公开(公告)号：US20220263670A1

公开(公告)日：2022-08-18

申请号：US17662072

申请日：2022-05-04

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Chunhui WAN ,  Tong JIN ,  Zhimin WEI ,  Jiaxiang LIU ,  Lei ZHANG ,  Bingxin FAN

IPC: H04L9/00 ,  G06F9/54 ,  G06F9/46 ,  G06F9/455

Abstract: Provided are a method and apparatus for operating a blockchain system, a device and a storage medium. The method is described below. To-be-processed blockchain data is acquired through a kernel engine of a blockchain system. The to-be-processed blockchain data is processed through the kernel engine, and a kernel component interface provided by a component adaptor is called during the processing process of the to-be-processed blockchain data to call a kernel component.

公开(公告)号：US20220129753A1

公开(公告)日：2022-04-28

申请号：US17572921

申请日：2022-01-11

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Yuxiang LU ,  Jiaxiang LIU ,  Xuyi CHEN ,  Shikun FENG ,  Shuohuan WANG ,  Yu SUN ,  Shiwei HUANG ,  Jingzhou HE

IPC: G06N3/08 ,  G06N3/04

Abstract: A pre-training method of a neural network model, an electronic device, and a medium. The pre-training data is inputted to the initial neural network model, and the initial neural network model is pre-trained in the first training mode, in the first training mode, the plurality of hidden layers share one hidden layer parameter, and the loss value of the initial neural network model is obtained, if the loss value of the initial neural network model is less than a preset threshold, the initial neural network model continues to be pre-trained in the second training mode, in the second training mode, each of the plurality of hidden layers has its own hidden layer parameter.

公开(公告)号：US20230030471A1

公开(公告)日：2023-02-02

申请号：US17698242

申请日：2022-03-18

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Jiaxiang LIU ,  Shikun FENG

IPC: G06F40/284

Abstract: The present disclosure provides a text processing method and apparatus, an electronic device and a storage medium, and relates to the field of artificial intelligence technologies such as deep learning and natural language processing. The method may include: configuring, for a to-be-processed text, attention patterns corresponding to heads in a Transformer model using a multi-head-attention mechanism respectively, wherein at least one head corresponds to a different attention pattern from the other N−1 heads, and N denotes a number of heads and is a positive integer greater than 1; and processing the text by using the Transformer model. Model performance and a corresponding text processing effect can be improved by using the solutions according to the present disclosure.