Aibrain Corporation

Hong Shik Shinn

Yeongju Kim

Run Cui

Cheongan Lee

Eunmi Hong

Byoung-Kwon Lim

Inhyuk Lee

Yi Hu

Won Taek Chung

Hye Jun Yu

Sungmin Lee

Jinhwal Lee

Dániel László Kovács

Taejun Kang

Sichang Yang

Hankyul Kim

An encoded artificial intelligence (AI) behavior specification is received. A data generation configuration specification is received. And a deep neural network configuration specification is received. A training data set based on the data generation configuration specification is generated. An AI behavior deep neural network that conforms to the deep neural network configuration specification is trained using at least a subset of the generated training data. The trained AI behavior deep neural network is provided from a remote AI add-in service to a development environment.

Adding deep learning based AI control

A plurality of images captured using a camera included in a robotic system are analyzed. A spatial map is generated using a sensor included in the robotic system. A semantic location map is generated using at least the analyzed plurality of captured images and the generated spatial map. A natural language input referencing a desired product item is received from a user. A speech recognition result is recognized from the natural language input and sent to a reasoning engine. In response to sending the recognized speech recognition result, one or more commands for the robotic system are received from the reasoning engine. The received one or more commands are performed and feedback to the user based on at least one of the one or more commands is provided.

Context aware interactive robot

A system comprises a motor and a base. The motor is configured to control the physical movement of the system and the base is configured to be coupled with a computing device. The computing device is configured to receive an indication of a target object and detect an obstacle object in a physical environment of the system. In response to detecting an obstacle object, the computing device provides to a user an inquiry associated with the detected obstacle object and receives a natural language response. Based at least in part on the natural language response, the computing device controls the motor to navigate the system around the detected obstacle object. Once the target object is detected, the computing device provides an indication that the target object has been located.

Interactive game with robot system

A specification of programmatic instructions is received. The specification uses instances of functional components connected together using specified links and includes the programmatic instructions for controlling a motorized base device. A simulation and debugging environment for the specification is provided and a distributable version based on the specification is generated. The distributable version is provided to a remote wireless device that executes the distributable version of the specification including by providing commands to the motorized base device based on the distributable version of the specification.

Intelligent robot software platform

An autonomous robotic system using an adaptive, interactive, and cognitive reasoner utilizing an advanced memory graph structure receives a natural language input. The natural language input is processed to identify components. At least a portion of the components of the natural language input is stored in a short-term artificial intelligence memory graph data structure. A long-term artificial intelligence memory graph data structure includes data that was previously stored in the short-term artificial intelligence memory graph data structure but is no longer stored in the short-term artificial intelligence memory graph data structure.

Adaptive, interactive, and cognitive reasoner of an autonomous robotic system utilizing an advanced memory graph structure

An artificial intelligence problem is solved using an artificial intelligence memory graph data structure and a lexical database to identify supporting knowledge. A natural language input is received and classified into components. A starting node of an artificial intelligence memory graph data structure, which comprises one or more data nodes, is selected to begin a search for one or more supporting knowledge data nodes associated with the classified components. Starting at the starting node, the artificial intelligence memory graph data structure is searched using a lexical database to identify the one or more supporting knowledge data nodes. An artificial intelligence problem is identified and solved using the one or more identified supporting knowledge data nodes of the artificial intelligence memory graph data structure.

Growing community of inventors

Seoul, South Korea

Hong Shik Shinn