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Top Deep Learning Companies in South Korea

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29 companies for Deep Learning in South Korea

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Narnialabs's Logo

Narnialabs

South Korea

A

11-50 Employees

2022

Key takeaway

Narnia Labs leverages deep learning through its AI-powered Generative Design technology, which aids in generating and exploring diverse product designs. This approach not only enhances design productivity but also minimizes development costs and time.

Reference

Core business

Narnia Labs | AI-powered Product Design

Algorithm LABS's Logo

Algorithm LABS

Seoul, South Korea

A

1-10 Employees

2017

Key takeaway

The company, Algorithm Labs, provides AI solutions to major domestic groups and has secured investments from top venture capitalists, positioning itself to contribute significantly to the popularization of artificial intelligence. They are actively engaged in research and development through collaboration with KAIST's KIXLAB and are focused on making AI accessible to everyone, which aligns with the growing importance of AI as highlighted by Gartner's predictions.

Reference

Core business

알고리즘랩스, Algorithm Labs

알고리즘 랩스는 AI 트레이닝과 코딩 없이 오직 아이디어만 가지고 AI 제작/시각화/제품 상용화까지 할 수 있는 서비스를 제공합니다.

AIMMO's Logo

AIMMO

Seongnam-si, South Korea

A

51-100 Employees

2016

Key takeaway

AIMMO's technology is poised to transform the machine learning workflow market by providing high-performance AI capabilities through its AIMMO Core™ platform, which ensures 99.9% accuracy and speed for machine learning operations. Their innovative approach to data management and collection systems positions them as leaders in the AI space, making them a key player in advancing deep learning solutions.

Reference

Service

AIMMO | AI Data Company

AIMMO Core, Enabling a data-powered tomorrow, AI Data company AIMMO

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Kakao Brain's Logo

Kakao Brain

Seongnam-si, South Korea

A

11-50 Employees

2017

Key takeaway

The company, Kakao Brain, emphasizes its expertise in large-scale AI models, which is highly relevant to the field of deep learning. Their commitment to advancing technology and creating valuable services highlights their contribution to the tech community.

Reference

Core business

카카오브레인

Our innovation is to contribute our world-leading technology on large-scale AI models and Digital Human to the tech community, and to create services that improve the value and quality of life.

Coxwave's Logo

Coxwave

Seoul, South Korea

A

11-50 Employees

2021

Key takeaway

The company is focused on developing analytics infrastructure to enhance AI products, emphasizing their mission to help AI learn from real-world data.

Reference

Core business

coxwave

Build Better Generate AI Application Faster

DEEPLY's Logo

DEEPLY

Seoul, South Korea

A

11-50 Employees

2017

Key takeaway

The company specializes in sound AI, which enhances safety and situational awareness by interpreting sounds. Their technology is particularly relevant in unmanned surveillance, detecting hazards and engine failures.

Reference

Core business

Deeply

Deeply protects the safety and happiness of the world through sound AI. Experience Listen AI, the world's most widely used sound artificial intelligence.

TUNiB's Logo

TUNiB

Seoul, South Korea

A

11-50 Employees

2021

Key takeaway

The company specializes in creating domain-specific conversational AI, emphasizing emotional engagement and the protection against AI-generated harmful content. Their expertise in NLP APIs could be relevant for those interested in deep learning applications.

Reference

Core business

TUNiB

Visang Education's Logo

Visang Education

Seoul, South Korea

A

501-1000 Employees

-

Key takeaway

Visang has been enhancing learning environments for 25 years, offering innovative edutech solutions like AllviA Connect Learning, which provides an optimized experience for educators and students.

Reference

Product

AllviA Connect Learning - Global Edtech Platform

RAONDATA | 라온데이터's Logo

RAONDATA | 라온데이터

Seoul, South Korea

A

1-10 Employees

2021

Key takeaway

The company develops multimodal deep learning models that utilize acoustic and visual features to detect depression and diagnose central serous chorioretinopathy (CSC) using spectral domain optical coherence tomography (SD-OCT) images. Their automated deep learning algorithms aim to enhance the analysis and diagnosis processes, demonstrating the potential of AI in medical applications.

Reference

Core business

RAONDATA | 라온데이터

RAONDATA - We build AI products

DMLab's Logo

DMLab

Seoul, South Korea

A

11-50 Employees

2020

Key takeaway

BEN's AI solutions utilize deep learning to deliver human-like responses and enhance user engagement through natural language processing and real-time problem-solving capabilities. Their systems are designed to provide personalized interactions, emphasizing comprehension and empathy in human-machine communication.

Reference

Core business

Ben | Personalizing AI Engagement

BEN's Al systems bring a deeper level of Comprehension, Empathy, & Understanding to human-machine interactions.


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Use cases around Deep Learning

A selection of suitable use cases for products or services provided by verified companies according to your search.

UseCase: EU-AI Act

Use case

EU-AI Act

All industries, Pharma, Finance, E-Mobility, Healthcare

er EU AI Act klassifiziert KI-Systeme in 4 Risikostufen: Verbotene KI: Soziale Bewertungssysteme, biometrische Echtzeit-Überwachung, manipulative Systeme Hochrisiko-KI: Kritische Infrastruktur, Bildung, Personalwesen, wichtige Dienste, Strafverfolgung Begrenzte Risiken: Chatbots (Transparenzpflicht), KI-generierte Inhalte (Kennzeichnungspflicht), Emotionserkennung Minimales Risiko: Alle anderen KI-Anwendungen ohne spezifische Auflagen Nachweis KI-Kompetenz: Unternehmen müssen dokumentieren, dass ihre KI-Systeme konform sind Verpflichtende Schulungen für Mitarbeiter im Umgang mit KI-Systemen Nachweis technischer Expertise im Entwicklungsteam Regelmäßige Überprüfung und Aktualisierung der KI-Kompetenzen Dokumentation von Risikobewertungen und Qualitätsmanagement Etablierung eines KI-Ethik-Boards für Hochrisiko-Anwendungen Inkrafttreten: 24 Monate nach Verabschiedung, Hochrisiko-Systeme: 36 Monate Übergangsfrist. Ziel ist ein sicherer, ethischer KI-Einsatz in der EU durch kompetente Anwendung und Überwachung.

UseCase: EU-AI Act

Use case

EU-AI Act

All industries, Pharma, Finance, E-Mobility, Healthcare

er EU AI Act klassifiziert KI-Systeme in 4 Risikostufen: Verbotene KI: Soziale Bewertungssysteme, biometrische Echtzeit-Überwachung, manipulative Systeme Hochrisiko-KI: Kritische Infrastruktur, Bildung, Personalwesen, wichtige Dienste, Strafverfolgung Begrenzte Risiken: Chatbots (Transparenzpflicht), KI-generierte Inhalte (Kennzeichnungspflicht), Emotionserkennung Minimales Risiko: Alle anderen KI-Anwendungen ohne spezifische Auflagen Nachweis KI-Kompetenz: Unternehmen müssen dokumentieren, dass ihre KI-Systeme konform sind Verpflichtende Schulungen für Mitarbeiter im Umgang mit KI-Systemen Nachweis technischer Expertise im Entwicklungsteam Regelmäßige Überprüfung und Aktualisierung der KI-Kompetenzen Dokumentation von Risikobewertungen und Qualitätsmanagement Etablierung eines KI-Ethik-Boards für Hochrisiko-Anwendungen Inkrafttreten: 24 Monate nach Verabschiedung, Hochrisiko-Systeme: 36 Monate Übergangsfrist. Ziel ist ein sicherer, ethischer KI-Einsatz in der EU durch kompetente Anwendung und Überwachung.

Information about Deep Learning in South Korea

The Deep Learning industry in South Korea is rapidly evolving, driven by significant government support and investment in technology. Key considerations include understanding the regulatory environment, which is becoming more robust to ensure ethical AI practices, data privacy, and security. Additionally, the competitive landscape features both established tech giants and innovative startups, making it crucial to identify niche markets and potential collaborations. Challenges such as talent shortages in specialized areas and the need for continuous research and development to stay ahead are prevalent. Opportunities abound, particularly in sectors like healthcare, autonomous vehicles, and finance, where deep learning applications can enhance efficiency and decision-making. Businesses must also consider the environmental impact of AI technologies, as energy consumption from data centers and training models is a growing concern. Moreover, South Korea's strategic position in the global market presents avenues for international collaboration and expansion. Companies looking to enter this industry should focus on building strong partnerships and investing in local talent to navigate these complexities effectively. Understanding consumer behavior and preferences in the South Korean market can further enhance the potential for success in deep learning applications.


Insights about the Deep Learning results above

Some interesting numbers and facts about your company results for Deep Learning

Country with most fitting companiesSouth Korea
Amount of fitting manufacturers18
Amount of suitable service providers9
Average amount of employees11-50
Oldest suiting company2016
Youngest suiting company2022

Frequently asked questions (FAQ) about Deep Learning Companies

Some interesting questions that has been asked about the results you have just received for Deep Learning

Based on our calculations related technologies to Deep Learning are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce

Start-Ups who are working in Deep Learning are Narnialabs, Coxwave, TUNiB, RAONDATA | 라온데이터

The most represented industries which are working in Deep Learning are IT, Software and Services, Other, Education, Biotechnology, Computer Hardware

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Deep Learning results by various countries

Related categories of Deep Learning