Powering Through: Building Resilient Communities in the Face of Disruption
This review examines how to strengthen power systems and the communities they serve against increasingly frequent and severe disruptions.
Science
Beyond the Hype: Real-World AI Security Concerns Emerge
A new analysis of developer forums reveals a disconnect between theoretical AI risks and the practical security challenges faced in building and deploying AI-powered projects.
Predicting Bitcoin’s Future: Global Money Supply as a Key Indicator
A new expert system leverages global liquidity data alongside advanced time-series forecasting to achieve more accurate long-term Bitcoin price predictions.
AI’s Growing Power: A New Framework for Responsible Development
![The ARC framework establishes a recursive approach to reasoning, wherein complex problems are decomposed into simpler subproblems until reaching a base case solvable with a defined operator [latex] \mathcal{R} [/latex], thus enabling compositional generalization and systematic program execution.](https://arxiv.org/html/2512.22211v1/arc_overview3.png)
As artificial intelligence systems gain increasing autonomy, a structured approach to managing their potential risks is becoming critical.
Beyond Defense: AI Agents and the Future of Cyber Resilience
As cyberattacks grow more sophisticated, a new security paradigm is emerging that leverages intelligent, autonomous AI agents to adapt and respond to threats in real-time.
Predicting CAT Bond Risk with Climate Data
A new study explores how incorporating climate variability indices into machine learning models can improve the pricing and risk assessment of catastrophe bonds.
Weathering the Storm: Predicting Power Outages with AI
A new machine learning framework leverages weather patterns and socio-economic data to forecast power disruptions caused by extreme events.
Fortifying AI: A Proactive Defense Against Emerging Threats
As artificial intelligence systems become increasingly integrated into critical infrastructure, securing them against adversarial attacks and data manipulation is paramount.
Leveling the Playing Field: Machine Learning for Rare Conditions in the ICU
Predictive modeling in emergency and critical care often struggles with limited data for the most serious-but least frequent-conditions.
Beyond Pairwise Connections: A New Network Robustness Predictor
Researchers have developed a novel approach to assessing the resilience of complex networks by modeling higher-order interactions, offering a more accurate prediction of cascading failures.