Invention Grant
- Patent Title: Method and system for artificial intelligence model training using a watermark-enabled kernel for a data processing accelerator
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Application No.: US16598281Application Date: 2019-10-10
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Publication No.: US11709712B2Publication Date: 2023-07-25
- Inventor: Yueqiang Cheng , Yong Liu
- Applicant: Baidu USA LLC
- Applicant Address: US CA Sunnyvale
- Assignee: BAIDU USA LLC,KUNLUNXIN TECHNOLOGY (BEIJING) COMPANY LIMITED
- Current Assignee: BAIDU USA LLC,KUNLUNXIN TECHNOLOGY (BEIJING) COMPANY LIMITED
- Current Assignee Address: US CA Sunnyvale; CN Beijing
- Agency: Womble Bond Dickinson (US) LLP
- Main IPC: G06F9/50
- IPC: G06F9/50 ; G06N5/04 ; G06N20/10 ; G06F21/16

Abstract:
In one embodiment, a computer-implemented method performed by a data processing (DP) accelerator, includes receiving, at the DP accelerator, first data representing a set of training data from a host processor; receiving, at the DP accelerator, a watermark kernel from the host processor; and executing the watermark kernel within the DP accelerator on an artificial intelligence (AI) model. The watermark kernel, when executed, is configured to: generate a new watermark by inheriting an existing watermark from a data object of the set of training data, train the AI model using the set of training data, and implant the new watermark within the AI model during training of the AI model. The DP accelerator then transmits second data representing the trained AI model having the new watermark implanted therein to the host processor.
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