South Korean researchers have successfully developed a core technology that can fundamentally resolve "memory shortages," a chronic bottleneck in large-scale artificial intelligence (AI) training. This technology is a next-generation memory expansion technology based on Ethernet, which is expected to drive infrastructural innovation across the entire AI and big data industries in the future.

Drones are becoming increasingly common in densely populated urban centers, supporting applications ranging from parcel delivery to surveillance. However, their growing presence has introduced significant challenges related to safety, congestion, and coordination in low-altitude airspace.

Researchers at Carnegie Mellon University are investigating how humans respond to artificial intelligence agents that sound physically present in the same room, work that could shape the future of audio-only AI systems used in smart glasses, accessibility tools and other screen-free technologies.

When you ask a large language model a question, the reply may include falsehoods, and if you challenge those statements with facts, the AI may still uphold the reply as true. That's what my research group found when we asked five leading models to describe scenes in movies or novels that don't actually exist.

Near misses like the one at New York's John F. Kennedy International Airport inspired a group from the AirLab in Carnegie Mellon University's Robotics Institute (RI) to create World2Rules, an AI system that learns interpretable safety rules from data to analyze, verify, and explain potential collision scenarios.