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By Jessica Heesen, University of Tübingen and Tori Smith Ekstrand, University of North Carolina at Chapel Hill The roll-out of the European Union’s Artificial Intelligence Act has hit a critical turning point. The act establishes rules for how AI systems can be used within the European Union. It officially entered into force on August 1 […]
By Better Images of AI Stewards We’re often told not to judge a book by its cover. And yet, a cover is often the reason why a reader first picks up a book. A book’s cover design is the window into its story and the author’s intentions. For Better Images of AI, in the context
Lone Thomasky & Bits&Bäume / Distorted Lava Flow / Licenced by CC-BY 4.0 By Seyedali Mirjalili, Torrens University Australia Poisoning is a term most often associated with the human body and natural environments. But it is also a growing problem in the world of artificial intelligence (AI) – in particular, for large language models such
What is AI poisoning? A computer scientist explains Read More »
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
Learning robust controllers that work across many partially observable environments Read More »
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
Review of “Exploring metaphors of AI: visualisations, narratives and perception” Read More »
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 Sangyun Lee and Giulia Fanti This blog post is based on the work BaNEL: Exploration Posteriors for Generative Modeling Using Only Negative Rewards. Tackling very hard problems The ultimate aim of machine learning research is to push machines beyond human limits in critical applications, including the next generation of theorem proving, algorithmic problem solving,
Learning from failure to tackle extremely hard problems Read More »
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
How AI can improve storm surge forecasts to help save lives Read More »
Drug repurposing often starts as a hypothesis: a known compound might help treat a disease beyond its original indication. A good example is minoxidil: initially prescribed for hypertension, it later proved useful against hair loss. Knowledge graphs are a natural place to look for such hypotheses because they encode biomedical entities (drugs, genes, phenotypes, diseases)
Rewarding explainability in drug repurposing with knowledge graphs Read More »
