Beyond Smart Devices: Building a Future with Agentic AI

A new architecture is needed to unlock the potential of truly autonomous physical systems and move beyond the limitations of today’s Internet of Things.

A new architecture is needed to unlock the potential of truly autonomous physical systems and move beyond the limitations of today’s Internet of Things.
As artificial intelligence increasingly manages critical infrastructure, a new approach to governance is needed to balance automation with human oversight and prepare for unforeseen disruptions.

A new approach leverages terrain connectivity and advanced machine learning to improve flash flood susceptibility mapping in the mountainous region of Himachal Pradesh.

New research shows that modeling the complex structure of Bitcoin transactions with hyperbolic graph neural networks significantly outperforms traditional Euclidean approaches.
A new framework leverages the power of artificial intelligence to automatically diagnose faults in intricate, high-dimensional event sequences.
A new framework leverages federated learning, knowledge graphs, and temporal transformers to improve early sepsis detection across multiple intensive care units.

New research reveals that artificial intelligence systems demonstrate surprisingly adept strategic reasoning when analyzing unfolding international crises, though reliable prediction remains a significant challenge.
![A system of interacting agents iteratively refines synthetic crisis-related tweets: a generator creates content, a compliance evaluator assesses its suitability, and a feedback augmenter relays evaluations back to the generator, with each accepted tweet accumulating over [latex]n[/latex] rounds to form a dataset [latex]\mathcal{D}\_{syn}[/latex], demonstrating a cyclical process of refinement inherent in complex systems.](https://arxiv.org/html/2603.13625v1/x1.png)
Researchers are using AI-powered workflows to generate realistic synthetic tweet datasets, overcoming the challenges of accessing real-time social media data during crises.
A new approach combines the power of machine learning with key indicators to forecast critical transitions in complex systems before they happen.

A new graph neural network model leverages spatial relationships to forecast how long power will be out after major storms.