CPC G06Q 10/0637 (2013.01) [G06F 11/3438 (2013.01); G06F 16/345 (2019.01); G06F 30/27 (2020.01); G06Q 30/0203 (2013.01)] | 20 Claims |
1. A method comprising:
generating, by a process based at least in part on a first set of message fragments and a plurality of user experience test result sets, a first set of automated prompts for a generative language model to generate an analysis for each user experience test result set of the plurality of user experience test result sets;
providing, by the process, the first set of automated prompts as input to the generative language model, wherein the generative language model applies at least one of a recurrent neural network or a transformer model to the first set of automated prompts;
generating, by the process based at least in part on a second set of message fragments and the analysis for each user experience test result set of the plurality of user experience test result sets, a second set of automated prompts for the generative language model to compare at least part of different analyses for the plurality of user experience test result sets;
providing, by the process, the first set of automated prompts as input to the generative language model, wherein the generative language model applies at least one of the recurrent neural network or the transformer model to the second set of automated prompts; and
presenting, within a user interface based on at least one response received from the generative language model to the second set of automated prompts, a comparison of the analysis for each user experience test result set of the plurality of user experience test result sets, wherein the comparison is used to implement at least one product design optimization to enhance user experiences with a product.
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