AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,919 papers
This release contains the source code used to produce the results reported in "Compact temporal-coding neurons for fast and energy-efficient edge computing". Please refer to the README for installation instructions, dependencies, and commands for reproducing the results. Full Changelog: https://github.com/ttttwwww/FNL-...
This is the extended, definitive version (v16.2) of the P0_Distilled research programme, with full technical appendices — it supplements the distilled entry-point paper (P0_Distilled_v0.1) with the complete Lakatosian structure, derivations, and experimental protocol. The programme's hard core is a single metaphysical...
《Quantum Environmental & Planetary Intelligence at the Limit: Water, Climate, Subsurface Systems, Pollution, Hazards, and Distributed Earth Sensing》 is a flagship-scale research volume exploring how quantum sensing, artificial intelligence, distributed observation, physical simulation, and planetary digital twins may...
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Abstract Woven cloth exhibits complex deformation behavior due to yarn-level interlacing structures, directional tension transfer, and the thermal response of fiber materials. In particular, when localized heat is applied, cloth does not simply shrink uniformly over its surface; instead, it forms pattern-dependent shri...
Developing high-performance optoelectronic neuromorphic hardware with specificity to the deep ultraviolet solar-blind spectrum, combined with transparency, multi-state capability, and persistent photoconductivity, is critical for solar-blind neuromorphic perception and autonomous monitoring. Here, we report a highly tr...
Papers I to III of this series built the buffer group ΠB = Ta/Tx for the edge between two infrastructure nodes, tested it plant by plant on the February 2021 Texas chain, and priced its hours with a cost group ΠC = ca/(vCd), all on one event. This paper reads a second. Winter Storm Elliott, 22 to 26 December 2022, ran...
We introduce the E8‑Phi Causal Tensor Network (EPC‑TN), which assigns each of the 240 E8 root vectors to a distinct causal edge in a brain‑wide tensor graph. By phi‑modulating a 132 Hz standing wave and coupling it to neuronal microtubule helices, the network self‑organizes into 120 paired harmonic eigenstates that cor...
The research examines the applications of sophisticated technologies like machine learning, blockchain, reinforcement learning, neural networks, edge computing, and the Internet of Things for solving challenges related to the scalability of MG systems.
《Quantum Environmental & Planetary Intelligence at the Limit: Water, Climate, Subsurface Systems, Pollution, Hazards, and Distributed Earth Sensing》 is a flagship-scale research volume exploring how quantum sensing, artificial intelligence, distributed observation, physical simulation, and planetary digital twins may...
Task offloading in End–Edge–Cloud computing enables resource-constrained User Devices (UDs) to execute computation-intensive applications with reduced latency and energy consumption. However, existing task offloading schemes generally overlook the heterogeneous privacy requirements of users, leading to inefficient priv...
Task offloading in End–Edge–Cloud computing enables resource-constrained User Devices (UDs) to execute computation-intensive applications with reduced latency and energy consumption. However, existing task offloading schemes generally overlook the heterogeneous privacy requirements of users, leading to inefficient priv...
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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