AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Category
2,492 papers
The Internet of Things (IoT) is expected to reach up to 41 billion connected devices by 2030, driving a shift from centralised cloud computing toward edge computing, in which sensing, processing, and decision-making are performed closer to the data source. This shift reduces latency, bandwidth usage, and dependence on...
Tracing every edge and visiting every vertex are taken to be two forms of one problem. This paper shows that adding one and the same edge destroys only one of them──one has a certificate at each vertex and the other has none. No new theorem or law is claimed. Scope of this paper (scope note): No new theorem or law is c...
The proposed PINN introduces a specialized physical loss coupling thermochemical energy balances with adsorption kinetics, driven by instantaneous edge inputs for direct SOC tracking, and demonstrates higher predictive accuracy than the conventional NN across all key outputs, relative to a high-fidelity white-box dynam...
Aims: This study develops a dynamic explanation for the gap between task-level artificial intelligence productivity and durable enterprise value. It introduces verification debt, the accumulated stock of unverified assumptions, weak review, concealed dependencies, deferred validation, and capability loss. Study Design:...
Reach audiences
Advertise in front of researchers, engineers, and readers.
In edge computing scenarios such as unmanned aerial vehicle (UAV) patrol and vehicular perception, moving object extraction is highly susceptible to failure under low-light, inclement weather, and low-framerate conditions because of constrained sensor signal-to-noise ratio (SNR) and environmental interference. Existing...
【概要 / Abstract (English & Japanese)】 Hyper-scale artificial intelligence (AI) compute infrastructure and advanced semiconductor manufacturing (2nm, A16 nodes and beyond) face severe physical bottlenecks: the saturation of commercial power grids and the acute fragility of globally centralized supply chains situated...
X-ray photoelectron spectroscopy analysis toolkit: high-throughput Voigt fitting and the analysis foundation around it. v0.2.0 adds two experimental diagnostics — how well a spectrum determines the Voigt widths, and energy-axis calibration on a Fermi edge — three runnable examples, and a set of corrections. No existing...
A companion manuscript reported a correspondence between light-nuclear structure and closure conditions on regular triangular polytopes, stating the results without disclosing the derivation. This manuscript supplies the method. We give the operation converting a subdivided triad into a tetrahedron, and show it is edge...
Isomorphic Collapse of the Primorial Modulus: Bypassing Arithmetic in Arbitrary-Precision Cryptanalysis: The 10-GHz Topological Routing Engine for Overcoming the Von Neumann Bottleneck in Large-Scale Integer Analysis Abstract Modern computational mathematics remains bounded by a fundamental material compromise: as the...
This repository contains the software and reproducibility materials associated with the study “Factorized Coordinated Double Deep Q-Learning for Multi-User Computation Offloading and Resource Allocation in Mobile Edge Computing.” The proposed Factorized Coordinated Double Deep Q-Network (FC-DDQN) separates the binary l...
What This IsThe NUMEN Autonomy Integrity Suite is a complete formal verification framework that establishesa mathematically certified chain of trust for measuring behavioral safety in autonomous AI sys‐tems. It consists of five integrated layers:autonomy_eval.py (933 lines) — A behavioral health measurement tool that e...
This record provides digital elevation models (DEMs) from post-event optical stereo satellite images following the 2026-08-26 ice-rock avalanche on the north flank of Langtang Lirung, Rasuwa District, Nepal. The DEMs were produced from Vantor WorldView-2, WorldView-3 and WorldView Legion 2/3 stereo images acquired 2026...
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
