技術

Retrieval-Augmented Generation (RAG)

定義

A technique that enhances LLM responses by retrieving relevant information from external knowledge sources before generating a response. RAG improves accuracy, reduces hallucinations, and enables LLMs to access up-to-date information without retraining.

例

Enterprise knowledge base chatbots
Customer support automation

関連用語

Large Language Model (LLM)

AI models trained on vast amounts of text data that can understand and generate human-like text. Examples include GPT-4, Claude, and Llama. LLMs power modern chatbots, content generation, and code assistance tools.

Vector Database

A specialised database designed to store and efficiently search high-dimensional embedding vectors using approximate nearest-neighbour algorithms. Vector databases are the infrastructure backbone of RAG systems and semantic search applications.

Embedding

A numerical representation of data (text, images, etc.) in a high-dimensional vector space where semantically similar items are mathematically close together. Embeddings are the foundational building block for semantic search, RAG pipelines, and recommendation systems.

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Retrieval-Augmented Generation (RAG)

定義

例

関連用語

Large Language Model (LLM)

Vector Database

Embedding

関連サービス

AIの理解にお困りですか？

Retrieval-Augmented Generation (RAG)

定義

例

関連用語

Large Language Model (LLM)

Vector Database

Embedding

関連サービス

AIの理解にお困りですか？