Today, we use smartphones, watch Netflix, or scroll through the rabbit hole of social media daily. But did you ever notice you are using collaboratively artificial intelligence (AI) and machine learning (ML) while doing those activities? 

Even if you did not realize those platforms use AI and ML to do things that need human interactions without using any human help.

AI is making a big impact on our world in so many ways. It can understand languages, recognize pictures, make choices, and learn from information using machines and software. 

But how does AI actually work? 

How can machines or software figure things out and do complex tasks without being told exactly what to do? 

The key is machine learning. It is a part of AI that creates algorithms that can learn from data and get better and better at what they do. In this article, we will dive into the relationship between these two concepts.

The Role of MNachine Learning in Artificial Intelligence

What is Artificial Intelligence? 

It is a type of computer science, and it focuses on making machines that can think and act like humans. This means that AI systems can learn from what they have done in the past, understand 

what people are saying, figure out patterns, and make choices.

What is Machine Learning(ML)? 

ML is a part of AI that lets computers learn on their own without someone telling them exactly what to do. Machine learning algorithms can look at data, find patterns, and make predictions or suggestions all by themselves.

Since machine learning is a part of AI, all machine learning algorithms are AI systems. However, all AI systems do not use machine learning. Some AI systems use other methods, like logic, rules, or knowledge bases, to do things that usually require human intelligence.

Furthermore, machine learning has become the most popular way to make AI systems in recent years. It is really good at dealing with complex and changing problems that are tough or impossible to solve using traditional methods. Machine learning algorithms can learn from lots of data, adapt to new environments, and improve as they go. 

They can even do things that are beyond human abilities, such as,

  • Analyze billions of web pages.
  • Play chess or go at superhuman levels.
  • Create realistic images or text.

Are Machine Learning and Artificial Intelligence Related?

As we discussed, machine learning is one of the key technologies that make AI work. AI systems can learn from data and get better and better using machine learning algorithms. It is like how we learn from our experiences and improve over time. This lets them make more accurate predictions or decisions and adapt to new situations.

For example, let us say we want an AI system to recognize pictures of cats. Obviously, we can use a machine learning algorithm to analyze many cat pictures and learn the features all cats have in common, like their shape, size, and color. Once the AI system has learned these features, it can use them to recognize new cat pictures it has not seen before.

How is Machine Learning Used in the Real World?

The connection between machine learning and AI has resulted in some amazing inventions that are benefiting tons of industries and applications in the real world today.

Entertainment

Machine learning algorithms can recommend movies, songs, books, or products that match your tastes and behavior. For instance, Netflix uses machine learning to suggest shows or movies you might like based on your viewing history and ratings.

Health care

Machine learning algorithms can diagnose illnesses, spot anything unusual, predict what might happen, or suggest treatments based on medical images, records, or sensors. 

For example, Google’s DeepMind made a machine-learning algorithm that can detect eye diseases like diabetic retinopathy or glaucoma just by looking at retina scans.

Education

Machine learning algorithms can make learning content just for you, check how you are doing, give you feedback, or even tutor you based on what you are good at and want to achieve. For example, Duolingo uses machine learning to make its language lessons fit each learner’s level and what they like.

Business

Machine learning algorithms can improve processes, improve customer service, find fraud, predict demand, or analyze how customers behave using different data sources. For example, Amazon uses machine learning to make its delivery routes better, improve how you search for products, and provide customer support through chatbots.

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Conclusion

Machine learning is a part of AI. It focuses on making algorithms that can learn from data. These algorithms let AI systems get better over time by learning from their experiences. Machine learning and AI are not the same thing, but they are closely related and often used together to make smart machines that can think and act like humans.