Machine Learning vs Artificial Intelligence : Difference between ML and AI

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Machine learning and artificial intelligence are hot topics these days. All big companies are utilizing these technologies to offer the best solution to their customers. But sometimes people use these words interchangeably. In reality machine learning is a subset of artificial intelligence. In this article we will discuss the difference between Machine Learning vs Artificial Intelligence.

What is Machine Learning?

In machine learning, computer programs and machines can learn and improve by its own experience. ML is used to analyze, understand and identify a pattern in a data. It is a subset of Artificial intelligence that provides capability to a system to learn from it’s own experience.

when a known input images or structured data is provided to machine learning algorithm for training. ML program analyse the data and identify the pattern between them.

When a known input (images or structured data) is provided to machine learning algorithm for training. ML programs analyse the data and identify the pattern between them.

When machine learning algorithms is trained and new unknown data is fed to it. It can identify the pattern and predict things based on previous learning.

After training is finished. When unknown input is provided to ML algorithm. It can identify the pattern and do prediction based on previous learning. Therefore it learns from previous experience without being explicitly programmed.

What is Artificial Intelligence?

Artificial Intelligence provides machines an ability to understand and think. It is a broader term. Machine learning, Deep Learning, machine vision, robotics are subset of artificial intelligence.

Machine learning, deep learning, sensors, cloud computing, data science, internet of things and robotics technologies are various components of artificial intelligence.

Ultimate goal of AI is to enable machines to think like humans. Similar to human, AI enabled machines can do the following tasks:

  • Understand speech in the way humans listen.
  • Process images in the way humans see.
  • Read text and if required to speak the text in the way humans do. 
  • Learn from their Mistakes.

In this way Artificial Intelligent enabled systems can listen, sense and convey information, learn from mistakes like the way we humans do. For example, AI enabled Self driving cars are improving day by day.

They are learning day by day. Self driving cars utilizes machine learning, deep learning, sensors, cloud computing, data science, internet of things and robotics technologies. All of these technologies are components of AI.

Machine Learning vs Artificial Intelligence

Description Machine Learning Artificial Inteligence
Definition Computer programs / machines can learn and improve from its own experience. Artificial Intelligence provides machines an ability to understand and think.
Scope ML is a subset of AI. AI is a broader term.
Goal Ultimate goal of ML is make machines that learns from their experience. Ultimate goal of AI is to enable machines think like humans.
Data Input ML utilizes data sets to acquire knowledge and experience. AI utilizes ML, cloud computing, data science, IoT, data science and robotic technologies.
Applications ML enabled system provides insight to its user. ML applications include :

  • Share Market
  • Healthcare
  • Fraud Detection
  • Shopping Suggestions
  • Manufacturing
AI enabled system can take decisions on their own. Artificial Applications include:

Conclusion

To sum up, Ultimate aim for artificial intelligence to create machines that can think and take decisions like human beings. Whereas machine learning is a component of artificial intelligence. 

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