Do you think Artificial Intelligence and Machine Learnings are the same? Or are you confused what is difference between AI and ML? So in this blog, I will make a clear what is difference between Artificial intelligence and Machine Learning is?
Artificial intelligence and machine learnings are the parts of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems. It can be said that artificial intelligence is an umbrella where machine learning consists of its small parts. AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.
Artificial intelligence is a new field of computer science that can mimic human intelligence. It is comprised of two words “Artificial” and “intelligence“, which means “a human-made thinking power.” Hence we can define it as,
Artificial intelligence is a technology that can simulate human intelligence in intelligent agents.
Read More What is Artificial Intelligence?
The Artificial intelligence system does not require to be pre-programmed, instead of that, they use algorithms that can work with their own intelligence. It involves machine learning algorithms. AI is being used in multiple places such as Siri, Google Assistant, etc.
Based on capabilities, AI can be classified into three types:
- Weak AI
- General AI
- Strong AI
Currently, we are working with weak AI and General AI. The future of AI is Strong AI that is said to be smarter than humans. Click here
Machine learning is about extracting information from data. It can be described as,
Machine learning is a subset of artificial intelligence, which enables machines to learn from previous data or to understand themselves without being clearly organized.
Machine learning allows a computer system to predict or make certain decisions using historical data without explicit editing. ML uses a large amount of systematic and fragmented data so that a machine learning model produces accurate results or provides predictions based on that data.
Machine learning works with an algorithm that learns using historical data. It only works on certain domains as when we create a machine learning model to get dog pictures, it will only give the dog image effect, but if we provide new data like a cat image it will be unresponsive. Machine learning is used in a variety of areas such as online recommendation systems, Google search algorithms, email spam filters, Facebook Auto Friend tag suggestions, etc.
It can be divided into three types:
o Supervised Learnings
o Unsupervised Learning
o Reinforcement Learnings