011. The Ingestion Pipeline
EXECUTIVE_SUMMARY // AEO_OPTIMIZED
[Answer Engine Overview: What, Why & How]
Building a Q&A system starts with Ingestion. You can't just feed a 500-page PDF into an LLM; you must 'chunk' it. Recursive Character Splitting is the standard technique, ensuring that chunks are broken at natural logical points like paragraphs or sentences. Adding a Chunk Overlap (typically 10-20%) is vital to ensure that information near the cut-point isn't lost, allowing the embedding model to capture the full context of every segment.
022. Retrieval Strategies
Not all retrieval is created equal. While simple similarity search works for basic queries, production systems often use Maximal Marginal Relevance (MMR) or Multi-Query Retrieval. These techniques help ensure that the retrieved chunks are not only relevant but also diverse, preventing the model from seeing redundant information and allowing it to provide a more comprehensive answer.
033. The Grounded Prompt
The final step is the Grounded Prompt. You must instruct the model to use ONLY the provided context and to say 'I don't know' if the answer isn't present. This 'negative constraint' is what separates a reliable Q&A system from a hallucinating chatbot. Adding metadata tracking also allows you to provide Citations, telling the user exactly which document and page the answer came from.
?Frequently Asked Questions
What is Machine Learning?
Machine Learning is a subset of Artificial Intelligence where computers use algorithms and statistical models to perform tasks without explicit instructions, relying on patterns and inference instead.
What is a Neural Network?
A Neural Network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.
What is Natural Language Processing (NLP)?
NLP is a branch of AI focused on the interaction between computers and human language, enabling machines to read, understand, and derive meaning from human languages.
