What Is Generative AI?
Generative AI is a category of artificial intelligence capable of creating new content—including text, code, images, and audio—by learning patterns from massive datasets.
Generative AI is a category of artificial intelligence capable of creating new content—including text, code, images, and audio—by learning patterns from massive datasets. In the context of AI engineering, it typically refers to the use of Large Language Models (LLMs) to drive intelligent applications.
Unlike traditional machine learning models that excel at pattern recognition or classification, Generative AI models are designed to predict the next token or pattern based on learned structures.
How it works
At the core of modern Generative AI are foundation models, such as Large Language Models (LLMs). These models are trained on massive datasets using a process called self-supervised learning, allowing them to understand context, nuance, and logic without explicit instructions for every task.
Realistic use cases
- Content Creation: Drafting emails, reports, and articles.
- Code Assistance: Generating boilerplate code, explaining complex logic, and debugging.
- Summarization: Reducing long documents into key actionable points.
How it differs from nearby concepts
While Generative AI is often confused with Agentic AI, the distinction is clear: Generative AI creates content, whereas Agentic AI orchestrates tools to perform actions based on that content.