Chinese Academy of Sciences

International Business Machines Corporation

Huawei Technologies Co., Limited

Cambricon Technologies Corporation Limited

Beijing Baidu Netcom Science and Technology Co., Ltd.

Boe Technology Group Co., Ltd.

The Hong Kong University of Science and Technology

Beijing Kuaimajiabian Technology Co., Ltd.

Chengdu Boe Optoelectronics Technology Co., Ltd.

Beijing Boe Display Technology Co., Ltd.

Baidu Online Network Technology (beijing) Co., Ltd.

Barco N.v.

Shanghai Xiaodu Technology Co. Ltd.

Zhejiang Chint Electrics Co., Ltd.

State Grid Corporation of China

Zhen Li

Shaoli Liu

Tianshi Chen

Jing Lan Chen

Ming Zhou

Yunji Chen

Chungu Xia

Yu Sun

Tao Luo

Shijin Zhang

Cheng Qian

Yukun Li

Heyuan Song

Jun W Zhang

Xinzhi Zhang

Zhonghua Tang

Xiangshui Miao

Benzhong Tang

Kai Yang

Junfeng Zhao

Qiang He

Xian Wu

Yuning Hong

Mi Wan Shum

DongJie Wei

Pei Yang

Matthias Haeussler

Haiqing Lin

Xiang Peng

Zongwei Li

Zhulin Wei

Haiyan Yang

Junjun Zhang

Ronggang Xu

Dianyu Chen

Shuai Gong

Yihai Xiang

Yongqiang Dong

Hui Tong

Zhongzhi Liu

Enxiu Guo

Changmin Xing

Samuel H Wong

Peng Wang

Rui Wang

Peng Li

Xiao Lin Zhang

Jun Wei Zhang

Dong Chen

Chen Wang

Qi Guo

Jun Liang

Bingrui Wang

Liang Chen

Jianting Wang

Rui Hou

Han Wang

Min Chen

Mi Zhou

Jian Zhang

Jiyong Wang

Yulin Wang

Haitao Song

Lu Qian

Bo Tang

Yinghong Yang

Huiying Lan

Ying Yang

Guibin Bian

Yan Qi

Zhe Zhou

Jing Feng

Jianguo Xing

Shengqi Wang

Rongrong Bai

Ming Hua

Jie Ge

Chang Jiang

Wenhao He

Xiangnan Yuan

Degang Qu

Muyun Lei

Yongliang Yang

Yuanfu Bao

Lei Bai

Huaquan Yang

Wei Han

Enhe Liu

Chengjing Xiao

Tao Wei

Xiaomei Shao

Lingmin Liao

Da Zhang

Xiaohu Yan

Di Shen

Anshun You

Shujie Zhang

Zailiang Lou

Yanmin Zhao

Qinghai Song

Display screen or portion thereof with a graphical user interface

The present disclosure provides a method, apparatus, electronic device and storage medium for training a semantic similarity model, which relates to the field of artificial intelligence. A specific implementation solution is as follows: obtaining a target field to be used by a semantic similarity model to be trained; calculating respective correlations between the target field and application fields corresponding to each of training datasets in known multiple training datasets; training the semantic similarity model with the training datasets in turn, according to the respective correlations between the target field and the application fields corresponding to each of the training datasets. According to the technical solution of the present disclosure, it is possible to, in the fine-tuning phase, more purposefully train the semantic similarity model with the training datasets with reference to the correlations between the target field and the application fields corresponding to the training datasets, thereby effectively improving the learning capability of the sematic similarity model and effectively improving the accuracy of the trained semantic similarity model.

Method, apparatus, electronic device and storage medium for training semantic similarity model

This disclosure provides a packaging structure for a display substrate, a packaging method and a display device. The packaging structure for the display substrate includes a base substrate, a light-emitting device arranged on the base substrate, and a packaging thin film covering the light-emitting device. The packaging thin film includes an inorganic thin film and an organic thin film that are laminated, and the organic thin film is arranged on a surface of the inorganic thin film away from the base substrate. The packaging thin film includes a central region and a peripheral region surrounding the central region, the inorganic thin film located in the central region has surface energy greater than that of the inorganic thin film in the peripheral region, and the organic thin film in the central region has a thickness less than that of the organic thin film in the peripheral region.

Packaging structure for display substrate, packaging method and display device

The present disclosure provides a data processing method and an apparatus and a related product. The products include a control module including an instruction caching unit, an instruction processing unit, and a storage queue unit. The instruction caching unit is configured to store computation instructions associated with an artificial neural network operation; the instruction processing unit is configured to parse the computation instructions to obtain a plurality of operation instructions; and the storage queue unit is configured to store an instruction queue, where the instruction queue includes a plurality of operation instructions or computation instructions to be executed in the sequence of the queue. By utilizing the above-mentioned method, the present disclosure can improve the operation efficiency of related products when performing operations of a neural network model.

Data processing method and apparatus, and related product

A method for training a language model based on various word vectors, a device and a medium, which relate to the field of natural language processing technologies in artificial intelligence, are disclosed. An implementation includes inputting a first sample text language material including a first word mask into the language model, and outputting a context vector of the first word mask via the language model; acquiring a first probability distribution matrix of the first word mask based on the context vector of the first word mask and a first word vector parameter matrix, and a second probability distribution matrix of the first word mask based on the context vector of the first word mask and a second word vector parameter matrix; and training the language model based on a word vector corresponding to the first word mask.

Method for training language model based on various word vectors, device and medium

A method and apparatus for obtaining word vectors based on a language model, a device and a storage medium are disclosed, which relates to the field of natural language processing technologies in artificial intelligence. An implementation includes inputting each of at least two first sample text language materials into the language model, and outputting a context vector of a first word mask in each first sample text language material via the language model; determining the word vector corresponding to each first word mask based on a first word vector parameter matrix, a second word vector parameter matrix and a fully connected matrix respectively; and training the language model and the fully connected matrix based on the word vectors corresponding to the first word masks in the at least two first sample text language materials, so as to obtain the word vectors.

Method and apparatus for obtaining word vectors based on language model, device and storage medium

The present disclosure provides an operation apparatus and method for an acceleration chip for accelerating a deep neural network algorithm. The apparatus comprises: a vector addition processor module and a vector function value arithmetic unit and a vector multiplier-adder module wherein the three modules execute a programmable instruction, and interact with each other to calculate values of neurons and a network output result of a neural network, and a variation amount of a synaptic weight representing the interaction strength of the neurons on an input layer to the neurons on an output layer; and the three modules are all provided with an intermediate value storage region and perform read and write operations on a primary memory.

Operation apparatus and method for acceleration chip for accelerating deep neural network algorithm

The present disclosure provides a compressor circuit, a Wallace tree circuit, a multiplier circuit, a chip and an apparatus. The compressor circuit includes a first full adder, a second full adder, and a first selection circuit. An output end of the first full adder is connected to an input end of the first selection circuit, and an output end of the first selection circuit is connected to an input end of the second full adder. The first selection circuit is configured to determine an input signal output by the first selection circuit to the second full adder according to a first selection signal; and the input signal output by the first selection circuit to the second full adder and a most significant bit signal of a plurality of input signals of the compressor circuit are used to control turning on and turning off of the second full adder, which can reduce circuit power consumption and delay.

Compressor circuit, Wallace tree circuit, multiplier circuit, chip, and device

A shutter-type adaptive three-dimensional (3D) display system based on medical microscopic imaging is provided. In the system, a binocular camera is connected to an operating microscope optical system through a beam splitter, and is configured to acquire binocular image data. A control module is configured to input control instructions, where the control instructions include a first type of control instructions and a second type of control instructions. An image processing module calculates image parallaxes based on the binocular image data under the first type of control instructions, and transmits the image parallaxes to the binocular camera to adjust offsets. A display module is configured to generate display data based on the binocular image data and display the display data through a display device for viewing with 3D glasses. The operating microscope optical system is configured to perform an adjustment based on the control instructions.

Shutter-type adaptive three-dimensional display system based on medical microscopic imaging

A screen control method, an apparatus, a device and a computer readable storage medium are provided. A display interface of a display screen includes a main display interface and a secondary display interface. The method includes: receiving a component call request sent by a user; switching the main display interface to the secondary display interface according to the component call request; and displaying preset component content on the secondary display interface according to a preset component display mode. Thus, the component content preset by the user can be uniformly displayed on the secondary display interface, which thus improves the user stickiness, makes the presented content more personalized and more compatible with the user's needs, thereby improving the user experience.

Smart sound box screen control method, apparatus, device and computer readable storage medium

Aspects for vector combination in neural network are described herein. The aspects may include a direct memory access unit configured to receive aa first vector, a second vector, and a controller vector. The first vector, the second vector, and the controller vector may each include one or more elements indexed in accordance with a same one-dimensional data structure. The aspects may further include a computation module configured to select one of the one or more control values, determine that the selected control value satisfies a predetermined condition, and select one of the one or more first elements that corresponds to the selected control value in the one-dimensional data structure as an output element based on a determination that the selected control value satisfies the predetermined condition.

Apparatus and methods for combining vectors

A nonlinear function operation device and method are provided. The device may include a table looking-up module and a linear fitting module. The table looking-up module may be configured to acquire a first address of a slope value k and a second address of an intercept value b based on a floating-point number. The linear fitting module may be configured to obtain a linear function expressed as y=k&#xd7;x+b based on the slope value k and the intercept value b, and substitute the floating-point number into the linear function to calculate a function value of the linear function, wherein the calculated function value is determined as the function value of a nonlinear function corresponding to the floating-point number.

Apparatus and methods for non-linear function operations

A fabrication method and a fabrication assembly for a flexible display substrate are provided. The fabrication assembly for a flexible display substrate includes: a rigid base substrate, including a first engaging structure being on a surface of the rigid base substrate; and a protective film, including a first surface and a second surface opposite to each other, and including a second engaging structure being on the first surface. The second surface of the protective film is configured to be attached to a flexible base substrate; and the rigid base substrate and the protective film are configured to be detachably connected with each other by the first engaging structure and the second engaging structure.

Fabrication method and fabrication assembly for flexible display substrate

Aspects for converting floating-point numbers in a processor are described herein. As an example, the aspects may include receiving, by a floating-point number converter, an exponent bit length, a base value, and one or more first floating-point numbers of a first bit length. Further, the aspects may include calculating, by the floating-point number converter, one or more second floating-point numbers of a second bit length based on the exponent bit length and the base value, the one or more second floating-point numbers respectively corresponding to the one or more first floating-point numbers.

Techniques for floating-point number conversion

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Beijing, China

Zhen Li