Artificial Intelligence (AI) and Machine Learning (ML) are the two of the most popular terms in the modern era of technology. Many people often tend to use both the terms as synonyms, as they don’t know the difference between them. However, being the part of the computer science environment based on statistics, and mathematics these two terms are actually different concepts. Therefore, it can be said that Machine Learning is a part of Artificial Intelligence, whereas Artificial Intelligence is a vast area of topics. When you sign up for AI and ML courses online, it will definitely cover the detailed difference between AI and ML.
This article will give a clear insight into the difference between Artificial Intelligence and Machine Learning, followed by some examples.
What is Artificial Intelligence?
AI or Artificial Intelligence is a field of computer science that makes a computer system that can mimic human intelligence or simply a system that can simulate human intelligence. AI is composed of two words, “Artificial” and “Intelligence,” which means a “human-made thinking power.”
What is Machine Learning?
Machine Learning, or ML, is a subset of Artificial Intelligence that enables a computer system to learn automatically using historical data without explicitly programming.
It means that all Machine Learning is AI, but not all AI is Machine Learning.
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Now, by definition, you would have understood that Artificial Intelligence and Machine Learning are different terminologies. So, now let’s understand how they work and the major differences between them.
Difference Between Artificial Intelligence and Machine Learning
Let’s go through the below-mentioned points and understand the key differences between AI & ML:
- Artificial Intelligence is a system that is built to mimic human intelligence.
- Machine Learning is a subset of Artificial Intelligence built for computer systems to learn from the inputs and data available without being programmed.
- The Artificial Intelligence system does not require pre-programmed; instead, it uses algorithms that can work with their intelligence. Basically, it includes Machine Learning algorithms like deep learning, neural network, reinforcement learning.
- Machine Learning uses a huge amount of structured and unstructured data to build a Machine Learning model that can give predictions or generate accurate results based on the data.
- Artificial Intelligence aims to make a computer system like humans to solve complex problems and are concerned about increasing the chances of success.
- Machine Learning aims to learn from data to provide accurate output, as they are mainly concerned about accuracy and patterns.
- Artificial Intelligence acts like a computer program with the objective to mimic human intelligence to find solutions for complex problems. In AI, intelligent systems are created that can perform any task like humans. AI deals with structured, semi-structured, and unstructured data, including learning, reasoning, and self-correction.
- Machine Learning uses a simple concept of collecting historical data and learning from it. ML enables systems to take in new things from the data, and that includes making self-learn algorithms. ML deals with structured and semi-structured data, which includes learning and self-correction when introduced with new data.
- The main applications of Artificial Intelligence are industrial robots, with the ability to monitor their performance and accuracy, and virtual assistants such as Siri by Apple, Alexa by Amazon, Google Home by Google, and Cortana by Microsoft. These virtual assistants help users get information, schedule emails, notify, etc.
- Machine Learning applications include an OTT recommendation system like Netflix streaming, Amazon’s shopping recommendation, Facebook friend tagging system, Google search algorithms, spam emails, and malware.
Note* – Artificial Intelligence (AI) and Machine Learning (ML) based technologies have played a crucial role during the COVID-19 pandemic. Scientists and experts used AI and ML to study the virus, diagnose individuals, analyze the public health impacts, test potential treatments, and more.
- Artificial Intelligence has a wide range of scope because it works to create an intelligent system that can perform various complex tasks.
- Machine Learning has a limited scope because machines can perform only those tasks for which they have been trained.
- Based on capabilities, Artificial Intelligence is classified into three types:
- Weak AI
- General AI
- Strong AI
- Machine Learning is divided into three types:
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
Artificial Intelligence and Machine Learning (AI & ML) sound different, but they are interconnected. To sum up, AI solves the tasks that require human intelligence, and Machine Learning solves specific tasks by learning from historical data and making predictions.
As the demand for data increases, AI and Machine Learning hold a promising future for anyone interested in playing with a variety of data and technology.