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Coded for glamour and glory, AI make-up arm steals the show in Hong Kong hackathon

Imagine a woman sitting at her vanity as a robotic arm reaches across the table, picks up her lipstick, and applies it to her lips while running through her morning schedule. Meet Iron Bestie, a personalised make-up assistant that just snatched top honours at what organisers billed as Hong Kong’s first physical artificial intelligence hackathon, beating more than 160 global competitors in an…

Coded for glamour and glory, AI make-up arm steals the show in Hong Kong hackathon

In a unique 48-hour hackathon, an AI-powered make-up arm won top honors in Hong Kong, beating out over 160 global competitors in a competition that combined hardware and software. The winning team comprised Luo Yuqing, a business information systems graduate from City University of Hong Kong with no formal coding experience, and Zeng Yitao, a senior algorithm developer from Southern University of Science and Technology in Shenzhen.

Iron Bestie, the personalized make-up assistant, utilized vision-language models and voice recognition to identify makeup on a table, select products based on a user's calendar, and apply them to the user's face. To ensure user data privacy, local redaction middleware was employed. Luo described a tangible feeling of connection when the robotic hand grasped her wrist, highlighting the potential of embodied AI.

Zeng credited their victory to a fully operational product, emphasizing the importance of deadlines in rapid technical development during hackathons. Hosted by Brizan Ventures, SpacemiT, and alloop.ai, the competition attracted over 1,000 applicants from around the world, with nearly 80% being students. While the winning team's algorithm was not particularly complex and two days were insufficient to create a market-ready product, the event showcased the potential of physical AI and inspired younger participants, including a team of secondary school students from Sha Tin College.

Written by urgent.news from SCMP Tech's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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