Machine Learning(ML) and Artificial Intelligence(AI) are two closely related but distinct field within the broader field of computer science. Machine Learning(ML) and Artificial Intelligence(AI) re interchangeably, especially when discussing big data, predictive analytics, and other digital transformation topic. Below are some main difference between Machine learning and Artificial Intelligence along with the overview of Artificial intelligence and Machine learning.
What is AI?
The term artificial intelligence or AI, refer to the process by which a machine simulates cognitive processes like learning and problem solving that people identify with the minds of other people. Even more basic, artificial intelligence(AI) can only be a set of rules that are written into machine to instruct it how to act in particular scenarios. Put differently, Artificial intelligence is limited to a sequenced of if then statement.
What is ML?
With the use of past data and machine learning, a computer system can be explicitly developed to make predictions or execute certain actions. To enable a machine learning model to produce accurate results or make predictions based on the data, machine learning needs a vast amount of structured and semi structured data. Algorithms used in machine learning use past data to learn their own. Only certain domains are supported by it. For example, if we build a machine learning model to identify dog photos, it will only return results for dog photographs. If we feed it additional data, such as cat image, it will stop responding. Numerous applications, including online recommender systems, Google search engines, email spam filters, Facebook auto friend tagging suggestions, and more use machine learning.
Machine Learning Vs Artificial Intelligence
1. Stands
ML stands for Machine Learning, and is the study that uses statistical methods enabling machines to improve with experience. On the other hand, AI stands for Artificial Intelligence, and is basically the study/process which enables machines to mimic behavior through particular algorithm.
2. Goal
The goal of machine learning is to allow machines to learn from data so that they can give accurate output. The goal of Artificial Intelligence is to make a smart computer system like humans to solve complex problems.
3. Terminology
The terminology Machine learning was first used in 1952 by IBM computer scientist Arthur Samuel, a pioneer in artificial intelligence and computer games, The terminology Artificial Intelligence was originally used by John McCarthy in 1956, who also hosted the first AI conference.
4. Aim
The Aim of ML is to increase accuracy, but it does not care about, the success. While The Aim is to AI is to increase the chance of success and not accuracy.
5. Subset
ML is the subset of AI, AI is the broader family consisting of ML and DL as it's components.
6. Algorithm
ML is an AI algorithm which allows system to learn from data, whereas AI is a computer algorithm which exhibits intelligence through decision making.
7. Work
ML can only use structured and semi structured data, AI work with all types of data such as Structured, Semi structured and unstructured.
8. Use
ML system relay on statistical models to learn and can self correct when provided with new data, AI systems use logic and decision trees to learn, reason and self correct.
9. Application
The main applications of ML are online recommender system, google search algorithms, Facebook auto friend tagging suggestions, In contrast, The main application of AI are Siri, Customer support using catboats, Online game playing, Expert system, Intelligent humanoid robot etc.
10. Scope
The Scope of ML is Limited, AI has a very wide range of scope.
11. Allow
ML allows system to learn new things from data, AI is decision making.
12. Efficiency
ML is less efficient than DL as it can't work for longer dimensions or higher amount of data. The efficiency of AI is basically the efficiency provided by ML and DL respectively.
13. Types
Machine learning can divided into mainly three types are supervised learning, unsupervised learning and reinforcement learning. On the other hand AI can be divided into three types, which are weak AI, general AI and Strong AI.
14. Concern
Machine learning is mainly concerned about accuracy and patterns. AI system is concerned about maximizing the chances of success.