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AI & Enterprise

KAIST develops SafeQL to more easily fix AI database query errors

Researchers at the Korea Advanced Institute of Science and Technology have developed a way to fix errors that occur when AI converts natural-language questions into SQL database queries without rebuilding the whole command. The technology, called SafeQL, identifies and corrects only the wrong parts using database error information and stored data. It was implemented inside PostgreSQL and tested on Bird and Spider benchmarks, reducing token use and repair time while improving execution accuracy.

People & Appointments

Kakao launches \'Tech for Impact Campus\' at 13 universities nationwide

Kakao Impact Foundation said on Sept. 3 it will start the second-semester 2026 programme of its \'Tech for Impact Campus\' at 13 universities nationwide for 355 students. The course pairs students with social innovation organisations to develop ways to solve social issues using AI and digital technology. The programme began in 2023 at KAIST and had 482 students at nine universities through the first semester.

AI & Enterprise

KAIST develops AI that creates executable plans, from delivery routing to logistics

KAIST said a research team led by computer science professor Minsoo Kim developed a reinforcement-learning technique, RL-SPH, that trains AI to produce plans that satisfy real-world constraints without external optimisation software. The system searches first for a feasible plan and then reduces cost and time while keeping constraints. In benchmark tests it found feasible plans in all cases, improved solution-quality metrics and reduced search and training time versus other AI methods.