公开(公告)号：US20250053800A1

公开(公告)日：2025-02-13

申请号：US18232063

申请日：2023-08-09

Applicant: HITACHI, Ltd.

Inventor： Dipanjan GHOSH ,  Ahmed FARAHAT ,  Xian Yeow LEE ,  Lasitha VIDYARATNE ,  Chetan GUPTA

IPC: G06N3/08 ,  G06N3/0475

Abstract: Systems and methods described herein can involve training a first generative artificial intelligence (AI) model for a general domain, the first generative AI model trained using standard information components of the general domain; training a second AI model for a specific domain from the first generative AI model, the training of the second AI model being based on the use of the standard information components, non-standard information components of the specific domain and available label data of the specific domain; and fine-tuning the second AI model to align with preferences of the specific domain to maximize reward and minimize error.

公开(公告)号：US20240420450A1

公开(公告)日：2024-12-19

申请号：US18210221

申请日：2023-06-15

Applicant: HITACHI, Ltd.

Inventor： Lasitha Sandaruwan VIDYARATNE ,  Xian Yeow LEE ,  Mahbubul ALAM ,  Ahmed FARAHAT ,  Dipanjan GHOSH ,  Maria Teresa GONZALEZ DIAZ ,  Chetan GUPTA

IPC: G06V10/762 ,  G06V10/74 ,  G06V10/77 ,  G06V10/774

Abstract: Systems and methods described herein which can involve for a first input of a plurality of labeled images of a new domain task, processing the first plurality of labeled images through a plurality of backbone snapshots, each of the backbone snapshots representative of a model trained across a plurality of other domain tasks, each of the plurality of backbone snapshots configured to output a first plurality of features responsive to the input; processing a second input of second plurality of unlabeled images through the plurality of backbone snapshots to output a second plurality of features responsive to the second input; and generating a representative model for the new domain task from the clustering and transformation of the first plurality of features and as associated from the clustered and transformed second plurality of features.