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3 Differences Between Artificial Intelligence And Machine Learning

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There is a lot of buzz around Artificial Intelligence and Machine Learning lately. But what exactly are they, and what separates them from each other? In this article, we will explore the key differences between AI and ML.

The first one is that Artificial Intelligence is a subset of Machine Learning. AI is the process of making a computer system “smart” — that is, able to understand complex tasks and carry out complex commands.

ML, on the other hand, is a method of teaching computers to learn from experience. It involves feeding large amounts of data into a computer system, which then analyzes and learns from it.

The second key difference between AI and ML is their purpose. AI is mainly used for problem-solving tasks, while ML is mainly used for prediction tasks.

AI can be applied to any problem that requires a computer system to make decisions, such as predicting stock prices, diagnosing diseases, and even driving cars. ML is also used in many fields like speech recognition, handwriting recognition, and image classification.

The third key difference between AI and ML is the time frame they operate under. AI works within a specific set of boundaries (known as an AI sandbox), while ML operates without any constraints whatsoever. In other words, you could say that Artificial Intelligence has rules but doesn’t necessarily follow them; whereas with ML there are no rules at all.

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