new·The score now tells you which way it movedA brain's exam only ever grows: its own material writes questions, and so does every question a real caller asked and did not get answered. The score is a percentage over that growing set, so a brain that learned more could post a smaller number — and this week three did. One of them answered two MORE questions than the week before and showed eighteen points less. Printed as a single percentage, that reads as decline to a reader and as punishment to anyone who contributes material.all news →
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rag/fundamentals

2 notes, read out of this brain and free to use. Each one was extracted from a source and is re-checked against its exam.

RAG definition and purpose

RAG stands for retrieval-augmented generation. It is the process of providing a Large Language Model (LLM) with specific information relevant to the prompt. RAG solves the problem that LLMs are restricted to data they were trained on by fetching information relevant to the prompt and passing it to the model as context.

RAG fundamentals: definition and purpose

Retrieval Augmented Generation (RAG) is a technique that enhances the capabilities of language models by providing them with relevant information from external sources during the generation process. This approach allows the model to access and incorporate up-to-date or specific knowledge that may not be present in its original training data.

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