Both the terms artificial intelligence and machine learning belong to the most-used buzzwords these days.
Undeniably, both the terms artificial intelligence and machine learning belong to the most-used buzzwords these days. Almost every tech organization is using these terms when talking about their products or services. Unfortunately, there’re still lots of confusion within the common people about what are these two exactly. Let’s go through the key differences between artificial intelligence and machine learning.
- Artificial intelligence is the intelligence demonstrated by machines. Any machine that understands its environment and is able to take actions that increase its chances of achieving some goals, can be described as an artificial intelligence-enabled machine. On the other hand, machine learning is one of the present applications of artificial intelligence.
- When machine learning goes beyond simple programming and can mirror and interact with people, even on the fundamental level, artificial intelligence comes into the picture. Though artificial intelligence needs machine learning to optimize decision, the former is the step beyond the latter. Artificial intelligence utilizes what it has obtained from machine learning to simulate intelligence.
- In artificial intelligence, a machine learns by gathering knowledge and understanding how to apply it. Here, the goal is to increase the chances of finding an optimal solution. It’s the study of training computers to try to do things which a human can do better at present. On the contrary, in machine learning, algorithms obtain the skill or knowledge via experience. It depends on big datasets to keep on reminding the data to identify common patterns.
- Based on capabilities, artificial intelligence can be distributed into two categories namely general AI and narrow AI. Based on learning methods, Machine learning can be distributed into three categories namely supervised learning, unsupervised learning, and reinforcement learning.
- The objective of artificial intelligence to develop smart systems like humans that can solve complex problems. The goal of machine learning is to let a machine learn from massive datasets so that they can provide accurate output.
- The key applications of artificial intelligence include customer support using chatbots, Siri, intelligent humanoid robot etc. The key applications of machine learning include Google search algorithms, online recommender system, Facebook friend tagging suggestions etc.
- Artificial intelligence holds a broad range of scope while machine learning comes with a limited scope.
- Artificial intelligence deals with structured, unstructured, and semi-structured data while machine learning works with only structured, and semi-structured data.
Trending AI Articles:
1. Machine Learning Concepts Every Data Scientist Should Know
3. AI Fail: To Popularize and Scale Chatbots, We Need Better Data
Both machine learning and artificial intelligence can leave valuable business implications. In the context of the coming future, both are imperative to our society. A robust understanding of both of these fields will be extremely important to comprehend the rapidly changing business world and how the devices we use everyday work. The promises and value of both these fields are being materialized because of each other.
If you’re an aspiring candidate looking to step into these fields, this is probably the best time to begin your journey. As advancements and adoptions of both artificial intelligence and machine learning continue to accelerate, one thing can be assumed for sure — the impact will be profound.
What are the main differences between artificial intelligence and machine learning? was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.
365 Data Science 