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...
Wai-Hung (Pan) Tam· Zenodo (CERN European Organi...· 0 citations
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/
David Ohnstad· Zenodo (CERN European Organi...· 0 citations
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...
Arash Mansourpour· Zenodo (CERN European Organi...· 0 citations
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...
Raffaele Bruno, Michela Natilli, Serge Fdida et al.· EPJ Research Infrastructures· 0 citations
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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...
Raghuram· Zenodo (CERN European Organi...· 0 citations
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...
Ikailo John Sessford· Zenodo (CERN European Organi...· 0 citations
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...
KokunoYumeto, OpenAI Codex· Zenodo (CERN European Organi...· 0 citations
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...
Taeho Lee· Zenodo (CERN European Organi...· 0 citations
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...
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...
Raghuram· Zenodo (CERN European Organi...· 0 citations
The study concludes that investing in network virtualization and edge cloud technology is highly viable, enabling telecommunication firms to minimize operational expenditures, optimize capital efficiency, and maximize Total Shareholder Return.
Saini Mahender, K. Shashidhar, K. Archan· International Journal of Dat...· 0 citations
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.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026
