ML and AI are two very popular terms in our modern world full of the newest technologies and innovations.
Nowadays, there are many AI ML platforms crafted to improve our lives and make complex computer systems do almost everything.
Of course, both these terms are based on math and statistics, but these are not the same subjects at all.
In our article, we are going to explain the main differences between these terms to clear up any misunderstandings.
People use these terms without knowing what each of them means exactly.
What Is Artificial Intelligence?
AI is a quite complex computer system that works almost like a human’s brain.
This is a very popular technology in our world where people develop various software and devices which simulate the work of a human brain.
This system does not require any pre-programming, but it should have some algorithms that can work using their intelligence.
In our everyday life, we use it on the phone when we talk to Siri or AlphaGo, launch Chess playing, and many other examples.
If to classify AI, it can be divided into 3 main groups:
- Weak level of intelligence
- General level of intelligence
- Strong level of intelligence
Nowadays, people only work with two first levels.
The future is a strong level that should be more intelligent than we are!
What Is Machine Learning?
ML means getting knowledge from any certain data.
Thanks to it, any machine can learn from any previous experience or any data without any pre-programming.
So, it’s a sort of subfield of Artificial Intelligence that forces any computer system to make a decision or a prediction without any previous programming.
ML uses a great amount of well-structured data, and a ML model generates the result that is based exactly on this data.
Macchine learning works on specific algorithms – just like if you were creating a ML model to detect images of parrots, it will provide results for parrots pics, but if you offer any unknown data like a mouse image, a system will not give any response.
ML is used in different systems, for example, spam filters for emails, browser search algorithms, Facebook suggestions, and many else. ML can be divided into 3 main groups:
- Supervised ML
- Reinforcement ML
- Unsupervised ML
Differences Between AI and ML
Let’s discover the main differences between these terms:
- AI is a technology that simulates human intelligence, and ML is a subfield of AI that allows learning from past experience or data without pre-programming.
- Artificial Intelligence’s main goal is to create a smart computer system that works like a human brain to solve various problems. The ML’s goal is to get knowledge from data and give an accurate response.
- AI requires creating intelligence systems to solve problems like a human. ML helps to teach machines to make a particular task and get a clear result.
- ML is a main subfield of AI, and deep learning (DL) is a subset of ML.
- Artificial intelligence has a great range of scope when machine learning’s scope is very limited.
- People use AI to make a smart system that can solve various complex problems and tasks. ML is teaching machines to solve particular tasks.
- AI works to maximize the chances of success when ML is concentrated on accuracy.
To sum up, artificial intelligence is a very complex computer system.
This system is for the work with complex tasks that require making difficult decisions.
The decisions with an instrument similar to human intelligence.
Machine learning on the other hand is a subfield of AI that teaches machines to make predictions.
Also, it provides accurate results learning on specific data or experience.
It means that all ML is artificial intelligence, but not all AL is ML.
Petr is a serial tech entrepreneur and the CEO of Apro Software, a machine learning company. Whenever he’s not blogging about technology for itechgyan.com or softwarebattle.com, Petr enjoys playing sports and going to the movies. He’s also deeply interested in mediation, Buddhism and biohacking.