edge computing

Quasi-static failure behavior and free-edge effect

HIOF•The Field — Series Note: Cover Sheet, Reading Order, and Statement of Contribution

Holographic Informational Ontology Framework - The Field (HIOF•tF) A short, non-technical companion to the four-part HIOF-tF series. Written for readers with a background in physics, information theory, or philosophy of science - not readers already familiar with the author's wider framework. The core idea, stated plai...

Edge Computing vs. Cloud Computing: Which is the Future?

As businesses strive to improve efficiency, reduce latency, and leverage the power of data, understanding the strengths and limitations of these two computing paradigms is crucial. Full article: https://davidohnstad.com/edge-computing-vs-cloud-computing-which-is-the-future/

ECI Framework v5.9.0 (Ecosystem Justice): A Quantum-Computing, Operational Consciousness-Metrics, and Distributed-Governance Framework for Autonomous AI Agents

ECI Framework v5.9.0 — Eternal Codex Infinitus An Integrated Framework for Quantum Computation, Operational Consciousness Metrics, and Distributed Governance of Autonomous AI Agents ECI Framework (Eternal Codex Infinitus) is an open-source Python framework that integrates three research domains into a single, tested so...

Designing a Pan-African Research Infrastructure for Digital Sciences: DIGITAfrica Vision, Blueprint Methodology, and Roadmap

This paper presents the vision, methodology, and deployment roadmap of DIGITAfrica, a Horizon Europe initiative preparing a pan-African Research Infrastructure in digital sciences, and introduces a blueprint-based methodology for specifying interoperable, incrementally deployable, and sustainable digital infrastructure...

mixingmatrix: optimal mixing matrices for graphs

Computes the edge weights that make averaging, gossip or a random walk converge as fast as possible on a given graph — the fastest-mixing Markov chain problem (Boyd, Diaconis & Xiao 2004) and its free-weight variant FDLA (Xiao & Boyd 2004). Returns a sparse weight matrix together with a rigorous bound on the distance f...

The identity component of a Jacobian lens inflates the noise floor computed from it

A transformer's residual stream adds each layer's output to what came before, so the corpus-averaged Jacobian lens J = E[dh_final/dh_l] contains a copy of the identity by construction, and its share grows with depth as less transformation remains above the layer: at the deepest fitted layer of the six lenses read here...

Program Matematika Indonesia v0.62.17 - Integrasi CLP v2.3.1

Start learning / Mulai belajar Bahasa Indonesia — open the learning map · English — open the learning map This update corrects two further missed, already-complete English editions: B80 Mathematical Computing (161 pages, 14 units, 75 exercises with hints and full solutions) and D50 Differential Geometry (658 pages, all...

EL-RAKHAWI'S AUTONOMOUS STABILITY NODE: A QUANTUM-RESILIENT, PHYSICS-INFORMED EDGE COMPUTING ARCHITECTURE FOR MICROSECOND GRID STABILIZATION AND CYBER-PHYSICAL IMMUNITY

EL-RAKHAWI'S AUTONOMOUS STABILITY NODE: A QUANTUM-RESILIENT, PHYSICS-INFORMED EDGE COMPUTING ARCHITECTURE FOR MICROSECOND GRID STABILIZATION AND CYBER-PHYSICAL IMMUNITY

neXus: A heterogeneous, horizontal, coordinate-addressed runtime network for agents and executable systems.

neXus is a horizontal fabric where heterogeneous software systems — servers, agents, edge devices, data centers, and even human-operated terminals — attach to a common peer-to-peer network through a single lightweight binary, nex. Every attached node speaks the same coordinate-addressed I/O interface, regardless of its...

APPLICATION OF INTERNET OF THINGS TECHNOLOGIES IN SMART MANUFACTURING SYSTEMS

The Internet of Things has become one of the key technological foundations of smart manufacturing. By connecting industrial machines, sensors, controllers, production lines, and information systems, IoT enables continuous data collection, real-time monitoring, remote control, predictive maintenance, and data-driven dec...

mixingmatrix: optimal mixing matrices for graphs

Computes the edge weights that make averaging, gossip or a random walk converge as fast as possible on a given graph — the fastest-mixing Markov chain problem (Boyd, Diaconis & Xiao 2004) and its free-weight variant FDLA (Xiao & Boyd 2004). Returns a sparse weight matrix together with a rigorous bound on the distance f...