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[기획 기사] 3 rising AI/ML startups from South Korea
2020. 11. 19
The South Korean government announced a renewed focus on artificial intelligence early this year as part of the country’s plans for economic recovery post-Covid-19.
AI is already a key part of South Korea’s national strategy, but the nation wants to be one of the region’s top AI powerhouses by 2030. That might be a good idea, as AI and machine learning (ML) could address many of the challenges faced by Korean society, creating opportunities for startups to plug the gaps along the way.
We hear from three rising AI/ML startups in South Korea on their journey to tap into this burgeoning market.
The following responses have been edited for brevity and clarity.
Anipen is a 3D content development platform that enables enterprises to develop video communications and entertainment platforms.
What is your core business or tech use case for which you use an AI or ML-based solution?
We apply AI/ML to our own augmented reality (AR) motion sequence engine, which has its foundations in a sketch-based content authoring technology, where you can easily add motion to characters by simply drawing lines.
We apply AI/ML to automate the content creation process. We analyze the content that users create and convert them to another type of graphic. For example, if you upload content like images using our AR motion sequence engine, the AI/ML engine will analyze the objects and identify features such as a human face, body, etc. in the contents, and you can easily switch the objects into AR objects.
What inspired you to start an AI/ML startup?
We already had the motion sequence engine. So we thought that we could develop a totally different sequence-authoring and motion-rendering engine in combination with deep learning, which can analyze and use the objects in the pictures and videos.
We believe AI/ML will be one of the essential components in AR, virtual reality, and other extended reality (XR) developments. Even AR/XR glasses in the near future may have an image and video-based motion sequence engine.
How has being on the cloud and AWS helped your startup scale fast?
We’re using Amazon SageMaker to help label images for bounding box object detection and use Amazon Mechanical Turk to help us outsource work with public datasets, such as dataset labelling for segmentation and feature extraction.