Natural Language Generation (NLG)

Natural Language Generation (NLG) is the process of using AI to produce human-like text based on structured or unstructured data. It is commonly used for report generation, content creation, and conversational AI.

Also known as: Automated content generation.

Comparisons

• NLG vs. NLP: NLG focuses on creating language output, while NLP processes and understands input language.

• NLG vs. RAG: RAG retrieves and integrates information, while NLG focuses solely on generating coherent text.

Pros

• Automated writing: Reduces manual effort for repetitive tasks.

• Personalization: Generates content tailored to specific audiences.

• Scalable: Produces large volumes of text quickly.

Cons

• Limited creativity: May lack originality or depth in generated content.

• Data dependency: Relies on quality input data for meaningful output.

Example

A news platform uses NLG to automatically create summaries of sports games, including scores, key moments, and player statistics.