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Wassim edited this page Jul 21, 2023
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- pre-trained data baked into the model
- Context provided content as Text
- Context provided content as Embeddings
- Fine tuning
- pre-filtering and pre-analysis of local Embeddings
- Scale up all local and referenced data into a Data-Lake
- consolidate a long text into its main components
- rephrase the content in an abstracted way
- analyzing a list of posts to identify which ones were answered and which not
- analyze a list of features or requirements to identify the type and cluster them in groups
- Named Entity Recognition by identifying certain categories or tagging a special type
- identify similarities and duplicates
- identify contradictions
- identify relationships between text elements
- identify references between text elements
- search for relevant info
- provide an answer to question with a reference