Before moving with the study of AI and ML within computer science, let’s first understand how they are interchangeably different. These days, technological advancements have been beneficiating people, helping them to work in various systems. The advanced models of Google maps, assistants, Alexa, and other applications powered by AI have changed commoners’ lifestyles. While necessity is the mother of all inventions, it brings along many drawbacks as well. The advancement of AI in technology is making people more prone to data scratching and hacking into their systems – Though that is a much broader term. Let’s look at the narrow spectrum on which AI stands with MI, making us determine how both are different.
Need information on the two fields of computer science, read our blog:-
What is Artificial Intelligence?
The term ‘Artificial Intelligence’ came to the fore in 1956 by a group of researchers, including Allen Newell and Herbert A. Simon. According to the Former-Dean of the School of Computer Science at Carnegie Mellon University, “Artificial intelligence is the science and engineering of making computers behave in ways that, until recently, we thought required human intelligence.” The AI is minded-assistant, which is upgrading our research, enhancing our ability as humans, and makes us productive in all ways.
What is Machine Learning?
According to Tom M. Mitchell: “Machine learning is the study of computer algorithms that allow computer programs to automatically improve through experience.” Under the term machine learning come three further types including:-
Supervised Learning
Unsupervised Learning
Reinforcement Learning
The Main Differences Between AI and ML
Here are the main differences between artificial intelligence and machine learning-based on various parameters include:-
- Artificial intelligence refers to the technology that simulates human behavior.
- Machine learning refers to the ability of a machine to learn from past inputs without feeding recent information.
- The goal of AI is to make a computer system smart, like a human mind.
- The goal of ML is to allow machines to learn from data and give accurate information.
- Main subsets of AI:
Machine Learning and Deep Learning
- Main Subset of ML :
Deep Learning
- AI aims to create an intelligent system with the ability to perform any tasks.
- Machine learning aims to create machines that can perform specific tasks that they get trained in.
- The main applications of AI are:-
Siri, Expert System, Online game playing, an intelligent humanoid robot, etc.
- The main applications of ML are:-
Online recommender systems, Google search algorithms, etc.
- Types of AI:-
Weak AI, General AI, and Strong AI
- Types of ML:-
Supervised Learning, Unsupervised Learning, and Reinforcement Learning
- Deals with Structured, Semi-Structured, and Unstructured Data.
- Deals With Structured and Semi-Structured Data.
