公开(公告)号：US20240346312A1

公开(公告)日：2024-10-17

申请号：US18750655

申请日：2024-06-21

申请人： Samsung Electronics Co., Ltd.

发明人： Jijoong MOON ,  Parichay KAPOOR ,  Jihoon LEE ,  Hyeonseok LEE ,  Myungjoo HAM

IPC分类号： G06N3/08 ,  G06N3/04

CPC分类号： G06N3/08 ,  G06N3/04

摘要： An electronic apparatus may include a memory configured to store data related to a neural network model and at least one processor configured to divide a learning step performed through a plurality of layers of the neural network model into a plurality of steps including a forward propagation step, a gradient calculation step, and a derivative calculation step, and determine an execution order of the plurality of steps, obtain first information regarding in which step of a plurality of steps according to the determined execution order a plurality of sensors used in the plurality of layers are used, based on the determined execution order, integrate the determined execution order based on the first information and second information regarding whether tensors used in neighboring layers from among the plurality of layers are able to be shared, allocate the data to the plurality of tensors by minimizing a region of the memory for allocating data corresponding to the plurality of tensors, based on the integrated execution order, and train the neural network model according to the integrated execution order using the plurality of tensors and the data allocated to the plurality of tensors. Various other embodiments are possible to be implemented.

公开(公告)号：US20210319282A1

公开(公告)日：2021-10-14

申请号：US17266781

申请日：2019-10-04

申请人： Samsung Electronics Co., Ltd.

发明人： Myungjoo HAM ,  Jijoong MOON ,  Jinhyuck PARK ,  Hyoungjoo AHN ,  Geunsik LIM ,  Jaeyun JUNG

IPC分类号： G06N3/04

摘要： The disclosure provides an electronic device and a method for controlling same. The electronic device comprises: a memory; and a processor, connected to the memory, for controlling the electronic device, wherein the processor executes at least one command stored in the memory, and is thereby capable of controlling scheduling of data processing of a plurality of artificial intelligence models on the basis of at least one of a data processing speed and a connection structure of the plurality of artificial intelligence models.

公开(公告)号：US20200341752A1

公开(公告)日：2020-10-29

申请号：US16855314

申请日：2020-04-22

申请人： Samsung Electronics Co., Ltd.

发明人： Geunsik LIM ,  Myungjoo HAM ,  Jijoong MOON ,  Wook SONG

IPC分类号： G06F8/71 ,  G06F11/36

摘要： An electronic apparatus for automatically performing a source code review and a method thereof are provided. The electronic apparatus includes a communication interface, a memory storing at least one instruction, and at least one processor to control the communication interface. The at least one processor, by executing the at least one instruction, is configured to, based on a source code being submitted to a source code repository with a pull request, receive a webhook event message from the source code repository through the communication interface, download the submitted source code from the source code repository, extract a changed source code among the downloaded source codes, and perform a code review of the extracted source code through at least one inspection module.

公开(公告)号：US20230144680A1

公开(公告)日：2023-05-11

申请号：US17437320

申请日：2020-11-24

申请人： SAMSUNG ELECTRONICS CO., LTD.

发明人： Jijoong MOON ,  Wook SONG ,  Sangjung WOO ,  Geunsik LIM ,  Jaeyun JUNG ,  Myungjoo HAM

IPC分类号： G06F21/60 ,  G06N3/08 ,  G06N3/0464

CPC分类号： G06F21/602 ,  G06N3/08 ,  G06N3/0464

摘要： An electronic apparatus and a method for controlling thereof are provided. The electronic apparatus includes a memory storing an artificial neural network and metadata including information of at least one layer in the artificial neural network, and a processor configured to: acquire a security vector based on the metadata and a security key of the electronic apparatus; map the security vector and the metadata with the security key and identification information of the artificial neural network; perform encryption on the at least one layer based on the metadata and the security vector; based on input data input to the artificial neural network, load the metadata and the security vector by using the security key and the identification information of the artificial neural network; and perform an operation between the input data and the encrypted at least one layer based on the loaded security vector and the metadata.