?

Take the time to watch both videos to improve your understanding. Take notes in your notebook for future reference.

Video Credit: Both videos are courtesy of Code.org

How Does AI Work?

What is Machine Learning?

Conclusion

The point of this lesson was to gain an in-depth understanding of data and how it is used and be able to differentiate between CS, AI, and ML. The lesson explored different types of data, the importance of data, ways in which data is collected and computed, and examples of how it is used in the real world. You should now be able to evidence an understanding of CS, AI, and ML and how those fields are related and the important part that data plays in each.

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