Settlement layer, full annual accessibility panel, motorway access points, 2025 rail cross-section and NUTS-3 aggregates underlying the article "Spatial inequalities in motorway accessibility across Europe: a settlement-level panel, 2010–2025" (under review). Road distance and travel time from 282,870 settlements in th...
Anonymised for double-blind review· Zenodo (CERN European Organi...· 0 citations
Continuous ingestion of high-dimensional telemetry forces predictive networks into a severe space-time trade-off, where conventional outlier rejection algorithms dilute mathematical gradients with benign idle data and induce thermal throttling on local hardware. This study introduces an $\mathcal{O}(d)$ ternary quantiz...
The current paradigm of frontier AI continues to yield significant value, but as compute scaling faces potentially diminishing returns, future AI progress is unlikely to rely on a single, isolated breakthrough. The next wave of capability improvements will most likely emerge from a complex mix of extensions, hybrids an...
Carolyn Ashurst, Angus Shennan, Sylvester Kaczmarek et al.· Alan Turing Institute Resear...· 0 citations
The deployment of large-scale 32-bit neural networks is hindered by the escalating parameter sizes and inherent susceptibility to noise. Here, we present a non-volatile memory (NVM)-based probabilistic computing architecture, which harnesses both the stochastic nature and in-memory computing capabilities of NVM to enha...
Hongchao Zhang, Tianxiao Nie, Weisheng Zhao et al.· AIP Publishing· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Abstract Neurosymbolic AI and Zero Trust Architecture (ZTA) are increasingly proposed together as a combined approach to securing cloud-edge IoT continuums in federal and critical infrastructure sectors, on the premise that neurosymbolic systems can supply the explainable, robust threat detection that continuous-verifi...
Michel Brumley· Zenodo (CERN European Organi...· 0 citations
The Compatibility Ratio (CR) is introduced as a simple guideline for evaluating performance trade-offs between optimal hardware micro-architecture configurations across different workloads and shows that, for the considered accelerator, a DNN model-family optimized configuration might occupy an effective middle ground...
Lukas Groth, Andrija Nešković, Rainer Buchty et al.· ACM Transactions on Embedded...· 1 citation
This paper presents a comprehensive survey of techniques aimed at improving the energy efficiency and sustainability of Green AIoT systems and examines how AI-assisted techniques, including TinyML, edge AI, and intelligent computation offloading, complement traditional Green IoT mechanisms to reduce energy consumption.
Mislav Has, Fehmi Ben Abdesslem, Mario Kušek et al.· Applied Sciences· 0 citations
Experimental results show that the proposed algorithm coordinates heterogeneous computing resources between the cloud center and the edge and exhibits earlier empirical reward stabilization and lower task-violation rates than the compared learning-based baselines under the tested workload conditions.
Jian Song, Jing Wang, Jun-Fei Yan et al.· Applied Sciences· 0 citations
These quantitative findings demonstrate that tightly coupled hybrid co-processing, physically adjacent to the control electronics, is critical for extending the computational bound of Noisy Intermediate-Scale Quantum (NISQ) devices.
Akshay Joseph, R. Delhibabu· Frontiers of Computer Scienc...· 0 citations
This paper’s key contribution is a module extension for an existing ROS-focused container framework that leverages Kubernetes’ capabilities—controlled rolling updates, ROS-adapted readiness checks, distributed workload management, and embedded observability—to bridge cloud-native practices with robotics development.
Nicholas Hopf, Rafael Arrais, Pedro Melo et al.· Applied Sciences· 0 citations
The deployment of large-scale 32-bit neural networks is hindered by the escalating parameter sizes and inherent susceptibility to noise. Here, we present a non-volatile memory (NVM)-based probabilistic computing architecture, which harnesses both the stochastic nature and in-memory computing capabilities of NVM to enha...
Hongchao Zhang, Tianxiao Nie, Weisheng Zhao et al.· AIP Publishing· 0 citations
Quantum Reinforcement Learning (QRL) represents a novel approach to reinforcement learning that leverages the unique capabilities of quantum computing to enhance learning efficiency and enable the exploration of complex behavioral rules. This paper explores the theoretical foundations, design principles, and potential...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 28, 2026
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
