公开(公告)号：US20210297498A1

公开(公告)日：2021-09-23

申请号：US17191698

申请日：2021-03-04

Applicant: SRI International

Inventor： Ajay Divakaran ,  Karan Sikka ,  Arijit Ray ,  Xiao Lin ,  Yi Yao

IPC: H04L29/08

Abstract: A method, apparatus and system for determining user-content associations for determining and providing user-preferred content using multimodal embeddings include creating an embedding space for multimodal content by creating a first modality vector representation of the multimodal content having a first modality, creating a second modality vector representation of the multimodal content having a second modality, creating a user vector representation, as a third modality, for each user associated with at least a portion of the multimodal content, and embedding the first and the second modality vector representations and the user vector representations in the common embedding space using at least a mixture of loss functions for each modality pair of the first, the at least second and the third modalities that pushes closer co-occurring pairs of multimodal content. Embodiments can further include generating content using determined attributes of a message to be conveyed and features of the user-preferred content.

公开(公告)号：US20190303404A1

公开(公告)日：2019-10-03

申请号：US16231059

申请日：2018-12-21

Applicant: SRI International

Inventor： Mohamed R. Amer ,  Timothy J. Meo ,  Xiao Lin

IPC: G06F16/738 ,  G06K9/62 ,  G06N20/00

Abstract: This disclosure describes techniques that include generating, based on a description of a scene, a movie or animation that represents at least one possible version of a story corresponding to the description of the scene. This disclosure also describes techniques for training a machine learning model to generate predefined data structures from textual information, visual information, and/or other information about a story, an event, a scene, or a sequence of events or scenes within a story. This disclosure also describes techniques for using GANs to generate, from input, an animation of motion (e.g., an animation or a video clip). This disclosure also describes techniques for implementing an explainable artificial intelligence system that may provide end users with information (e.g., through a user interface) that enables an understanding of at least some of the decisions made by the AI system.

公开(公告)号：US20240403728A1

公开(公告)日：2024-12-05

申请号：US18614388

申请日：2024-03-22

Applicant: SRI International

Inventor： Yunye Gong ,  Yi Yao ,  Xiao Lin ,  Ajay Divakaran

IPC: G06N20/20 ,  G06N7/01

Abstract: In general, techniques are described that address the limitations of existing conformal prediction methods for cascaded models. In an example, a method includes receiving a first validation data set for validating performance of an upstream model of the two or more cascaded models and receiving a second validation data set for validating performance of a downstream model of the two or more cascaded models wherein the second validation data set is different than the first validation set; estimating system-level errors caused by predictions of the upstream model based on the first validation data set; estimating system-level errors caused by predictions of the downstream model based on the second validation data set; and generating a prediction confidence interval that indicates a confidence for the system based on the system-level errors caused by predictions of the upstream model and based on the system-level errors caused by predictions of the downstream model.

公开(公告)号：US11210836B2

公开(公告)日：2021-12-28

申请号：US16231020

申请日：2018-12-21

Applicant: SRI International

Inventor： Mohamed R. Amer ,  Xiao Lin

IPC: G06T13/80 ,  G06N3/04 ,  G06N3/08 ,  G06K9/00 ,  G06F16/738 ,  G06N20/00 ,  G06K9/62 ,  G06F16/34 ,  G06F16/901 ,  G06T13/40 ,  G06T7/246 ,  G06F40/205

Abstract: This disclosure describes techniques that include generating, based on a description of a scene, a movie or animation that represents at least one possible version of a story corresponding to the description of the scene. This disclosure also describes techniques for training a machine learning model to generate predefined data structures from textual information, visual information, and/or other information about a story, an event, a scene, or a sequence of events or scenes within a story. This disclosure also describes techniques for using GANs to generate, from input, an animation of motion (e.g., an animation or a video clip). This disclosure also describes techniques for implementing an explainable artificial intelligence system that may provide end users with information (e.g., through a user interface) that enables an understanding of at least some of the decisions made by the AI system.

公开(公告)号：US20190304104A1

公开(公告)日：2019-10-03

申请号：US16231020

申请日：2018-12-21

Applicant: SRI International

Inventor： Mohamed R. Amer ,  Xiao Lin

IPC: G06T7/246 ,  G06K9/00 ,  G06N20/00

Abstract: This disclosure describes techniques that include generating, based on a description of a scene, a movie or animation that represents at least one possible version of a story corresponding to the description of the scene. This disclosure also describes techniques for training a machine learning model to generate predefined data structures from textual information, visual information, and/or other information about a story, an event, a scene, or a sequence of events or scenes within a story. This disclosure also describes techniques for using GANs to generate, from input, an animation of motion (e.g., an animation or a video clip). This disclosure also describes techniques for implementing an explainable artificial intelligence system that may provide end users with information (e.g., through a user interface) that enables an understanding of at least some of the decisions made by the AI system.

公开(公告)号：US11430171B2

公开(公告)日：2022-08-30

申请号：US16231059

申请日：2018-12-21

Applicant: SRI International

Inventor： Mohamed R. Amer ,  Timothy J. Meo ,  Xiao Lin

IPC: G06F16/738 ,  G06T13/80 ,  G06N3/04 ,  G06N3/08 ,  G06N20/00 ,  G06K9/62 ,  G06F16/34 ,  G06F16/901 ,  G06T13/40 ,  G06T7/246 ,  G06F40/205 ,  G06V20/40 ,  G06V40/20

Abstract: This disclosure describes techniques that include generating, based on a description of a scene, a movie or animation that represents at least one possible version of a story corresponding to the description of the scene. This disclosure also describes techniques for training a machine learning model to generate predefined data structures from textual information, visual information, and/or other information about a story, an event, a scene, or a sequence of events or scenes within a story. This disclosure also describes techniques for using GANs to generate, from input, an animation of motion (e.g., an animation or a video clip). This disclosure also describes techniques for implementing an explainable artificial intelligence system that may provide end users with information (e.g., through a user interface) that enables an understanding of at least some of the decisions made by the AI system.