公开(公告)号：US20240005654A1

公开(公告)日：2024-01-04

申请号：US17656391

申请日：2022-03-24

Applicant: SRI International

Inventor： Arijit Ray ,  Michael A. Cogswell ,  Ajay Divakaran ,  Yi Yao ,  Giedrius T. Burachas ,  Kamran Alipour

IPC: G06V10/98 ,  G06T11/00 ,  G06V10/776 ,  G06V10/77

CPC classification number: G06V10/98 ,  G06T11/001 ,  G06V10/776 ,  G06V10/7715

Abstract: A computing system comprising a memory configured to store an artificial intelligence (AI) model and an image, and a computation engine executing one or more processors may be configured to perform the techniques for error-based explanations for AI behavior. The computation engine may execute the AI model to analyze the image to output a result. The AI model may, when analyzing the image to output the result, process, based on data indicative of the result, the image to assign an error score to each image feature extracted from the image, and obtain, based on the error scores, an error map. The AI model may next update, based on the error map and to obtain a first updated image, the image to visually indicate the error score assigned to each of the image features, and output one or more of the error scores, the error map, and the first updated image.

公开(公告)号：US20240403649A1

公开(公告)日：2024-12-05

申请号：US18520800

申请日：2023-11-28

Applicant: SRI International

Inventor： Han-Pang Chiu ,  Yi Yao ,  Zachary Seymour ,  Alex Krasner ,  Bradley J. Clymer ,  Michael A. Cogswell ,  Cecile Eliane Jeannine Mackay ,  Alex C. Tozzo ,  Tixiao Shan ,  Philip Miller ,  Chuanyong Gan ,  Glenn A. Murray ,  Richard Louis Ferranti ,  Uma Rajendran ,  Supun Samarasekera ,  Rakesh Kumar ,  James Smith

IPC: G06N3/0895

Abstract: In an example, a system includes processing circuitry in communication with storage media. The processing circuitry is configured to execute a machine learning system including at least a first module, a second module and a third module. The machine learning system is configured to train one or more machine learning models. The first module is configured to generate augmented input data based on the streaming input data. The second module includes a machine learning model configured to perform a specific task based at least in part on the augmented input data. The third module configured to adapt a network architecture of the one or more machine learning models based on changes in the streaming input data.

公开(公告)号：US11934793B2

公开(公告)日：2024-03-19

申请号：US17516409

申请日：2021-11-01

Applicant: SRI International

Inventor： Ajay Divakaran ,  Karan Sikka ,  Yi Yao ,  Yunye Gong ,  Stephanie Nunn ,  Pritish Sahu ,  Michael A. Cogswell ,  Jesse Hostetler ,  Sara Rutherford-Quach

IPC: G06F40/35 ,  G06F16/33 ,  G06N5/04

CPC classification number: G06F40/35 ,  G06F16/3335 ,  G06N5/04

Abstract: A method, apparatus and system for training an embedding space for content comprehension and response includes, for each layer of a hierarchical taxonomy having at least two layers including respective words resulting in layers of varying complexity, determining a set of words associated with a layer of the hierarchical taxonomy, determining a question answer pair based on a question generated using at least one word of the set of words and at least one content domain, determining a vector representation for the generated question and for content related to the at least one content domain of the question answer pair, and embedding the question vector representation and the content vector representations into a common embedding space where vector representations that are related, are closer in the embedding space than unrelated embedded vector representations. Requests for content can then be fulfilled using the trained, common embedding space.