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AssigneeOracle International Corporation
InventorsVineela Sesh Mannepalli, Veda Sruthi Bondada, Pyay Aung San, Jeffrey Thomas Colvard, Yogendra Swami, Forrest Elliott, Alexander Nathan Lederman, Ajit Kumar Das, Sravan Maringanti, Peter Weiss, Alasdair John Joseph Bailey, Caitlin Moran, Sripranav Kumar Muktevi
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Techniques for triggering regeneration of content by a generative AI model based on changes to stored data are disclosed. A system inputs a prompt to a generative AI model to generate content based on a target data set stored at a memory location. The system monitors the target data set to detect changes to the target data set. Responsive to detecting changes to the target data set, the system triggers the generative AI model to generate updated content based on the updated version of the target data set that is currently stored at the memory location. For example, in the context of project proposal generation, when details such as scope, timelines, or budget are updated to the underlying dataset, the system automatically regenerates the proposal content using a generative AI model. This enables organizations to deliver timely, accurate, high-quality proposals to prospective customers, increasing the likelihood of winning deals.
One or more non-transitory computer readable media comprising instructions which, when executed by one or more hardware processors, cause performance of operations comprising:
A method comprising:
A system comprising:
Dependencies are inferred from the claim text.