Difference Between AI and Machine Learning.

Difference Between AI and Machine Learning

Artificial Intelligence and Machine Learning are two important parts of Computer Science that are interconnected with one another. Both technologies are seeing increasing recognition in the 21st century as they are being used to create intelligent systems.

Although both technologies are related to each other and people sometimes use the terms interchangeably, AI and Machine Learning are quite different and have specific use cases.

On a broad and superficial level, we could distinguish AI and Machine Learning as the following:

AI is an idea to create Intelligent Machines which can mimic human thinking capability and behavior, whereas, machine learning is a program or subset of AI that enables machines to learn from information without being programmed explicitly.

Below we mention some of the main differences between AI and Machine Learning along with an overview of them both.

Artificial Intelligence

Artificial intelligence is a field of computer science that creates a computer system that is capable of mimicking human intelligence. The word Artificial Intelligence is comprised of two phrases “Artificial” and “Intelligence”, which essentially translates to “a human-made thinking power.” Hence we can define it as,

Artificial Intelligence is a technology with the help of which we can create intelligent systems that could mimic human intelligence.

The Artificial Intelligence program does not need to be pre-programmed, rather than that, they use such algorithms which can work with their own intelligence. It involves machine learning algorithms such as Reinforcement Learning algorithm along with deep learning neural networks. AI is being used in various digital inventions like Siri, Google’s Alpha Go, and AI in chess games, etc.

An Artificial Intelligence program does not need to be pre-programmed to adapt to new circumstances as it would depend upon algorithms that would aid it in improving its own intelligence. They would employ machine learning algorithms such as reinforcement learning along with deep learning neural networks. AI is currently being used in various digital inventions like Siri, Google’s Alpha Go and AI in chess games, etc.

Based on their working capabilities, AI can be classified into following three categories:

  • Weak AI
  • General AI
  • Strong AI

Currently, we are using Weak AI and General AI in modern day society. The future of AI is in Strong AI, which is defined as being more intelligent than humans.

Machine learning

Machine learning is all about learning from the data. It can be defined as,

“Machine learning is a branch of artificial intelligence, which enables machines to learn from past data or experiences without being programmed.”

Machine learning enables a computer system to predict something or take a key decision by using historical data rather than being directly programmed. Machine learning uses a massive amount of structured and semi-structured data so that accurate results can be generated or predicted based on historical data.

Machine learning works using algorithms that have an ability to learn on their own by using historical data. They work only for the specific task for which they have been set up for. For example, if we built a model to detect pictures of cats but instead provided images of dogs then the algorithm would not be able to adapt. Machine learning is being used in various platforms such as for online recommendation systems, Google’s search algorithms, email spam filters, Facebook’s auto friend tagging system, etc.

Machine Learning can be divided into three types:

  • Supervised learning
  • Reinforcement learning
  • Unsupervised learning

Key differences between AI and Machine learning:

Artificial Intelligence Machine Learning
Artificial Intelligence is a technology that employs machine learning to mimic human behavior. Machine learning is a part of AI that allows a machine to learn automatically from past data without additional programming.
The goal for AI is to develop a smart computer system (like a human being) to solve complex problems. The goal of ML is to allow machines to learn from data provided to them to give an accurate outcome.
In AI, intelligent systems are developed to perform any task as well as a human or even better. In ML, we teach machines by providing them with the data to perform a particular task and get an accurate outcome.
Machine Learning and deep learning are the two main branches of AI. Deep Learning is the main branch of ML
AI is about developing intelligent computer systems which can solve multiple complex problems in a better way than human beings. MI is about creating machines that can perform specific tasks for which they are trained.
AI is all about learning, reasoning and self-correction. ML includes self-learning when a new set of data is given to it.

 

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