AI vs. Machine Learning – Differences & Comparison

AI and Machine Learning are two well-known platforms that are widely spreading all over the world rapidly. Both of these terms are similar in many ways as well as have some key differences. The complete form of AI is Artificial Language and is the creation of intelligent machines.

Main Difference

Machine Learning is a subset of artificial intelligence that involves training models. Moreover, AI has a more extensive scope and supports a wide range of applications, while Machine Learning has not had an enormous area and keeps focus on some particular tasks.

They are interchangeable with each other. Let us discuss the main differences between AI and Machine Learning in detail to clarify the users’ confusion about both platforms.

What is AI?

AI is a short form of Artificial Intelligence and a highly demanded computer science field. It is designed to perform tasks that require human intelligence. The charges include recognizing objects in images, understanding natural language, and making decisions.

Moreover, AI has two main categories: weak AI and strong AI. Weak AI is mainly used to perform some particular tasks. At the same time, strong AI can perform all functions that human beings require. In addition,  AI has an approach to multiple techniques. Chatbots, Facial recognition, and self-driving cars are good examples of AI(artificial intelligence).

Features

  • Broad scope
  • Widely spreading
  • Cognitive computing
  • Operate independently

What is Machine Learning?

Machine Learning is a subset of artificial intelligence that involves training models. This tool teaches machines to learn data. It has an approach to statistical techniques to improve model performance. Moreover, Machine Learning can perform particular tasks.

Furthermore, it teaches without being explicitly programmed. It is a technique to achieve specific tasks and has a narrow scope. In addition, the requirements of Machine Learning are data, algorithms, and model training expertise.

Features

  • Easy to use
  • broadly spreading
  • narrow scope
  • supports a wide range of data
  • provides learning techniques

Major differences between AI and Machine Learning

  1. AI has a broad and more extensive size, while Machine Learning has a narrow area.
  2. AI is divided into Weak and Strong, while Machine Learning has no branch.
  3. The requirements of AI are domain expertise, while Machine Learning requires training model expertise.
  4. AI has an approach to multiple techniques, while Machine Learning has a policy to statistical methods.
  5. AI is a broad field of computer science, while Machine Learning is a subset of AI.

Comparison chart

Features    AI Machine Learning
Scope High scope Low scope
Type Field of computer science Subset of AI
Branches Two branches No branch
Require A large amount of data, domain expertise Algorithms and training model expertise

Conclusion

We conclude that AI and Machine Learning are two different platforms. AI has a broad scope and requires more data than Machine Learning. They provide other services and features.

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