Real ChatGPT answer · index seedJ79MqrvMLwwcompleteB2B software · AI and automation toolsinformational
Is it difficult to fine tune an open source model on our own company documents for internal search?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Is it difficult to fine tune an open source model on our own company documents for internal search?
1 real search · 1 real-search pass
RAG versus fine-tuning enterprise internal document search architecture permissions evaluation open source models guidanceGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
RAG versus fine-tuning enterprise internal document search architecture permissions evaluation open source models guidance Google ↗
- How to Build an Enterprise RAG Architecture (Retrieval Augmented Generation) · chmit.tech
- AWS Prescriptive Guidance - Retrieval Augmented Generation options and architectures on AWS · docs.aws.amazon.com
- Enterprise RAG: Architecture, Security, and How to Evaluate It · voiceflow.com
- Fine-tuning vs. RAG · d1.awsstatic.com