AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,919 papers
The rapid expansion of edge computing and the Internet of Things (IoT) has transformed the deployment of intelligent applications by shifting computation from centralized cloud infrastructures to resource-constrained edge devices. Although this paradigm enables low-latency processing, reduced bandwidth consumption, and...
Vehicle-base station cooperative perception extends sensing coverage and detection precision in intelligent transportation systems. However, random task arrivals, heterogeneous communication-computing resources and short vehicle coverage residence time bring great difficulties to efficient task scheduling. To solve thi...
Paper V found that the buffer group ΠB = Ta/Tx, applied to cell sites whose buffers are unknown, predicted worse than exposure alone in two blind storms, and traced the failure to the unknown numerator. This paper moves the test to an edge where the numerator is written down. Since 1 December 2023 every ERCOT generatio...
Experiments show that CAS-YOLO improves detection accuracy within a YOLOv10n-based lightweight framework, and this study is strictly limited to civilian applications in public safety, traffic management, and autonomous driving assistance.
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This paper presents a comparative review and synthesis of the hyperscale data analytics cloud architectures of Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP). The review characterizes storage, processing, machine learning, data lake, governance and business intelligence services depending on...
======================================= GENSI™ INVENTTECH HUG & SOVEREIGN IP PROTOCOL ======================================= REGISTRANT: Stephan Richard Lee ORCID iD: 0009-0008-1177-3857 ASSIGNEE: GenSi Holdings LLC Georgia LLC Control Number: 26197798 LEGAL PERIMETER: Continuous Iterative Progress (CIP) Amendment Fra...
This chapter examines the human layer as the primary battlefield in AI-driven cybersecurity. While traditional cybersecurity has focused on networks, applications and data, autonomous AI systems shift adversarial activity toward human cognition, trust and decision-making. Systems like Anthropic's Mythos demonstrate tha...
A continuum-native agent paradigm is argued for that decomposes agents into intelligence, persona, and memory, allowing their independent placement, migration, and replication across the computing continuum, from cloud to edge, IoT, and emerging hardware platforms.
This research release develops a rigidity theory for sharp eigenvalue bounds on finite compact metric quantum graphs. Its central result is a proof candidate showing that, in the stated high-index regime, equality in a single sharp lower eigenvalue bound forces the full extremal spectral structure: maximal threshold mu...
The rapid integration of artificial intelligence (AI) into edge computing has enabled real-time, low-latency decision-making in safety-critical autonomous systems, including unmanned aerial vehicles (UAVs), V2X-connected vehicles, and roadside units. However, edge AI models are vulnerable due to limited computational r...
This systematic review and evidence map will assess how far TinyML and edge-AI systems for managed honey-bee (Apis mellifera) hive monitoring have progressed from offline algorithm development to physical on-device inference and validation under realistic apiary conditions. Deployment readiness is operationalised along...
The escalating computational demand of modern AI is increasingly constrained by the data-movement overhead of von Neumann architectures, motivating memristor-based compute-in-memory (CIM) as an energy-efficient alternative. Yet extending CIM to reliable analog computation remains difficult because practical memristor a...
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.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
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