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Naver, Kakao set licensing terms for commercial AI use
๐Ÿ‡ฐ๐Ÿ‡ท South Korea /Technology

Naver, Kakao set licensing terms for commercial AI use

From Chosun Ilbo · () Korean

Translated from Korean, summarized and contextualized by DistantNews.

At a glance

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  • Naver requires companies with over 10 million monthly active users to request a license for commercial use of its HyperCLOVA X SEED AI model.
  • Kakao's Kanana-2 AI model requires a separate license for on-device or on-premise sales.
  • This indicates a move by both tech giants to monetize their large-scale AI technologies.

South Korean tech giants Naver and Kakao are establishing licensing requirements for the commercial use of their advanced AI models, signaling a strategic push to monetize their investments in artificial intelligence.

Naver's HyperCLOVA X SEED AI model, designed for broad application, comes with specific terms for businesses. Companies that offer products or services with a monthly active user base exceeding 10 million will need to obtain a license from Naver for commercial deployment. This tiered approach suggests Naver aims to capture value from its most successful platforms leveraging its AI technology.

Similarly, Kakao is implementing licensing for its Kanana-2 AI model. Businesses looking to sell Kanana-2 in an on-device format or offer it as an on-premise solution to clients will require a separate license from Kakao. This move highlights Kakao's strategy to control and profit from the integration of its AI into various business infrastructures.

These licensing frameworks underscore the growing importance of large-scale AI models in the tech industry. Both Naver and Kakao are positioning themselves to benefit financially from the widespread adoption of their AI technologies, setting precedents for how AI services will be commercialized in the future.

DistantNews Editorial

Originally published by Chosun Ilbo in Korean. Translated, summarized, and contextualized by our editorial team with added local perspective. Read our editorial standards.