Artificial Intelligence (AI) vs Machine Learning
What is artificial intelligence?
Artificial intelligence is defined as the application of advanced analysis and logic-based techniques to enable machines to learn from experience—adjusting to new inputs to perform manual tasks normally performed by humans. Platforms or software imbued with artificial intelligence enables the ability to analyze an environment using either predetermined rules and search algorithms, or pattern-recognizing machine learning models, to make decisions based on those analytics.
What is machine learning?
Machine learning is a subset of artificial intelligence used in data science. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data.
Machine learning algorithms are made up of different technologies—including deep learning, and natural language processing—used in supervised and unsupervised learning, that operate using lessons from existing information. Machine learning algorithms have existed for decades, but the ability to automatically and continuously apply complex mathematical calculations to big data is a recent development in computer science.
Machine learning automates analytical model building. It uses methods from neural networks, statistics, operations research, and physics to find hidden insights in data without being explicitly programmed where to look or what to conclude.
What is the difference between artificial intelligence and machine learning?
Machine learning is a subset of artificial intelligence. In other words, all machine learning is considered artificial intelligence, but not all artificial intelligence is considered machine learning.
Other differences between artificial intelligence and machine learning include:
- The aim of artificial intelligence is to increase the chances of success and is not concerned with accuracy. While the aim of machine learning is to increase accuracy and is not concerned with success.
- The goal of artificial intelligence is to simulate intelligence in order to solve complex problems. While the goal of machine learning is to learn from data on certain tasks in order to maximize the performance of the machine on the task.
- Artificial intelligence is decision making. While machine learning is creating self-learning algorithms.
- Artificial intelligence is about finding the optimal solution. While machine learning finds the solution—whether it is optimal or not.
- Artificial intelligence leads to intelligence. Machine learning leads to knowledge.