The main difference between artificial intelligence and machine learning is: Machine learning is a subset of Artificial Intelligence that allows the computer to act and make decisions based on data to carry out a certain task.
Artificial Intelligence involves machines that operate the way humans think. Creating artificial intelligence involves creating a computer system that can execute tasks that humans do. Machine learning does the same thing, but goes one step further: it changes the behavior of your program based on what it learns. These programs or algorithms are designed in a way that they can learn and improve over time when exposed to new data.
7 Differences Between Artificial Intelligence and Machine Learning
- The goal of artificial intelligence is to increase the chances of success and not accuracy. The goal of machine learning is to increase accuracy, but success doesn’t matter.
- Artificial intelligence works like a computer program that does intelligent work. Machine learning is a simple concept machine that takes data and learns from it.
- Artificial intelligence simulates natural intelligence to solve complex problems. Machine learning learns from data about certain tasks to maximize machine performance on this task.
- Artificial intelligence is decision making. Machine learning allows the system to learn new things from the data.
- Artificial intelligence leads to the development of a system to mimic human behavior to respond in certain circumstances. Machine learning creates self-learning algorithms.
- Artificial intelligence will go to find the optimal solution. Machine learning will look for a single solution for that, whether it’s optimal or not.
- Artificial intelligence leads to intelligence or wisdom. Machine learning leads to knowledge.
Today, many companies are beginning to use machine learning capabilities for predictive analytics. As big data analytics have become more popular, machine learning technology has become more common, and is a standard feature in many analytics tools.