AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,981 papers
This paper proposes a novel cryptographic key exchange protocol leveraging concepts inspired by quantum mechanics, specifically superposition and probabilistic exploration, through a graph-based routing mechanism. Traditional key exchange protocols often rely on computationally intensive mathematical problems, making t...
The simulation of quantum systems on classical computers faces significant challenges due to the exponential scaling of computational resources required to accurately represent quantum states and their evolution. This work proposes a novel approach to quantum computing simulation based on graph representation and graph...
This paper proposes a novel approach to distributed edge computing resource scheduling based on consensus mechanisms. Traditional edge computing resource management often suffers from inefficiencies due to manual allocation, lack of real-time adaptability, and limited scalability. This research addresses these limitati...
Climate tipping points—abrupt, potentially irreversible transitions in Earth subsystems such as the Atlantic Meridional Overturning Circulation (AMOC)— represent one of the most consequential risks in climate science. Existing early-warning indicators based on critical slowing down (rising variance and autocorrelation)...
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The integration of intelligent multiple access technologies, edge intelligence and advanced antenna technologies would be critical for reliable and scalable wireless networks that would be able to support next generation applications such as extended reality, autonomous systems and large-scale IoT systems.
This paper proposes a novel approach to edge computing resource sharing leveraging blockchain technology. Traditional edge computing platforms often suffer from centralized control, leading to vulnerabilities and a suboptimal utilization of resources. This research introduces a decentralized system where edge computing...
This paper proposes a novel approach to distributed edge computing resource scheduling based on consensus mechanisms. Traditional edge computing resource management often suffers from inefficiencies due to manual allocation, lack of real-time adaptability, and limited scalability. This research addresses these limitati...
The proliferation of Internet of Things (IoT) devices has generated vast amounts of data, presenting significant challenges for centralized processing. Graph Neural Networks (GNNs) have emerged as a powerful tool for analyzing complex, interconnected data, particularly in applications like smart cities, industrial moni...
The energy sector is undergoing a profound transition from conventional, centrally managed electricity systems toward intelligent, connected and increasingly decentralized smart energy ecosystems. This transformation is being accelerated by Artificial Intelligence (AI), the Internet of Things (IoT), advanced data analy...
FINDING: Topological insulators are bulk-insulating but surface/edge-conducting quantum phases, with disorder-driven metal-TI transitions showing critical exponent ν≈2.7. | MATH: Critical exponent ν≈2.7 (from arXiv:1211.5026v2); topological invariant (Z₂ index) classifying band structure; bulk-boundary correspondence l...
FINDING: Topological insulators are bulk-insulating but surface/edge-conducting quantum phases, with disorder-driven metal-TI transitions showing critical exponent ν≈2.7. | MATH: Critical exponent ν≈2.7 (from arXiv:1211.5026v2); topological invariant (Z₂ index) classifying band structure; bulk-boundary correspondence l...
The energy sector is undergoing a profound transition from conventional, centrally managed electricity systems toward intelligent, connected and increasingly decentralized smart energy ecosystems. This transformation is being accelerated by Artificial Intelligence (AI), the Internet of Things (IoT), advanced data analy...
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.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
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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…
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
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.
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