Artificial Intelligence and Machine Learning
Instead of writing down every rule by hand, it is like having a computer solve thousands of practice exams so it figures out the formula on its own.
Definition Artificial Intelligence (AI) is the broad concept of creating machines that think and reason like humans, while Machine Learning (ML) is a specific method that trains computers to discover rules directly from data.
Memorizing Study Guides vs. Solving Practice Exams
When studying for an exam, you can either memorize a study guide word for word or solve countless practice exams to pick up question patterns on your own. In computer programming, the exact same two approaches exist. If traditional programming is about a machine strictly following rules written by humans, machine learning is how a computer figures out the formulas and intuition itself by reviewing massive sets of questions and answers.
All of this falls under the grand goal of Artificial Intelligence (AI)—building machines that think intelligently like humans. AI is not just the name of a specific technology; it is the broadest umbrella and the ultimate vision that covers any tech mimicking human intelligence.
Most modern AI we encounter every day—like smartphone voice assistants, translation tools, and recommendation algorithms—is powered by this very study method called machine learning.
Why Let the Machine Learn Instead of Giving All the Rules?
Things that feel effortless to humans can be brutally hard for computers. For instance, imagine writing code with every single rule to distinguish whether an animal in a photo is a cat or a dog. If you define a cat as 'an animal with pointy ears, fur, and whiskers,' the computer gets completely lost the moment it sees a cat with folded ears or a long-haired dog.
Humans tell them apart intuitively, but explaining those complex criteria in words and code is virtually impossible. That is why machine learning skips the rulebook and simply hands the computer tens of thousands of photo examples instead.
By comparing countless images, the computer uncovers statistical patterns on its own: 'Aha, cats usually have this eye shape and these contours.' The machine ends up picking up subtle distinctions that humans could never fully put into words.
Putting It All Together: AI, Machine Learning, and Deep Learning
In the news, AI, machine learning, and deep learning are often used interchangeably, but they fit together like Russian nesting dolls. The largest, outermost doll is Artificial Intelligence, the overarching concept referring to any machine capable of human-like behavior.
The medium-sized doll inside AI—using 'learning from data' as its core engine—is Machine Learning. In the past, a chess program built purely on hardcoded rules counted as AI, but it was not machine learning because it did not learn from data.
And nestled deep inside machine learning is Deep Learning, the newest technique that mimics neural networks in the human brain to process complex data with incredible precision. In short, deep learning is a subset of machine learning, and machine learning lives inside the vast universe of AI.
🤔 Common misconceptions
Artificial intelligence and machine learning are the exact same thing.
AI is the overarching goal and field, while machine learning is one specific method to achieve that goal. All machine learning is AI, but not all AI is machine learning.
🧺 Where you meet it
AI is the grand dream of building smart machines, and machine learning is the method where machines study data to make that dream come true.