Chunking is the process of breaking down large pieces of text into smaller, manageable sections (chunks) to facilitate easier processing and analysis by AI models. This helps in improving the performance of tasks like summarization, retrieval, and text generation.
- Glossary > Letter: C
What does "Chunking" mean?

Use Cases
Document Analysis:
Breaking down long documents into sections for summarization or extraction of key information.
Search Optimization:
Improving the accuracy of search results by indexing smaller text chunks.
Text Generation:
Generating text in smaller sections to maintain coherence and relevance.

Importance
Efficiency:
Makes large volumes of text more manageable for AI models.
Accuracy:
Enhances the accuracy of tasks like summarization and retrieval by focusing on smaller, more relevant sections of text.
Performance:
Improves the overall performance of AI models by reducing the complexity of processing large texts.

Analogies
Chunking is like dividing a large book into chapters and sections, making it easier to navigate and understand
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