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Artificial Intelligence Versus Machine Learning

Do you think Artificial Intelligence and Machine Learnings are the same?  Or are you confused what is difference between AI and ML? So in this blog, I will make clear the difference between Artificial intelligence and Machine Learning is.

Artificial intelligence and machine learnings are the parts of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems. It can be said that artificial intelligence is an umbrella where machine learning consists of its small parts. AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior. Machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.



Artificial Intelligence

Artificial intelligence is a new field of computer science that can mimic human intelligence. It is comprised of two words “Artificial” and “intelligence“, which means “a human-made thinking power.” Hence we can define it as,

Artificial intelligence is a technology that can simulate human intelligence in intelligent agents.

Read More What is Artificial Intelligence?

The Artificial intelligence system does not require to be pre-programmed, instead of that, they use such algorithms which can work with their own intelligence. It involves machine learning algorithms. AI is being used in multiple places such as Siri, Google Assistant etc.

Based on capabilities, AI can be classified into three types:

  • Weak AI
  • General AI
  • Strong AI

Currently, we are working with weak AI and General AI. The future of AI is Strong AI that is said to be smarter than humans.

Machine Learning

Machine learning is about extracting information from data. It can be described as,

Machine learning is a subset of artificial intelligence, which enables machines to learn from previous data or to understand themselves without being clearly organized.

Machine learning allows a computer system to predict or make certain decisions using historical data without explicit editing. ML uses a large amount of systematic and fragmented data so that a machine learning model produces accurate results or provides predictions based on that data.
Machine learning works with an algorithm that learns using historical data. It only works on certain domains such as when we create a machine learning model to get dog pictures, it will only give the dog image effect, but if we provide new data like a cat image it will be unresponsive. Machine learning is used in a variety of areas such as online recommendation systems, Google search algorithms, email spam filters, Facebook Auto Friend tag suggestions, etc.
It can be divided into three types:
o Supervised Learnings
o Unsupervised Learning
o Reinforcement Learnings

Artificial Intelligence Versus Machine Learning

AI vs ML
AI vs ML

Key differences between Artificial Intelligence (AI) and Machine learning (ML):

Artificial Intelligence Machine learning
Artificial intelligence is a technology that enables a machine to simulate human behavior. Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.
The goal of AI is to make a smart computer system like humans to solve complex problems. The goal of ML is to allow machines to learn from data so that they can give accurate output.
In AI, we make intelligent systems to perform any task like a human. In ML, we teach machines with data to perform a particular task and give an accurate result.
Machine learning and deep learning are the two main subsets of AI. Deep learning is the main subset of machine learning.
AI has a very wide range of scope. Machine learning has a limited scope.
AI is working to create an intelligent system that can perform various complex tasks. Machine learning is working to create machines that can perform only those specific tasks for which they are trained.
AI system is concerned about maximizing the chances of success. Machine learning is mainly concerned with accuracy and patterns.
The main applications of AI are Siri, customer support using catboats, Expert System, Online game playing, an intelligent humanoid robot, etc. The main applications of machine learning are:

Online recommender system, Google search algorithms, Facebook auto friend tagging suggestions, etc.

On the basis of capabilities, AI can be divided into three types, which are,

Weak AI,

General AI,

Strong AI.

Machine learning can also be divided into mainly three types that are

  1. Supervised learning,

      2 . Unsupervised learning,

      3. Reinforcement learning.

It includes learning, reasoning, and self-correction. It includes learning and self-correction when introduced with new data.
AI completely deals with Structured, semi-structured, and unstructured data. Machine learning deals with Structured and semi-structured data.

Noor Ahmad Haral

Passionate Machine Learning Engineer interested in Tech innovations, GPT, Blogging and writing almost everything.

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