We all know that Artificial Intelligence (AI) and Machine Learning (ML) are the two buzz words on the internet. But most people don’t know the difference between AI and Machine Learning.
And quite often there seems to be confusion among both and used interchangeably. In this article, we will be clearing the confusion by telling the difference between AI and Machine Learning.
But first, we’ve to understand the basic definition of Artificial Intelligence(AI) and Machine Learning(ML) before we compare AI vs ML.
What is the definition of AI vs ML?
There are many variations of definition for AI and ML on the internet. We have summed the simple definition of both the terms.
Definition of AI:
It is the study of how to train the computer to perform a task better than humans.
Definition of ML:
Machine Learning is the study of computer algorithms that allow computer programs to automatically improve through experience.
Machine Learning is the science of getting computers to learn better than humans with the provided data. And Machine Learning is the branch of AI as defined by Computer Scientist and Machine Learning pioneer Tom M. Mitchell.
Diving into AI and ML Definitions
Now that we learned the basic definition of AI and ML, let’s look into their deeper definitions.
What is Artificial Intelligence(AI)?
AI is the general way to think about the most advanced computer with intelligence. AI can be a computer program that plays a game of poker and voice recognition systems like Siri, interpreting and responding.
There are three groups in Artificial intelligence (AI) they are:
- Artificial General Intelligence(AGI)
- Narrow AI and
- Superintelligent AI
Artificial General Intelligence(AGI) is an AI that is considered to be at a human level that can perform a different set of tasks. In 1996 IBM’s Deep Blue beat the grandmaster chess champion Garry Kasparov and in 2016 it beat Lee Sedol. This is the example of Narrow AI.
Superintelligent AI takes things to a whole new level. It is when the machines have outsmarted us. According to Nick Bostrom, “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom, and social skills.”
What is Machine Learning(ML)?
As mentioned earlier, Machine Learning is a subset of AI. In Machine Learning the machine takes the data and then learns for themselves.
It is currently one of the most promising tools in the AI kit for business. ML can quickly adapt the knowledge and train themselves to perform better. Some of the well-known fields where ML excels are as below:
- Object recognition
- Facial recognition
- Speech recognition, etc.
By using Machine Learning, computers can learn to recognize the patterns on their own and make accurate predictions.
Some of the major companies that use AI and Machine Learning every day are Microsoft, Google, IBM, Amazon, etc.
5 Difference between AI and Machine Learning
Now that we know the definition of AI and ML, let’s understand the key difference between AI and Machine Learning.
|Artificial Intelligence||Machine Learning|
|Goal of the AI is to increase the chance of success.||Goal of ML is to increase the accuracy of the task.|
|A computer program that does computer task in an intelligent way.||In ML, the computer is fed with the data and learn from it.|
|AI behaves as natural as human intelligence to solve complex problem.||ML learns from the data that is fed to computer program to increase the performance of the task.|
|AI will make decisions.||ML learns new things from the data.|
|It is designed to mimic human behaviour.||It creates its own algorithms by self learning.|
In conclusion, there is a major difference between AI and ML that one has to learn before diving into the subject. Well, I hope this article was clear in helping you understand the key difference between AI and ML.
Also, check out the best resources to learn Machine Learning to improve your career.
Help your friends and colleagues by sharing this difference with them.