With all the trending technologies available today, few get as much buzz as AI and machine learning. Scientists, engineers, and executives alike are extremely wary and excited about these technologies due to the vast societal impact they will have. Although they are different, they are mistakenly used interchangeably. In this post, we will cover what AI and machine learning are and the key differences that distinguish the two technologies from each other.


What is AI?

Artificial intelligence is systems or machines that mimic human intelligence to perform tasks. AI relies on algorithms and real-time data to make decisions. There are several categories of AI like general AI (AI designed to learn) and narrow AI (specific AI for narrowly defined tasks). Most references of AI in a business context refers to narrow AI. This includes software and programs that help automate repetitive tasks in business operations.


What is machine learning?

Machine learning is a branch of AI which focuses on using data and algorithms to perform tasks. With machine learning, the more data it processes, the more accurate its decision-making is. There are a variety of machine learning use cases depending on your industry. Some prominent examples that you might be familiar with include chatbots, image recognition, fraud detection and more.


Main differences between AI and machine learning


Although there’s significant overlap between them there are several key differences. Some of the main differences include:

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Machine learning is a subset of AI: Machine learning is a branch within AI and it focuses on learning from data without being explicitly programmed. Instead of focusing on increasing the general capabilities of general AI, machine learning focuses on utilizing data to improve the decision making of systems within businesses.


Scope: Machine learning has a limited scope in comparison to AI. With machine learning, machines are equipped with data to give faster and more accurate results. It’s very task-specific while AI is broad in nature. AI focuses on solving the larger problem of general intelligence. As AI develops more, its cognitive capacity increases, and it can solve more complex issues.


Reasoning: Another key difference is the ability to use reasoning. Machine learning focuses on learning from data to make better predictions and decisions for its given objectives. Machine learning cannot reason further than the data is provided. In contrast, AI focuses on problems that require human intelligence. This means that AI can think and problem solve like a regular human; this can lead to the AI making inferences, reasoning using unrelated concepts and more. As AI develops further, it will start reasoning beyond the limitations of human reasoning to gain further insights on complex problems.


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