The Difference Between Artificial Intelligence And Machine Learning

The Difference Between Artificial Intelligence And Machine Learning

Artificial Intelligence is the future of technology. It is used in almost everything we do on a daily basis; In banking, healthcare, transportation, you name it. AI and ML are capable of predicting analyzing, image and video processing, speech recognition, and many more Although artificial intelligence and machine learning are connected there are also differences. Most people use Artificial Intelligence and machine learning as the same and don't know the difference. Here we'll talk about Artificial Intelligence and Machine learning, the application of Artificial Intelligence, and the difference between artificial intelligence and machine learning.

Artificial Intelligence is a branch of computer science whose aim is to make a computer or machine capable of imitating human behavior or intelligence. AI allows machines to think without any human intervention. It is a broad area of computer science.

Artificial intelligence is a technology in which we can create intelligent systems that can simulate human intelligence. AI covers everything related to making machines smarter and more intelligent. The Artificial intelligence system does not need to be pre-programmed, instead of that, they use algorithms that can work with their own intelligence. It involves machine learning algorithms like deep learning, neural networks.

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The concept of Artificial Intelligence first appeared in Alan Turing’s 1950 seminal work, “Computing Machinery and Intelligence”. Often considered the “father of computer science,” Turing asked in the paper the following question: “Can machines think?”. Then he described a method for testing his question, now known as the Turing Test. Read about it here

Artificial Intelligence systems fall into three types: Artificial Narrow Intelligence, Artificial General Intelligence Artificial Super Intelligence

Machine Learning (ML) is a branch of AI. Machine Learning refers to an AI system that can self-learn based on the algorithm. Systems that get smarter and smarter over time without human intervention is ML. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate results or give predictions based on that data.

Here are Forbes 5 reasons why ai and Ml should be top of mind click here

Application of Artificial Intelligence

1.E-Commerce •Virtual Personal Assistants Some examples of virtual personal assistants are, Siri, Alexa, and Google they help in discovering information when asked over voice. You can ask questions using your voice and get replies. Questions like, What's my schedule for today or what's the news headline. They find the answers and say them back to you. Machine learning is an important part of these personal assistants as they collect and refine the information based on your previous involvement with them. •Search engines •Recommendation systems •Personalized Shopping •AI-powered Assistants Language translation •Spam filter •Web feeds and post

2. Education •Creating Smart Content •Personalized Learning

3.Automobiles •Traffic Predictions: like GPS •Online Transportation Networks: estimation of prices.

4. Cyber Security •Network protection •Fraud detection •Application security

5. Robotics •In hospitals, factories, and warehouses it can be used for carrying goods. •Cleaning offices and large equipment Inventory management

6. Finance •Trading and investing •Audit •History

7. Healthcare

8. Agriculture

9. Gaming

10. Service

11. Social Media*

12. Marketing

13. Chatbots

14. Media

15. Astronomy and space activities.

16. Government

Difference between Artificial Intelligence and Machine Learning

Artificial Intelligence

•Artificial intelligence is a technology which enables a machine to simulate human behavior.

•In AI, we make intelligent systems to perform any task like a human.
•AI has a very wide range of scope.

•AI is working to create an intelligent system that can perform various complex tasks

•AI system is concerned about maximizing the chances of success.
•The main applications of AI are Siri, customer support using catboats, Expert systems, Online game playing, intelligent humanoid robots, etc.

•Based on capabilities, AI can be divided into three types, which are, Weak AI, General AI, and Strong AI.

•It includes learning, reasoning, and self-correction.

•AI completely deals with Structured, semi-structured, and unstructured data.

•Artificial Intelligence aims to create a computer that could “think” like a human person and solve complex problems.

Machine learning.

•Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.

•The goal of ML is to allow machines to learn from data so that they can give accurate output.

•In ML, we teach machines with data to perform a particular task and give an accurate result.

•Machine learning has a limited scope.

•Machine learning is working to create machines that can perform only those specific tasks for which they are trained.

•Machine learning is mainly concerned with accuracy and patterns.

•The main applications of machine learning are the Online recommender system, Google search algorithms, Facebook auto friend tagging suggestions, etc.

•Machine learning can also be divided into mainly three types that are Supervised Learning, Unsupervised Learning, and Reinforcement Learning.

•It includes learning and self-correction when introduced to new data.

•Machine learning deals with Structured and semi-structured data.

•ML helps the computer do that by enabling it to make predictions or take decisions using historical data and without any instructions from humans