Machine learning is a way of teaching computers to do tasks. In the past, to do anything, computers depended on detailed, step-by-step instructions written by a person. But with machine learning, computers pick up new skills on their own, using examples or experience. This makes machine learning a powerful form of artificial intelligence, or AI. AI is the ability of a machine to think or learn like a person. AI systems power many kinds of machines—from smartphones to robots.
There are a few types of machine learning. The most common is supervised(监督的) learning. In this method, a computer is fed lots of sorted training data. For example, it may look at many photos of dogs. Each photo might be sorted by the dog's kind. By studying those photos, the computer learns what each kind of dog looks like. Then, the computer can pick out dog kinds in new, unsorted photos. The more data the computer studies, the better it gets at its task.
Another important kind of machine learning is reinforcement(强化) learning. Using this type of learning is sort of like training your dog to do a trick. The computer learns to achieve some goal by interacting with its environment. When the computer makes a choice that brings it closer to its goal, it gets a virtual reward. Through trial and error, the computer learns to make better choices. This type of machine learning has helped computers master difficult games like Go and StarCraft II. It has also been used to teach self-driving cars how to get around.
Machine learning has helped create technology all around us. It powers language translators and search engines. When your streaming services recommend new shows you might like, that's machine learning at work. Machine learning systems also organize posts in social media feeds. They even help judge diseases. In many ways, the problem-solving power of machine learning is reshaping the world.
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