New generative artificial intelligence technologies such as OpenAI’s ChatGPT, Microsoft’s Bing and Google’s Gemini (formerly called Bard), have taken the world by storm, promising to disrupt every industry. However, AI and machine learning have been in use in a wide range of industries, from IT to manufacturing to finance, for decades.

As companies rush to adopt new AI solutions, leaders must understand the different types of AI and how AI compares to ML.

In this TechRepublic Premium guide, let’s look at what AI and ML are, the different types of both technologies, their use cases and how they compare.

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THE DIFFERENT TYPES OF AI

There are many different ways to classify AI, but commonly AI is divided into four main categories that describe how advanced the system is:

Narrow or reactive AI: Narrow AI systems are designed to perform a specific task or set of tasks. For example, a narrow AI system might be designed to play chess, translate languages or diagnose diseases.

Narrow AI is also known as reactive AI. This AI excels in simple classification and pattern recognition tasks. They are used in scenarios where all parameters are known and outperform humans in these specific tasks because of calculation speed. However, these models are limited to a narrow scenario and use.

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