US 12,769,987 B2Granted

Synchronization system for generative artificial intelligence recommendation systems

AssigneeIntuit Inc.

InventorYaakov Tayeb

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Abstract

Systems and methods for a tunable synchronization network configured to facilitate communication between recommendation systems and generative artificial intelligence systems to generate custom content that is unique to each user. The systems and methods leverage a novel framework including a natural language processing transformer that includes a synchronization layer that can trained to generate profile vectors and a vector translator configured to translate intensity values from profile vectors cells to generate prompts for generative artificial intelligence systems. Notably, this novel framework is agnostic to both the recommendation systems and generative artificial intelligence systems that are used.

Claims16

Dependent claims

A system comprising:

at least one processor;
and
at least one non-transitory computer readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform processing comprising:
receiving a user ID and an item;
generating a profile vector associated with the user ID and the item, wherein the profile vector includes data indicative of one or more tones and one or more emotions;
configuring a translator to translate the data;
generating training profile vectors by determining at least a number of cells in the profile vector assigned intensity values associated with the of one or more tones and the one or more emotions, wherein the profile vector includes an array of cells, wherein each cell is assigned a numerical value associated with an intensity value of either the one or more tones or the one or more emotions;
translating, via the translator, the training profile vectors into one or more training vector descriptions;
generating one or more training prompts that include data from the one or more training vector descriptions, wherein the one or more training vector descriptions represent the numerical value associated with the intensity value in textual form;
generating, via a generative artificial intelligence model, one or more training items responsive to the one or more training prompts;
inputting, the one or more training items as input and the training profile vectors as labels, into a natural language processing model that includes a synchronization component;
and
adjusting the natural language processing model to minimize a difference between the training profile vectors and output from the synchronization component and optimize the natural language processing model for a user associated with the user ID.

10 more elements

Dependencies are inferred from the claim text.