Samsung Electronics Co., Ltd.

Dongsoo Lee

Sangjin Hyun

Hoonjoo Na

Wonkeun Chung

Sejung Kwon

Jaeyeol Song

Byeoungwook Kim

Suyoung Bae

Jae-Jung Kim

HyungSuk Jung

Jonghan Lee

Parichay Kapoor

Rakhwan Kim

Sangyong Kim

Jinkyu Jang

Baeseong Park

Sangho Jang

Seungha Oh

Minjung Park

Taehyun Kim

Daehyun Kim

Jaehyun Lee

Dongsuk Shin

Wandon Kim

Sangheon Lee

Hyung Joo Lee

Youngchul Cho

Doyoung Choi

Sangsu Lee

Seok Goh

Kangmin Jeon

Tae-Hwa Kim

Kyounghoon Han

Yeongkwang Lee

Jongpil Won

Seogho Lim

Changho Shin

Chanhoon Park

Guyeon Wei

Jonghun Lee

Saehyung Lee

Kyoungbok Cho

Sangkeun Ahn

Hyeji Shin

Yongkyun Park

Wooram Oh

Kibeom Kil

Kwanghoon Son

Anhi Pyun

Jinyi Lee

Sukbyung Chae

Jaeseoung Park

Chanhyeong Lee

A semiconductor device may include a channel pattern stacked on a substrate and a gate electrode on the substrate. The channel pattern includes semiconductor patterns. The gate electrode extends to cross the channel pattern. The gate electrode may include dielectric layers, first work function adjusting patterns, and second work function adjusting patterns. The dielectric layers may enclose the semiconductor patterns, respectively. The first work function adjusting patterns may enclose the dielectric layers, respectively, and the second work function adjusting patterns may enclose the first work function adjusting patterns, respectively. The first work function adjusting patterns may be formed of an aluminum-containing material, and each corresponding one of the first work function adjusting patterns may be in contact with a corresponding one of the second work function adjusting patterns enclosing the corresponding one of the first work function adjusting patterns.

Semiconductor device and method of fabricating the same

An electronic apparatus is provided. The electronic apparatus includes a memory configured to store one instruction or more and a processor configured to obtain output data by inputting input data to an artificial intelligence model including a plurality of layers by executing the instruction, and the artificial intelligence model is configured to output the output data based on operation through the plurality of layers and the processor is configured to encode operation data output from one of the plurality of layers and store the encoded operation data in the memory, obtain recovery data corresponding to the operation data by decoding the encoded operation data stored in the memory, and provide the obtained recovery data to another layer from among the plurality of layers.

Electronic apparatus for artificial intelligence model compression and method thereof

A semiconductor device includes a substrate including first and second regions, first and second active patterns provided on the first and second regions, respectively, a pair of first source/drain patterns on the first active pattern and a first channel pattern therebetween, a pair of second source/drain patterns on the second active pattern and a second channel pattern therebetween, first and second gate electrodes respectively provided on the first and second channel patterns, and first and second gate insulating layers respectively interposed between the first and second channel patterns and the first and second gate electrodes. Each of the first and second gate insulating layers includes an interface layer and a first high-k dielectric layer thereon, and the first gate insulating layer further includes a second high-k dielectric layer on the first high-k dielectric layer.

Semiconductor device and method of manufacturing the same

Provided is an electronic apparatus. The electronic apparatus includes a memory and a processor. The processor is configured to apply a low rank approximation using a matrix decomposition for a first square matrix among a plurality of square matrices based on parameter values of a deep learning model, and obtain a first approximated matrix and a second approximated matrix for the first square matrix, obtain second approximated matrices for each of a plurality of remaining square matrices other than the first square matrix among the plurality of square matrices, based on the first approximated matrix for the first square matrix, and store the first approximated matrix the first square matrix and the second approximated matrices for each of the plurality of square matrices in the memory.

Electronic apparatus and controlling method thereof

Disclosed are semiconductor devices and methods of manufacturing the same. The semiconductor device comprises a first transistor on a substrate, and a second transistor on the substrate. Each of the first and second transistors includes a plurality of semiconductor patterns vertically stacked on the substrate and vertically spaced apart from each other, and a gate dielectric pattern and a work function pattern filling a space between the semiconductor patterns. The work function pattern of the first transistor includes a first work function metal layer, the work function pattern of the second transistor includes the first work function metal layer and a second work function metal layer, the first work function metal layer of each of the first and second transistors has a work function greater than that of the second work function metal layer, and the first transistor has a threshold voltage less than that of the second transistor.

An integrated circuit (IC) device includes first and second fin-type semiconductor active regions on a substrate. A plurality of first semiconductor patterns are provided, which are stacked on the first fin-type active region as a first plurality of spaced-apart channel regions of a first FINFET. A plurality of second semiconductor patterns are provided, which are stacked on the second fin-type active region as a second plurality of spaced-apart channel regions of a second FINFET. A first gate structure is provided on the plurality of first semiconductor patterns. This first gate structure includes a first material region, which at least partially fills spaces between the first plurality of spaced-apart channel regions. A second gate structure is also provided on the plurality of second semiconductor patterns. The second gate structure includes second and third material regions, which at least partially fill spaces between the second plurality of spaced-apart channel regions.

Integrated circuits and method of manufacturing the same

A method for an electronic apparatus to perform an operation of an artificial intelligence model includes acquiring resource information for hardware of the electronic apparatus while a plurality of data used for an operation of a neural network model are stored in a memory, the plurality of data respectively having degrees of importance different from each other; obtaining data to be used for the operation of the neural network model among the plurality of data according to the degrees of importance of each of the plurality of data based on the acquired resource information; and performing the operation of the neural network model by using the obtained data.

Electronic apparatus and method of performing operations thereof

The present disclosure relates to a substrate transfer apparatus. The substrate transfer apparatus includes a first transfer apparatus, a second transfer apparatus, a substrate carrier driver, a sensor, a swing apparatus, and a controller. The first transfer apparatus is configured to transfer a substrate in a first direction. The second transfer apparatus is configured to receive the substrate from the first transfer apparatus and transfer the substrate and comprising a substrate carrier on which the substrate transferred from the first transfer apparatus is seated. The substrate carrier driver is configured to move the substrate carrier. The sensor is configured to detect an abnormal transfer of the substrate from the first transfer apparatus to the second transfer apparatus and generate a detection signal corresponding to the abnormal transfer of the substrate. The swing apparatus is configured to swing the substrate carrier. The controller is connected to the sensor and the swing apparatus and configured to control the swing apparatus based on the detection signal of the sensor.

Substrate transfer apparatus

An electronic device is provided. The electronic device includes a first memory configured to operate at a first speed and store compressed vectors corresponding to words, and scaling factors corresponding to the compressed vectors; a second memory that is faster than the first memory and is configured to store a first group of the compressed vectors, and store a first group of the scaling factors; and a processor configured to obtain a first compressed vector and a first scaling factor corresponding to an input word from the first memory or the second memory and process the obtained first compressed vector and the obtained first scaling factor by using a neural network.

Electronic device and operation method for embedding an input word using two memory operating speeds

A light emitting device includes a printed circuit board (PCB) substrate, a first ink layer covering the PCB substrate, the first ink layer having a first refractive index, light emitters on the first ink layer, and a second ink layer on the first ink layer and spaced apart from the light emitters, the second ink layer having a second refractive index different from the first refractive index.

Light emitting device with light emitting members on printed circuit board substrate

A fluid supply apparatus includes a container supply holder configured to supply a container to a cap separator using a loading box, the container including a detachable nozzle cap, and configured to store a process fluid, a cap separator configured to receive the container from the loading box and separate the nozzle cap from a container body of the container using a cap clamper and a rotation actuator, the cap clamper configured to clamp and hold the nozzle cap, and the rotation actuator configured to rotate the container body, a fluid supplier configured to supply the process fluid contained in the container body through a fluid supply line, and a controller configured to control the container supply holder, the cap separator, and the fluid supplier.

Fluid supply apparatus and substrate processing apparatus including the same

A decompression apparatus is provided. The decompression apparatus includes a memory configured to store compressed data decompressed and used in neural network processing of an artificial intelligence model, a decoder configured to include a plurality of logic circuits related to a compression method of the compressed data, decompress the compressed data through the plurality of logic circuits based on an input of the compressed data, and output the decompressed data, and a processor configured to obtain data of a neural network processible form from the data output from the decoder.

Decompression apparatus for decompressing a compressed artificial intelligence model and control method thereof

An electronic apparatus is provided. The electronic apparatus includes sample data and memory storing a first matrix included in an artificial intelligence model trained based on sample data, and a processor configured to prunes each of a plurality of first elements included in the first matrix based on a first threshold, and acquire a first pruning index matrix that indicates whether each of the plurality of first elements has been pruned with binary data, factorize the first matrix to a second matrix of which size was determined based on the number of rows and the rank, and a third matrix of which size was determined based on the rank and the number of columns of the first matrix, prunes each of a plurality of second elements included in the second matrix based on a second threshold, and acquire a second pruning index matrix that indicates whether each of the plurality of second elements has been pruned with binary data, prunes each of a plurality of third elements included in the third matrix based on a third threshold, and acquire a third pruning index matrix that indicates whether each of the plurality of third elements has been pruned with binary data, acquire a final index matrix based on the second pruning index matrix and the third pruning index matrix, and update at least one of the second pruning index matrix or the third pruning index matrix by comparing the final index matrix with the first pruning index matrix.

Electronic apparatus and control method thereof

Disclosed are ball jumping apparatuses and ball absorption methods using the same. The ball jumping apparatus comprises a fixing part, a moving part spaced apart from the fixing part, and a resilient member that connects the fixing part and the moving part to each other. The resilient member extends upwardly from the fixing part and has a connection with the moving part. The fixing part includes a fixing plate that spreads in a horizontal direction. The moving part includes an oscillating vessel that has a ball receiving space in which a ball is received, and an oscillator coupled to the oscillating vessel. A bottom surface of the oscillating vessel is upwardly spaced apart from a top surface of the fixing plate.

Ball jumping apparatus and ball absorption

Growing community of inventors

Suwon-si, South Korea

Dongsoo Lee