As financial technology matures and cryptocurrencies become increasingly popular, the security of blockchains used to process these transactions has emerged as a significant concern. Prof. Allen Men Ho AU, Associate Head (Research and Development) and Professor of the Department of Computing at The Hong Kong Polytechnic University, has introduced the Regulatable Privacy-Preserving Smart Contracts (RPSC), a smart contract system that effectively balances privacy with public transparency. RPSC’s compatibility has been demonstrated on Ethereum smart contract. As financial technology matures and cryptocurrencies become increasingly popular, the security of blockchains used to process these transactions has emerged as a significant concern. Prof. Allen Men Ho AU, Associate Head (Research and Development) and Professor of the Department of Computing at The Hong Kong Polytechnic University, has introduced the Regulatable Privacy-Preserving Smart Contracts (RPSC), a smart contract system that effectively balances privacy with public transparency. RPSC’s compatibility has been demonstrated on Ethereum smart contract. 

Autonomous driving systems increasingly rely on data-driven approaches, yet many still struggle with reasoning, handling rare scenarios, and transparently explaining their actions. A new study introduces DriveMLM, a multi-modal large language model framework that aligns language-based reasoning with structured behavioral planning states, enabling full closed-loop driving in realistic simulators. By integrating multi-view images, LiDAR inputs, traffic rules, and natural-language instructions, DriveMLM generates both driving decisions and human-readable explanations that map directly to vehicle control. The system significantly improves safety, adaptability, and interpretability, demonstrating how large language models (LLMs) can advance the next generation of autonomous driving technology.

A comprehensive review in Current Molecular Pharmacology highlights how machine learning, molecular dynamics simulations, and hybrid AI-MD platforms are revolutionizing antimicrobial discovery. These computational strategies can drastically reduce development time and costs while enabling the design of novel antibiotics and antimicrobial peptides. The authors propose an integrated “computation-experiment-clinical translation” framework to overcome current bottlenecks and combat the global AMR crisis.

Abu Dhabi, United Arab Emirates – The United Arab Emirates has launched Abu Dhabi’s AI Ecosystem for Global Agricultural Development, a platform designed to bring AI solutions to climate-exposed agricultural regions and support the communities most affected by shifting weather patterns.

Meet the robotic dog with a memory like an elephant and the instincts of a seasoned first responder. Developed by Texas A&M University engineering students, this AI-powered robotic dog doesn’t just follow commands — it sees, remembers and thinks. Designed to navigate chaos with precision, the robot could revolutionize search-and-rescue missions, disaster response and many other emergency operations. With cutting-edge memory and voice-command capabilities, it’s not just a machine. It’s a game-changing partner — and the smartest dog around — in emergencies.