Samsung Display Co., Ltd.

Lg Electronics Inc.

Hanon Systems

Snu Rdb Foundation

Makinarocks Co., Ltd.

Taeho Lee

Junwoo You

Jongwoo Han

Jaehong Kim

Hyoeun Kim

Hangil Jeong

Eui Jeong Kang

Seung Hwan Baek

Yong-Hoon Kwon

Hyejeong Jeon

Min-young Song

Dongmin Yeo

Atsushi Nemoto

Sunhee Oh

Byoung Dae Ye

Byoungdae Ye

Jeongjin Park

Doyoung Lee

Young-Min Park

Yoojin Choi

Sangwon Lee

Donghoon Kim

Joong-Hyun Kim

Donghyeon Lee

Dami Choe

Yongkyu Kang

Heeyeon Choi

Chan-Jae Park

Joonghyun Kim

Sanghyuck Yoon

Chang-Yuil Kang

Seunghwan Baek

Jinsung Choi

Seungsoo Ryu

Hyun-hwa Song

Sanghee Kim

Chan-jae Park

Chungseok Lee

Jeonghoon Lee

Joongjae Kim

Euijeong Kang

Boseop Kim

Sanghyeok Choi

Minseop Kim

Beomsuk Moon

Ikchan Ju

Chanjae Park

Junwoo Yoo

Hyun-Jun Youn

Yoon-Sook Lee

Kyoo-A Lee

Minjae Cho

Dong Jae Baek

Disclosed is a method for predicting areas of environmental information needed to be collected, which is performed by one or more processors of a computing device. The method may include: outputting one or more episodes based on environmental information; measuring uncertainty for each of the one or more episodes; and predicting an area of the environmental information needed to be collected based on the measured uncertainty.

Method for predicting the areas of information needed to be collected

An embodiment of the present invention provides, comprising: a communication unit configured to communicate with a plurality of external AI apparatuses; and a processor configured to receive sound signals of the user from the plurality of external AI apparatuses, calculate a distance and a variation of the distance from each of the plurality of external AI apparatuses to the user based on the received sound signals, determine a current path of the user based on the calculated distance and the calculated variation of the distance, and determine a future path of the user based on the current path.

Artificial intelligence apparatus for determining path of user and method for the same

Disclosed herein an artificial intelligence apparatus for updating an artificial intelligence model including a memory configured to store an artificial intelligence model and training data for the artificial intelligence model and a processor configured to receive sensor data, calculate a confidence level of the received sensor data for the stored artificial intelligence model, label the received sensor data if the calculated confidence level is less than a reference value, store the labeled received sensor data in the memory as the training data or test data, and update the stored artificial intelligence model using the stored training data.

Artificial intelligence apparatus and method for updating artificial intelligence model

A display device includes a display panel including a first pad on a base substrate, an adhesive pattern which faces the base substrate with the first pad therebetween, a circuit board electrically connected to the display panel at the first pad and including a second pad facing the first pad, and a plurality of conductive members between the first pad and the second pad to electrically connect the first pad and the second pad to each other. The first pad of the display panel has a planar shape, and each of the plurality of conductive members is within the planar shape of the first pad and penetrates the adhesive pattern to contact the first pad.

Display panel having conductive members contacting pad at opening in display panel layer

A laundry treatment device includes a washing module configured to perform operation related to washing, a camera configured to capture an image of a tag attached to a laundry, and a processor configured to acquire laundry information of a plurality of laundries, to convert the acquired laundry information into encoding data, and to acquire values of laundry control variables corresponding to the converted encoding data based on a laundry course learning model learned using a plurality of reference data through a deep learning algorithm.

Laundry treatment device and method of determining laundry course thereof

A window includes a base layer including a folding region in which a groove is defined and a non-folding region, and a resin disposed on the groove and including a thiol group, wherein a difference between the refractive index of the base layer and the refractive index of the resin is less than about 0.1.

Window and display device including the same

Disclosed is an artificial intelligence (AI) apparatus comprising: a short-range communication module configured for sensing a plurality of laundry treatment apparatuses positioned around the AI apparatus; and a processor configured for: acquiring laundry information about laundry and characteristic information of each of the detected laundry treatment apparatuses; determining a laundry group corresponding to the laundry, based on the acquired laundry information; comparing characteristic information of the determined laundry group and characteristic information of each of the plurality of laundry treatment apparatuses with each other; and determining a laundry treatment apparatus for washing the laundry among the plurality of laundry treatment apparatuses based on the comparison result.

AI apparatus and operation method thereof

An AI device is provided. The AI device includes a content output interface to output video data contained in content and voice data contained in the content, and a processor to control the content output interface to acquire a voice recognition result by providing, to a voice recognition model, content extraction information including at least one of video information acquired from the video data in the content or tag information of the content and the voice data, and control the content output interface to output the voice recognition result.

Artificial intelligence device

Disclosed herein is a washing machine including a first data acquirer configured to collect data related to a laundry pattern of a user, a second data acquirer configured to collect data related to context information, and a processor configured to provide the laundry pattern of the user and the context information to a reinforcement learning model as an environment and to train the reinforcement learning model using feedback of the user on a recommended laundry course when the reinforcement learning model recommends the laundry course.

Washing machine

Disclosed is a laundry scheduling apparatus. The apparatus includes a communication unit, an output unit, and a processor configured to pair with at least one washing machine via the communication unit, obtain laundry preference parameters of a user generated by learning based on at least one of a deep learning algorithm or a machine learning algorithm, using at least one of a laundry log of the user or laundry satisfaction information of the user as input data, generate laundry scheduling information by using washing machine information about the paired at least one washing machine, the laundry preference parameters, and laundry item information obtained via at least one of a user input unit, an interface unit, or a sensor, and cause the output unit to output the laundry scheduling information.

Laundry scheduling apparatus and method

A display device apparatus provides an increased color reproduction rate and/or contrast ratio. The display device includes a first substrate; a second substrate disposed on the first substrate; and a liquid crystal layer arranged between the first substrate and the second substrate. A reflective layer is disposed on the first substrate, a polarizing layer is disposed on one surface of the second substrate, and a metasurface pattern layer is disposed on the second substrate. The metasurface pattern layer includes a third substrate and a first metasurface pattern disposed on the third substrate.

Reflective display device

A laundry scheduling device according to an embodiment of the present invention includes an input interface that receives speech including a plurality of words respectively representing a plurality of laundry items from a use, and a processor that acquires one or more features represented by each of the plurality of words by inputting speech data corresponding to the received speech to a learning model and performing word embedding, and generates a laundry schedule of the plurality of laundry items based on the one or more features represented by each of the plurality of words.

Laundry scheduling device

An AI device is provided. The AI device includes a memory to store data, a voice acquisition interface to acquire a voice signal, and a processor to perform preprocessing for the voice signal based on a parameter, to provide the preprocessed voice signal to a voice recognition model, to acquire a voice recognition result, to store a characteristic of the preprocessed voice signal in the memory, and to change the parameter using a distribution of characteristics of voice signals accumulated in the memory.

Artificial intelligence device with a voice recognition

An artificial intelligence apparatus for recognizing a user includes a camera, and a process configured to receive, via the camera, image data including a recognition target object, generate recognition information corresponding to the recognition target object from the received image data, calculate a confidence level of the generated recognition information, determine whether the calculated confidence level is greater than a reference value, if the calculated confidence level is greater than the reference value, perform a control corresponding to the generated recognition information, and if the calculated confidence level is not greater than the reference value, provide a feedback for the object recognition.

Artificial intelligence apparatus for recognizing user from image data and method for the same

A display device includes a display panel, a light guide plate, a first light source unit, and an optical member. The light guide plate is on the display panel. The first light source unit is configured to provide light to a side surface of the light guide plate. The optical member is between the light guide plate and the display panel. The optical member includes an interconnection layer, an optical pattern unit including first optical patterns on a surface of the interconnection layer, and first pattern shaping wires configured to receive a control voltage from the interconnection layer and to control a shape of each of the first optical patterns via the control voltage. Each of the first optical patterns is connected to a respective some of the first pattern shaping wires.

Display device having optical member, optical member controlled with pattern shaping wires, and method of fabricating optical member

Growing community of inventors

Seoul, South Korea

Taeho Lee