International Business Machines Corporation

Keysight Technologies, Inc.

Gm Global Technolgoy Operations, Inc.

Beijing University of Chemical Tehcnology

Li Cao

Ze Ming Zhao

Cheng Fang Wang

Bo Tong Liu

Shuo Li

Xiaobo Wang

Sheng Yan Sun

Fei Fei Li

Xing Xing Shen

Ya Jing

Zhu Wen

Thorsten Hertel

Han Su

Peng Hui Jiang

Xin Peng Liu

Yi Shan Jiang

Jing Yan Ma

Fan Wang

Xiao Dong Li

Qing Ql Li

Zhi Hong Li

WeiFeng Zhang

Zhan Peng Huo

He Jiang Jia

Jun Long Xiang

Yan Wei Zhao

Sheng Jie Bj Han

Zhong Hao Wang

Ren Jie Feng

Hui Wang

Qi Cheng Li

Bin Xu

Hamid Ghavami Kia

Hong Mei Zhang

Hong Min

Xin Zhao

Jing James Xu

Wen Liu

Yong Wu

Jing Chen

Wei Song

Dong Hui Liu

Wei Cui

Yang Chen

Xue Ying Zhang

Guang Cheng Li

Peng Fei Tian

Lei Gao

Jia Tian Zhong

Jia Yu

Yubo Li

Qi Li

Qin Yue Chen

Yong Yin

Wu Song Fang

Qi Ming Teng

Hong Wei Sun

Zhao Wang

Shuang Shuang Jia

Rui Wang

Chu Yun Tong

Jiangang Deng

Hua Wei Fan

Xiao Tian Xu

Xiao-Yu Li

Wan Yue Chen

Qing Li

Jing Bai

Jin Sheng Gao

Zhou Wen Ya

Li Hong Qi

Yue Lin

Ya Ju Yan

Rong Yan

Yi Chai

Enrico James Monteleone

Hong Yi Zhang

Bing Qian

Leilei Hu

Tian Jiao Pu

Xiaoping Liu

Xiao Kou

Zhen Ou Yun

Xiaonong Chen

Qijiayu Wu

Zhou Kun

Mu Wei

Xiao Juan Chen

The present invention provides a computer-implemented method, a system, and a computer program product for path planning According to the computer-implemented method, a target discriminator is selected from a set of discriminators with different kernel sizes based on a target image obtained from an image capturing device. In this case, a confidence of the target image is determined using the target discriminator. The confidence indicates whether the target image contains a target object to be captured. Thereby, a movement indication for moving the image capturing device to capture the target object is determined based on the confidence of the target image.

Path planning

In a method for improving converter and compiler operator granularity, a processor extracts an operator granularity from an artificial intelligence framework and an original model. A processor receives device characteristics from a target device. A processor outputs a converter granularity level to a converter based on the operator granularity and the device characteristics. A processor outputs a compiler granularity level to a compiler based on the operator granularity and the device characteristics.

Optimizing operator granularity in compiling and converting artificial intelligence (AI) models

Aspects of the invention include generating a plurality of predictions that each define a plurality of future inputs for a model. A deviation curve is generated by determining a distance between each prediction of the plurality of predictions and a respective known data point of a plurality of known data points. One or more points in the deviation curve are sampled and the sampled points are compared to a low threshold and a high threshold. A judgement is determined for each prediction to determine whether the respective prediction will be accepted or denied as an input to the model. The future inputs for the model are modified based on the judgments.

Dynamic evaluation of model acceptability

A method, system, and computer program product for dependency-based software upgrading. The method may include determining respective dependency degrees between a plurality of software products based on property information related to a plurality of upgraded versions of the plurality of software products, a target software product depending on the plurality of software products. The method may also include dividing the plurality of software products into a plurality of groups of software products based on the respective dependency degrees. The method may also include determining a plurality of test scores associated with the plurality of groups, each test score indicating a performance enhancement degree of the target software product achieved by installing upgraded versions of at least one software product comprised in one of the plurality of groups. The method may also include determining a target upgrade solution for the target software product based on the plurality of test scores.

Dependency-based software upgrading

A method determines corrected TRP or TIS of an AUT in a near-field test chamber, the AUT having a phase center offset from a rotation center of the test chamber. The method includes performing EIRP or EIS measurements of the AUT at first sampling grid points on a first closed-surface geometric shape centered at the rotation center; mapping second sampling grid points to the first closed-surface geometric shape to provide mapped sampling grid points on the first closed-surface geometric shape, where the second sampling grid points are on a second closed-surface geometric shape centered at the phase center of the AUT; determining estimated EIRPs or EISs at the mapped sampling grid points using the EIRP or EIS measurements; scaling the estimated EIRPs or EISs at the mapped sampling grid points to provide scaled EIRPs or EISs; and calculating the corrected TRP or TIS based on the scaled EIRPs or EISs.

System and method for determining corrected total radiated power (TRP) or corrected total isotropic sensitivity (TIS) of offset antenna under test

Aspects of the invention include converting an artificial intelligence (AI) model generated in a first framework to a uniform exchange formatted model by engaging a master table to retrieve instructions for converting from the AI model to the uniform exchange formatted model in accordance with the first framework. The uniform exchange formatted model in compiled by engaging the master table to retrieve instructions for compiling the uniform exchange formatted model in accordance with the first framework. Data is received as an input to the compiled uniform exchange formatted model and an output is generated by engaging the master table to retrieve instructions for generating the output in accordance with the first framework.

Uniform artificial intelligence model conversion

A computer-implemented method to estimate computing cost of database queries. The method includes receiving a query. The method also includes generating one or more access plans for the query. The method further includes dynamically generating a learning model based on each of the generated access plans. The method includes estimating, by the learning model and for each of the one or more access plans, a predicted cost to execute the query. The method includes selecting, based on the predicted cost, a first access path associated with a lowest cost of the predicted costs and executing the query according the selected access path.

Estimating computational cost for database queries

An approach to optimize performance for large scale inference models. Data in the form of images is received from sensors such as cameras. The data is processed to generate data tags associated with the context of the image and portion the images. Model tags are generated based on data characteristics or user input. The tags and their associated data are added to a time-based queue for delivery to the appropriate inference models. Based on the embedded delivery time and frequency, the portioned images are delivered to the appropriate inference models.

Inference model optimization

A machine translation system, a ChatOps system, a method for a context-aware language machine identification, and computer program product. One embodiment of the machine translation system may include a density calculator. The density calculator may be adapted to calculate a part of speech (POS) density for a plurality of word tokens in an input text, calculate a knowledge density for the plurality of word tokens, and calculate an information density for the plurality of word tokens using the POS density and the knowledge density. In some embodiments, the machine translation system may further comprise a sememe attacher and a context translator.

Context-aware machine language identification

Aspects of the invention include systems and methods configured to efficiently evaluate the efforts of a code migration (e.g., porting task) between different platforms. A non-limiting example computer-implemented method includes receiving a function of a source platform. The function can include a plurality of fields. An initial vector is constructed for each of the plurality of fields. The initial vector encodes a value of the respective field according to an encoding rule. The initial vectors are merged into a single final vector and the final vector is classified into one of a plurality of system function families of the source platform. A vector of a target platform at a minimum distance to the final vector is identified and an assessment is provided that includes a difficulty in porting a project comprising the function between the source platform and the target platform based at least in part on the minimum distance.

Fast porting of projects

A system and method are provided to determine at least one of equivalent isotropic radiated power (EIRP) or effective isotropic sensitivity (EIS) of an antenna under test (AUT) in a test chamber, the AUT including an antenna array with an array phase center that is offset from a center of a quiet zone of the test chamber. The method includes performing a local beam peak direction scan of an antenna pattern of the AUT using a probe antenna located at laterally offset positions at a near-field distance from the AUT to determine a beam peak direction; performing EIRP and/or EIS near-field measurements of the AUT in the determined beam peak direction using the probe antenna located at near-field distances from the AUT in a radial direction; deriving a far-field equivalent of the EIRP and/or EIS near-field measurement along the determined beam peak direction; and deriving the beam peak direction of the AUT.

System and method for performing measurements of antenna under test offset from center of quiet zone

Aspects include determining a coding intention and a dimension of interest to a user. A plurality of relevant projects that each include a logical code block that meets the coding intention are located. The locating includes searching a plurality of code repositories based at least in part on the coding intention. A score is assigned to each of the plurality of logical code blocks based at least in part on properties associated with the logical code blocks and on the dimension of interest to the user. A logical code block with the highest score is promoted to the user.

Dynamic code snippet promotion

The present disclosure provides a computer-implemented method, computer system and computer program product for text processing. The present in invention may include obtaining an original text input from a collaborative development environment. The present invention may include extracting a first text statement from the original input text. The present invention may include calculating a similarity value between the first text statement and a second text statement, wherein the second text statement is obtained from a statement database. The present invention may include comparing the similarity value to a pre-set threshold.

Text standardization and redundancy removal

A multi-layer language translator operating in conjunction with a syntax-based model, coupled with machine learning and artificial intelligence, performs language translations from a source language text to text expressed in a target language. A relevancy-based 'chunking' module breaks a source text into smaller units and applies a part-of-speech tag to some or all of the units. A hierarchy-based structuring module determines grammatical structure of the source text based, at least in part, on the applied part-of-speech tags. The hierarchy-based structuring module recursively combines grammatically linked units into one or more phrases, and applies to the phrases higher-level tags. A syntax-based translating module translates the units and/or phrases into the target language, and based on syntax differences between the source and target languages, reconfigures the translated text, as needed, such that the translated text is expressed in the target language using target language syntax rules and conventions.

Syntax-based multi-layer language translation

Embodiments for locating performance hot spots include collecting sample data having instruction addresses, the sample data being for a neural network model and determining instructions in the instruction addresses that are performance hot spots. A listing file is used to map the instructions of the sample data that are performance hot spots to locations in a lower-level intermediate representation. A mapping file is used to map the locations of the lower-level intermediate representation that are performance hot spots to operations in one or more higher-level representations, one or more of the operations corresponding to the performance hot spots, the mapping file being generated from compiling the neural network model.

Locate neural network performance hot spots

Growing community of inventors

Beijing, China

Li Cao