Low-Hanging Fruit for RAG Search - jxnl.co

I think the biggest mistake around improving the system is that most people are spending too much time on the actual synthesis without actually understanding whether or not the data is being retrieved correctly. To avoid this:

• Create synthetic questions for each text chunk in your database


• Use these questions to test your retrieval system


• Calculate p

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Sounds fancy. Why do we care? GAR involves taking the source documents and having an LLM enrich them, prior to indexing. For example, the LLM might... * Generate titles for documents that are missing them * Standardize author names/formats* Extract dates, URLs, citations and other elements that might be valuable to search as separate fields* Create... See more

This begs the question: What might it mean to reimagine the form of these datasets in a world unconstrained by pressures like speed, scale, and universality? By looking to artists like Anna Ridler and others for their rejection of “off-the-shelf” datasets, we can imagine what it would be like to curate datasets with much deeper intention and contex... See more