By AsianMarketCap Official on The Capital
Artificial Intelligence (AI) and Machine Learning (ML) are two of the most popular buzzwords in this technology era and often seem to be used interchangeably.
They are not quite the same thing but such perception sometimes leads to some confusion.
What most people don’t know is that AI and ML are way more different from each other in these areas: approach, algorithms, and logical thinking.
On a broader level, we can differentiate AI and ML as:
Artificial Intelligence is a field of computer science that has an emphasis on the creation of intelligent machines that can work and react like humans. 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 using which we can create intelligent systems that can simulate human intelligence.”
Artificial Intelligence — devices designed to act intelligently — are often classified into one of two fundamental groups — applied or general.
Applied AI is far more common — systems designed to intelligently trade stocks and shares or maneuver an autonomous vehicle would fall into this category.
Generalized AI — systems or devices which can handle any task are less common, but this is where some of the most exciting advancements are happening today. It is also the area that has led to the development of Machine Learning.
Machine Learning can be defined as a subset of AI or can be termed as an application of Artificial Intelligence. In Machine Learning, machines have the ability to learn on their own without being explicitly programmed.
It allows applications to modify themselves based on data in real-time scenarios. It works on an algorithm which learns on its own using historical data. ML is being used in various places such as for online recommender systems, for Google search algorithms, email spam filter, Facebook friend tagging suggestion, etc.
After digging into the basic overview of AI and ML, here are the main differences between these two intimidating technology terms.
1. Artificial Intelligence
Ø The concept of Artificial Intelligence is broader than Machine Learning. It uses a computer to imitate the cognitive human functions.
Ø Machine Learning is a subset of AI, where machines have the ability to think and perform actions based on their past experiences. They can change the algorithm as per the data sets on which they are operating.
2. Artificial Intelligence
Ø The main aim of AI is to increase the chances of success and not accuracy.
Ø ML focuses on accuracy and patterns.
3. Artificial Intelligence
Ø AI is not a system; it can be implemented within a system to operate on computer programs that can work smart.
Ø In ML, the system can work and learn from data sets.
4. Artificial Intelligence
Ø The goal is to stimulate natural intelligence to solve complex problems.
Ø The goal is to learn from data for a certain task to maximize the performance of the machine on the task.
5. Artificial Intelligence
Ø AI is primarily used in decision-making.
Ø ML allows the system to learn from previous experiences.
6. Artificial Intelligence
Ø It develops a system to mimic humans, thus the systems can respond and behave in certain circumstances.
Ø It helps in creating self-learning algorithms.
7. Artificial Intelligence
Ø Ai will help in finding the optimal solution.
Ø ML will go after the solution, without thinking much about the optimal solution.
8. Artificial Intelligence
Ø AI leads to intelligence or wisdom
Ø ML leads to knowledge
9. Artificial Intelligence
Ø On the basis of capabilities, AI can be divided into three types: weak AI, General AI, and Strong Ai.
Ø ML can also be divided into mainly three types: Supervised learning, Unsupervised Learning, and Reinforcement Learning.
10. Artificial Intelligence
Ø AI completely deals with Structured, Semi-structured, and Unstructured data.
Ø ML deals with Structured and Semi-structured data.
In summary, Artificial Intelligence uses the experience to acquire knowledge/skill and also how to apply that knowledge for new environments. Machine Learning uses the experience to look for the pattern it learned. The fact that we will eventually develop human-like AI has often been treated as something of an inevitability by technologists. Certainly, today we are closer than ever and we are moving towards that goal with increasing speed.
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Basic Differences: Artificial Intelligence VS Machine Learning was originally published in The Capital on Medium, where people are continuing the conversation by highlighting and responding to this story.