Amazon Technologies, Inc.

Sandesh Swamy

Rashmi Gangadharaiah

Jonathan James Pezzino

Abhijit S Barde

A method includes accessing user trajectory information associated with a user account, wherein the user trajectory information corresponds to a first session, the first session including user interactions with a cloud computing provider, generating, by a large language model, a plurality of questions based on the user trajectory information, generating, for at least a subset of the plurality of questions, a plurality of answers corresponding to the at least the subset of the plurality of questions, wherein an answer of plurality of answers corresponds to a resource of the cloud computing provider, receiving, from a user device associated with the user account, an indication that the user account has started a second session, and responsive to receiving the indication, causing display of the at least the subset of the plurality of questions and corresponding answers on the user device.

Automatic user console question generation

Techniques for a provider network user console with a natural language querying feature. The techniques include collecting a set of templatized query pairs. A pair includes a templatized natural language query (NLQ) and a templatized domain-specific index query language query. The set of templatized query pairs is expanded by substituting named variable tokens in the templatized query pairs with synthetic values to create a set of instantiated query pairs. A pre-trained neural machine translation model is retrained using the set of instantiated query pairs to yield a fine-tuned neural machine translation model. For a natural language query received, the fine-tuned neural machine translation model is used to translate the target natural language query to a corresponding domain-specific index query language query. The domain-specific index query language query is then executed against an index to yield an index result. The techniques reduce or eliminate the need for manual training data generation.

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Sandesh Swamy