articles

Researchers from Australia’s national science agency CSIRO, Federation University Australia and RMIT University have developed a method to improve the detection of audio deepfakes. The new technique, Rehearsal with Auxiliary-Informed Sampling (RAIS), is designed for audio deepfake detection — a growing threat in cybercrime risks such as bypassing voice-based biometric authentication systems, impersonation and disinformation. […]

In intelligent systems, applications range from autonomous robotics to predictive maintenance problems. To control these systems, the essential aspects are captured with a model. When we design controllers for these models, we almost always face the same challenge: uncertainty. We’re rarely able to see the whole picture. Sensors are noisy, models of the system are

IceMing & Digit / Stochastic Parrots at Work / Licenced by CC-BY 4.0 Better Images of AI and We and AI have been exploring the role of visual and narrative metaphors in shaping our understanding of AI. As part of this we invited some researchers who have been conducting different types of research into the

  Autonomous systems increasingly face value-laden choices. This blog post introduces the idea of designing “conflict-sensitive” autonomous traffic agents that explicitly recognise, reason about, and act upon competing ethical, legal, and social values. We present the concept of Value-Aligned Operational Design Domains (VODDs) – a framework that embeds stakeholder value hierarchies and contextual handover rules

By Navid Tahvildari, Florida International University Hurricanes are America’s most destructive natural hazards, causing more deaths and property damage than any other type of disaster. Since 1980, these powerful tropical storms have done more than US$1.5 trillion in damage and killed more than 7,000 people. The No. 1 cause of the damages and deaths from

By Isla C. Duporge, Princeton University The Great Wildebeest Migration is one of the most remarkable natural spectacles on Earth. Each year, immense herds of wildebeest, joined by zebras and gazelles, travel 800-1,000km between Tanzania and Kenya in search of fresh grazing after the rains. This vast, circular journey is the engine of the Serengeti-Mara

EZSpecificity combines extensive new enzyme-substrate docking data and a new machine learning algorithm to predict the best pairing for making a desired product, with up to 91.7% accuracy. Illinois professor Huimin Zhao led the study. Photo by Fred Zwicky. By Liz Ahlberg Touchstone A new artificial intelligence-powered tool can help researchers determine how well an