AI and ML Defined

The terms artificial intelligence (AI) and machine learning (ML) are often used interchangeably, which is understandable given their close relationship. However, they differ in scope and application.

Artificial Intelligence (AI): AI is a broad field involving technologies that enable machines and computers to mimic cognitive functions associated with human intelligence. These functions include visual perception, understanding and responding to spoken or written language, data analysis, and making recommendations. AI is not a system itself but a set of technologies implemented in systems to enable reasoning, learning, and action to solve complex problems.

Machine Learning (ML): ML is a subset of AI that allows machines to learn from data without explicit programming. It uses various models to analyze large datasets, learn from insights, and make predictions or informed decisions. ML algorithms improve performance over time as they are trained with more data.

To distinguish between AI and ML, think of AI as an umbrella term encompassing various specific approaches and algorithms. Under this umbrella are subfields such as ML, deep learning, robotics, expert systems, and natural language processing.

Generative AI: Generative AI, a subfield of AI, creates new content such as text, images, audio, and synthetic data. Google utilises generative AI in products like Google Workspace to automate tasks, such as generating document summaries. Developers can use generative AI APIs to create customised products and services. Applications of generative AI include conversational bots, content generation, document synthesis, and product discovery.