公开(公告)号：US12265899B2

公开(公告)日：2025-04-01

申请号：US18328041

申请日：2023-06-02

Applicant: INTUIT INC.

Inventor： Terrence J. Torres ,  Tharathorn Rimchala ,  Andrew Mattarella-Micke

IPC: G06N20/20 ,  G06F40/126 ,  G06F40/284

Abstract: A machine learning system executed by a processor may generate predictions for a variety of natural language processing (NLP) tasks. The machine learning system may include a single deployment implementing a parameter efficient transfer learning architecture. The machine learning system may use adapter layers to dynamically modify a base model to generate a plurality of fine-tuned models. Each fine-tuned model may generate predictions for a specific NLP task. By transferring knowledge from the base model to each fine-tuned model, the ML system achieves a significant reduction in the number of tunable parameters required to generate a fine-tuned NLP model and decreases the fine-tuned model artifact size. Additionally, the ML system reduces training times for fine-tuned NLP models, promotes transfer learning across NLP tasks with lower labeled data volumes, and enables easier and more computationally efficient deployments for multi-task NLP.

公开(公告)号：US12265794B2

公开(公告)日：2025-04-01

申请号：US18482783

申请日：2023-10-06

Applicant: INTUIT INC.

Inventor： Rami Cohen ,  Noa Haas ,  Oren Sar Shalom ,  Alexander Zhicharevich

IPC: G06F40/30 ,  G06N20/20 ,  G10L15/26 ,  H04M3/51

Abstract: A computing system identifies an incoming voice call from a user device to an agent device associated with the computing system. The computing system generates a transcription of the incoming voice call using one or more natural language processing techniques. The computing system extracts a problem description from the transcription. The problem description indicates a topic for the incoming voice call. A first machine learning model estimates a situation vector from the problem description. A second machine learning model identifies a pre-existing situation vector that closely matches the estimated situation vector. The computing system retrieves a situation description that corresponds to the identified pre-existing situation vector.

公开(公告)号：US20250103795A1

公开(公告)日：2025-03-27

申请号：US18475388

申请日：2023-09-27

Applicant: INTUIT INC.

Inventor： Subrata SANTRA

IPC: G06F40/166 ,  G06F40/40 ,  G06N3/09

Abstract: A method for automatically generating content for a document for an individual includes providing input data to a trained artificial intelligence model. The input data includes a plurality of input features specific to the individual, and the trained artificial intelligence model is trained through a supervised learning process using training data that includes a plurality of input features for each of a plurality of individual other than the individual for whom the document is being created. The method includes receiving output data from the artificial intelligence model that is based, at least in part, on the input data and includes the content the artificial intelligence model automatically generated for the document for the individual. The method includes receiving user feedback on the content automatically generated by the artificial intelligence model and generating updated training data for the artificial intelligence model based, at least in part, on the user feedback.

公开(公告)号：US20250078550A1

公开(公告)日：2025-03-06

申请号：US18241031

申请日：2023-08-31

Applicant: Intuit Inc.

Inventor： Preeti DURAIPANDIAN ,  Tharathorn Joy RIMCHALA ,  Peter Caton ANTHONY

IPC: G06V30/19 ,  G06V30/416

Abstract: Systems and methods for training an encoder-decoder model are disclosed. An example method includes receiving, over a communications network, a plurality of extraction model outputs from a corresponding plurality of extraction models, each extraction model output received from a corresponding extraction model and each extraction model output including a respective plurality of key-value pairs corresponding to extracted text from one or more training documents, receiving, over the communications network, character recognition data corresponding to the one or more training documents, receiving, over the communications network, ground truth key-value data corresponding to the one or more training documents, and training the encoder-decoder model based at least in part on the plurality of extraction model outputs, the character recognition data, and the ground truth key-value data, wherein the trained encoder-decoder model is configured to generate key-value pairs for subsequent outputs of the plurality of extraction models.

公开(公告)号：US20250078171A1

公开(公告)日：2025-03-06

申请号：US18240828

申请日：2023-08-31

Applicant: INTUIT INC.

Inventor： Kyle Bruno SCENNA ,  Vinoth Jeba Kumar RADHA KRISHNAN ,  David Cameron THOMPSON

IPC: G06Q40/12

Abstract: A method for generating supplemental content for an explanation for a particular result determined by a software application includes receiving data indicative of a user selecting a first modality of a plurality of different modalities for supplementing the explanation. In response to receiving the data, the method includes providing inputs to a generative artificial intelligence model. The inputs include data indicative of the explanation and data indicative of a first natural language prompt associated with the first modality. The method includes receiving an output from the generative artificial intelligence model. The output includes supplemental content for the explanation. The method includes displaying the supplemental content for viewing via a user interface.

公开(公告)号：US20250077528A1

公开(公告)日：2025-03-06

申请号：US18240819

申请日：2023-08-31

Applicant: INTUIT INC.

Inventor： Nazanin Zaker HABIBABADI ,  Xue HAN ,  Wei WANG

IPC: G06F16/2457 ,  G06N3/0455

Abstract: The present disclosure provides techniques for fast record matching using machine learning. One example method includes receiving a request indicating one or more attributes, identifying, from a plurality of records using a first machine learning model, a set of records, wherein each record of the set of records indicates the one or more attributes, computing, for each record of the set of records using a second machine learning model, a first relevance score for the record, computing, for each record of the set of records using a third machine learning model, a second relevance score for the record, and identifying, based on the first relevance score for each record of the set of records and the second relevance score for each record of the set of records, a given record of the set of records best matching the request.

公开(公告)号：US12236559B2

公开(公告)日：2025-02-25

申请号：US18508762

申请日：2023-11-14

Applicant: INTUIT INC.

Inventor： Jiaxin Zhang ,  Kamalika Das ,  Sricharan Kallur Palli Kumar

IPC: G06T5/70 ,  G06T9/00

Abstract: Augmented Denoising Diffusion Implicit Models (“DDIMs”) using a latent trajectory optimization process can be used for image generation and manipulation using text input and one or more source images to create an output image. Noise bias and textual bias inherent in the model representing the image and text input is corrected by correcting trajectories previously determined by the model at each step of a diffusion inversion process by iterating multiple starts the trajectories to find determine augmented trajectories that minimizes loss at each step. The trajectories can be used to determine an augmented noise vector, enabling use of an augmented DDIM and resulting in more accurate, stable, and responsive text-based image manipulation.

公开(公告)号：USD1061559S1

公开(公告)日：2025-02-11

申请号：US29874759

申请日：2023-04-24

Applicant: Intuit Inc.

Designer： Brittany Sumarsono ,  Xueyin Liu ,  James A. Buffington ,  Shekinah Cravens

公开(公告)号：US12217287B2

公开(公告)日：2025-02-04

申请号：US18129823

申请日：2023-03-31

Applicant: Intuit Inc.

Inventor： Ivan Shevchenko ,  Tatiana Sukhova

IPC: G06Q30/0241 ,  G06F40/106 ,  G06F40/186

Abstract: A method implements brand engine for extracting and presenting brand data with user interfaces. The method includes receiving a blueprint with a set of structure blocks extracted from a selected content. A structure block of the set of structure blocks includes a set of style parameter requests for a section of the selected content. The method further includes processing the set of structure blocks with a first set of smart blocks to generate a set of scores. A smart block of the first set of smart blocks includes brand data with style parameter selections. The method further includes selecting a second set of smart blocks, for the set of structure blocks, from the first set of smart blocks, using the set of scores. The method further includes presenting the second set of smart blocks with the brand data.

公开(公告)号：US12212671B2

公开(公告)日：2025-01-28

申请号：US18485165

申请日：2023-10-11

Applicant: INTUIT INC.

Inventor： Margarita Vald ,  Julia Zarubinsky ,  Yaron Sheffer ,  Sergey Banshats

IPC: H04L9/08

Abstract: Systems and methods that may be used to provide policies and protocols for blocking decryption capabilities in symmetric key encryption using a unique protocol in which key derivation may include injecting a random string into each key derivation. For example, a policy may be assigned to each client device indicating whether the client device has been assigned encryption only permission or full access permission to both encrypt and decrypt data. The disclosed protocol prevents client devices with encryption only permission from obtaining keys for decryption.