公开(公告)号：US20240362473A1

公开(公告)日：2024-10-31

申请号：US18306687

申请日：2023-04-25

申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION

发明人： Martin G. Keen ,  John M. Ganci, JR. ,  Atul Mene ,  Sarbajit K. Rakshit

IPC分类号： G06N3/08 ,  G06N3/0475

CPC分类号： G06N3/08 ,  G06N3/0475

摘要： An embodiment for compressing media utilizing a generative adversarial network (GAN) is provided. The embodiment may include receiving one or more media assets and historical data from a knowledge corpus in accordance with an identified usage context. The embodiment may also include identifying one or more objects in the one or more media assets. The embodiment may further include deriving a relevance score for each identified object. The embodiment may also include creating a training data set. The embodiment may further include applying one or more modifications to each object in a first set. The embodiment may also include in response to determining a GAN discriminator is able to identify each object in the first set modified by the GAN generator as real, generating one or more updated media assets including a second set of one or more objects that are identified by the GAN discriminator as real.

公开(公告)号：US20240362467A1

公开(公告)日：2024-10-31

申请号：US18375923

申请日：2023-10-02

申请人： Box, Inc.

发明人： Nachiket Deo ,  Iyer Nirmal Ganesh ,  Virender Gupta ,  Benjamin John Kus ,  Denis Grenader

IPC分类号： G06N3/0475

CPC分类号： G06N3/0475

摘要： A method for processing content management system workflows. Systems and subsystems are established for configuring a content management system to implement workflow processes wherein the content management system (CMS) exposes instances of stored content objects to a plurality of user devices through an electronic interface. Further systems and subsystem are established for identifying metadata maintained by the CMS for the stored content objects, and for identifying a generative AI entity (GAIE) to interact with the CMS. On an ongoing basis, the foregoing systems and subsystems carry out steps for (1) forming a GAIE prompt, wherein the GAIE prompt comprises at least a portion of the metadata identified from the CMS for the stored content objects, (2) receiving a response from the GAIE, wherein the response corresponds to the GAIE prompt; and (3) using, by the CMS, the response from the GAIE to implement processing of a content management system workflow.

公开(公告)号：US20240331210A1

公开(公告)日：2024-10-03

申请号：US18128906

申请日：2023-03-30

申请人： Adobe Inc.

发明人： Michele Saad ,  Ajay Jain

IPC分类号： G06T11/00 ,  G06N3/045 ,  G06N3/0475 ,  G06N3/094 ,  G06Q30/0601 ,  G06Q50/00

CPC分类号： G06T11/00 ,  G06N3/045 ,  G06N3/0475 ,  G06N3/094 ,  G06Q30/0631 ,  G06Q50/01

摘要： Some embodiments described herein relate to systems and methods for parameter-based synthetic model generation and recommendations including an image generation module and a recommendation module. The image generation module can receive one or more parameters and, responsive to receive the one or more parameters, generate a parameterized image using a generative machine learning model. The generative ML model may use the parameters as a seed for generating the parameterized image. The recommendation module may generate a first set of recommendations for a user of the client device and receive the one or more parameters. The recommendation module may determine, based on the one or more parameters, a second set of recommendations for the user of the client device. The second set of recommendations may include at least one element from the first set of recommendations.

公开(公告)号：US20240311749A1

公开(公告)日：2024-09-19

申请号：US18122057

申请日：2023-03-15

申请人： X Development LLC

发明人： Grace Taixi Brentano ,  Salil Vijaykumar Pradhan ,  Rebecca Radkoff ,  David Andre ,  Lam Thanh Nguyen ,  Sze Man Lee ,  Gearoid Murphy

IPC分类号： G06Q10/0835 ,  G06N3/0475 ,  G06N3/092 ,  G06N3/094

CPC分类号： G06Q10/08355 ,  G06N3/0475 ,  G06N3/092 ,  G06N3/094

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating alternative networks. One of the methods includes receiving supply chain data representing a first supply chain network having nodes and links, receiving map data, providing the map data and the supply chain data as input to a generative process that is configured to generate one or more second supply chain networks, receiving, as output from the generative process, a second supply chain network, performing a supply chain simulation on the second supply chain network generated by the generative model, and computing a performance metric for the second supply chain network based on performing the simulation.

公开(公告)号：US20240303474A1

公开(公告)日：2024-09-12

申请号：US18586141

申请日：2024-02-23

申请人： Direct Cursus Technology L.L.C

发明人： Nikita PAVLICHENKO ,  Dmitrii USTALOV

IPC分类号： G06N3/0475 ,  G06F40/279 ,  G06N3/08 ,  G06T11/00

CPC分类号： G06N3/0475 ,  G06F40/279 ,  G06N3/08 ,  G06T11/001

摘要： A method and a server for fine-tuning a generative machine-learning model (GMLM) are provided. The method comprises: receiving a given textual description of a testing object a testing image thereof, the given textual description being indicative of what is to be depicted in the testing image in a natural language; receiving keywords associated with the given textual description, a given keyword being indicative of a rendering instruction for rendering the testing object in the testing image; generating, based on the keywords, augmented textual descriptions of the image; feeding to the GMLM, each one of the augmented textual descriptions to generate image candidates of the object; transmitting the image candidates to a plurality of human assessors for pairwise comparison thereof; based on the pairwise comparison, determining for the given image candidate, a respective degree of visual appeal; and using the respective degree of visual appeal for fine-tuning the GMLM.

公开(公告)号：US20240296276A1

公开(公告)日：2024-09-05

申请号：US18117314

申请日：2023-03-03

申请人： Microsoft Technology Licensing, LLC

发明人： Poonam Ganesh HATTANGADY ,  Adam Douglas TROY ,  Michael Ivan BORYSENKO ,  Susan Marie GRIMSHAW ,  Caleb WHITMORE

IPC分类号： G06F40/166 ,  G06F3/0484 ,  G06F40/103 ,  G06F40/279 ,  G06F40/58 ,  G06N3/0475 ,  G06N3/09

CPC分类号： G06F40/166 ,  G06F3/0484 ,  G06F40/103 ,  G06F40/279 ,  G06F40/58 ,  G06N3/0475 ,  G06N3/09

摘要： Systems and methods for using a generative artificial intelligence (AI) model to generate a suggested draft reply to a selected message. A message generation system and method are described that optimize input that is provided to the AI model so that it provides the most relevant information. In some examples, input prompts to the AI model are limited in size and latency can be impacted based on the size of the input provided to the AI model. Thus, the method and system identify, include, and format relevant information in an input prompt. The prompt reduces latency by the generative AI model in processing the prompt and may also lead to more relevant results produced by the generative AI model.

公开(公告)号：US20240281657A1

公开(公告)日：2024-08-22

申请号：US18638513

申请日：2024-04-17

申请人： CCNets, Inc.

发明人： Jun Ho Park

IPC分类号： G06N3/08 ,  G06N3/0475

CPC分类号： G06N3/08 ,  G06N3/0475

摘要： Disclosed herein is the framework of causal cooperative networks that discovers the causal relationship between observational data in a dataset and a label of the observation thereof and trains each model with inference of a causal explanation, reasoning, and production. In the case of the supervised learning, neural networks are adjusted through the prediction of the label for observation inputs. On the other hand, a causal cooperative network that includes the explainer, a reasoner, and a producer neural network models, receives an observation and a label as a pair, results multiple outputs, and calculates a set of losses of inference, generation, and reconstruction from the input and the outputs. The explainer, the reasoner, and the producer are adjusted by error propagation for each model obtained from the set of losses.

公开(公告)号：US20240277449A1

公开(公告)日：2024-08-22

申请号：US18292217

申请日：2022-08-08

申请人： 3M INNOVATIVE PROPERTIES COMPANY

发明人： Benjamin D. Zimmer ,  Cody J. Olson ,  Nicholas A. Stark ,  Nicholas J. Raddatz ,  Alexandra R. Cunliffe ,  Guruprasad Somasundaram

IPC分类号： A61C7/00 ,  A61C7/08 ,  G06N3/0475

CPC分类号： A61C7/002 ,  A61C7/08 ,  G06N3/0475

摘要： Methods for generating intermediate stages for orthodontic aligners using machine learning or deep learning techniques. The method receives a malocclusion of teeth and a planned setup position of the teeth. The malocclusion can be represented by translations and rotations, or by digital 3D models. The method generates intermediate stages for aligners, between the malocclusion and the planned setup position, using one or more deep learning methods. The intermediate stages can be used to generate setups that are output in a format, such as digital 3D models, suitable for use in manufacturing the corresponding aligners.

公开(公告)号：US20240273306A1

公开(公告)日：2024-08-15

申请号：US18169793

申请日：2023-02-15

申请人： Microsoft Technology Licensing, LLC

发明人： Manas Somaiya ,  Lakshman Somasundaram ,  Laura Lorenzetti Soper ,  Yao Pan ,  Nicholas Pezarro

IPC分类号： G06F40/40 ,  G06F16/957 ,  G06F40/186 ,  G06N3/0475 ,  G06N3/08

CPC分类号： G06F40/40 ,  G06F16/957 ,  G06F40/186 ,  G06N3/0475 ,  G06N3/08

摘要： Embodiments of the disclosed technologies include creating a first set of title prompts by applying a first set of title prompt templates to a seed, where the seed includes a topic descriptor, applying a first generative language model to the first set of title prompts, outputting, by the first generative language model, based on the first set of title prompts, a first set of document titles, creating a first set of document prompts by applying a first set of document prompt templates different from the first set of title prompt templates to the first set of document titles, applying a second generative language model to the first set of document prompts, and outputting, by the second generative language model, based on the first set of document prompts, a first set of documents.

公开(公告)号：US20240273286A1

公开(公告)日：2024-08-15

申请号：US18169802

申请日：2023-02-15

申请人： Microsoft Technology Licensing, LLC

发明人： Maria Iu ,  Lakshman Somasundaram ,  Yilin Li ,  Shweta Patira ,  Adam Kaplan ,  Sara Remi Fields

IPC分类号： G06F40/197 ,  G06F40/117 ,  G06F40/166 ,  G06F40/258 ,  G06N3/0475 ,  G06N3/08

CPC分类号： G06F40/197 ,  G06F40/117 ,  G06F40/166 ,  G06F40/258 ,  G06N3/0475 ,  G06N3/08 ,  H04L67/06

摘要： Embodiments of the disclosed technologies include generating, by a generative language model, a first version of a first document, generating a second version of the first document by dividing the first version of the first document into a plurality of segments, where a first segment of the plurality of segments includes a subset of the digital content generated by the generative language model; enabling contributions to the first segment; enabling contributions to a second segment of the plurality of segments; receiving a first contribution to the second version of the first document, where the first contribution includes digital content generated by a first user of the network; creating a first segment-contribution pair by linking the first contribution with the first segment; receiving a second contribution to the second version of the first document; and creating a second segment-contribution pair by linking the second contribution with the second segment, where at least one of the first segment-contribution pair or the second segment-contribution pair is capable of being used to generate, by the generative language model, a second document.