Insilico Medicine raised a total of HKD 2.277 billion in its largest Hong Kong biotech IPO, with 94,690,500 shares offered globally and oversubscribed by approximately 1427 times. The company aims to advance its mission of extending human productive longevity using AI-powered drug discovery and development.
A new end-to-end framework, DarkAD, enhances anomaly detection in low-light environments by introducing a feature adapter that reduces noise and amplifies critical features. The model outperforms other state-of-the-art models in detecting subtle anomalies with high accuracy and speed.
SourceShibaura Institute of Technology·JournalResults in Engineering·TypeExperimental study·DateApr 30, 2025
A Lancaster University academic argues that AI and algorithms contribute to polarization, radicalism, and political violence, posing a threat to national security. The paper examines how AI has been securitized throughout its history, highlighting the need for better understanding and management of its risks.
SourceLancaster University·JournalTechnology in Society·TypeCommentary/editorial·DateNov 2, 2023
A team of researchers at Osaka University has created a machine learning system that can virtually remove buildings from a live view, streaming in real-time on a mobile device. This technology can help accelerate the process of urban renewal based on community agreement, reducing conflicts and delays.
SourceOsaka University·JournalJournal of Computational Design and Engineering·TypeComputational simulation/modeling·DateJul 26, 2022
Creality K1 Max 3D Printer
Creality K1 Max 3D Printer rapidly prototypes brackets, adapters, and fixtures for instruments and classroom demonstrations at large build volume.
Researchers aim to create a flexible security feature that learns from past cyberattacks and requires minimal human intervention. They'll collaborate with device developers to share solutions and improve future responses to attacks.
Computer scientists at the University of Leeds are developing a robotic autonomy system that combines automated planning with reinforcement learning. The robot learns to plan sequences of moves to reach objects in cluttered spaces, generalizing its abilities to new tasks.