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AI & Enterprise

KAIST develops tech to cut sensory confusion and hallucinations in multimodal AI

Researchers in South Korea have developed techniques to reduce cases in which AI confuses multiple sensory inputs or generates nonexistent information. KAIST said a team led by professor Yong-man Ro developed two methods to improve sensor understanding in multimodal large language models and reduce confusion between visual and audio data. The approaches are designed to work with less data or be applied without retraining. KAIST said the technology could be used in autonomous driving, rescue robots, drones and medical AI.

Games & Commerce

Naver unveils core technology behind AI Tab

Naver has unveiled key technologies used in its conversational AI search service AI Tab, which it launched on June 25. At a tech session in Seoul, it introduced a specialised lightweight model based on HyperCLOVA X, an operating framework called harness engineering, and Smart Lens-based multimodal technology. Executives said AI Tab must deliver conversational answers every time a user selects the tab, requiring high quality, speed, cost efficiency and stability at scale.

Mobility

Xpeng unveils predictive autonomous driving AI framework X-Mind

Xpeng unveiled X-Mind, a vehicle AI framework designed to predict and reason about future traffic conditions before an autonomous vehicle acts. Presented at a CVPR 2026 workshop in Denver, the system shifts autonomous driving from a perception-action model to a prediction-and-reasoning structure. It uses a “Thought Sketch” of key driving elements rather than generating full future video, aiming to cut computation, improve real-time performance and make decision processes visual and easier to verify.