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AnthropicAnnouncement
Anthropic opens Seoul office
Summary
Anthropic has opened its Seoul office and announced partnerships with Korean enterprises, startups, researchers, and the Ministry of Science and ICT. Through an MOU, the company will collaborate on AI safety and cybersecurity, including Korean-language model-safety evaluation with the Korea AI Safety Institute and information exchange on AI-enabled cyber threats. Korean deployments described include Claude Code across NAVER’s engineering organization, Claude at LG, Hanwha, Samsung SDS, and Nexon, plus Claude-powered products and nonprofit use. Anthropic will provide Claude access to up to 60 NAIRL-affiliated researchers, launch Claude for Startups in Korea, and support developer events and a hackathon. The office is led by KiYoung Choi and is hiring across a range of roles.
Context
Anthropic opened a Seoul office to establish a long-term presence alongside Korean organizations shaping AI, while supporting Korea’s AI ambitions and the safe and responsible adoption of AI across the public sector.
Approach / What changed
Anthropic is expanding partnerships with Korean enterprises, startups, researchers, nonprofits, and government bodies; collaborating on AI safety and cybersecurity; providing Claude access to NAIRL-affiliated researchers; and supporting developers through Claude for Startups, meetups, Build Day, and a planned hackathon.
Takeaways
NAVER has deployed Claude Code across its entire engineering organization, where thousands of engineers use it to diversify coding tools and increase coding productivity.
Anthropic’s MOU with Korea’s Ministry of Science and ICT includes Korean-language model-safety evaluation with the Korea AI Safety Institute and exchanges on AI-enabled cyber threats.
Claude access will be provided to up to 60 researchers affiliated with the National AI Research Lab, supporting research into safety, evaluation, alignment, robustness, and frontier AI.
Source and freshness
- Source
- anthropic.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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