🍇@COP_PILOT_Horizon's Cluster 4 completed its 3rd pilot at Filipe Palhoça Vinhos, showcasing smart viticulture through soil sensors, drone monitoring, edge computing & vineyard analytics in one interoperable workflow.
The pilot validated scalable digital services for sustainable agriculture with feedback from 40+ vineyard stakeholders.
📰 Read more: https://cop-pilot.eu/2026/05/12/cop-pilot-cluster-4-avipe-2026/
⚡ COP-PILOT joined AIOTI’s workshop on #5G/#6G & Edge Intelligence.
Rolf Riemenschneider (European Commission) highlighted Europe’s shift toward smarter, distributed energy infrastructures, while #CEISphere showcased collaboration across the Cloud-Edge-IoT ecosystem.
EnakronIC presented COP-PILOT Cluster 3E pilots on smart grids, EV charging & biogas monitoring.
This year’s COMPUTEX theme “AI Together” sets the stage for Shuttle’s powerful AI edge computing solutions designed for the applications of tomorrow. Our platforms combine performance, stability and scalability – for reliable AI right at the edge.
📍 Meet us at COMPUTEX 2026
Booth No. R0114, Nangang Hall 2, 4F
#Shuttlecomputer #COMPUTEX2026 #AITogether #EdgeComputing #AI
AI Strategy Has a Blind Spot: The Network
AI 인프라 투자에서 GPU에 집중하는 동안 네트워크 인프라의 중요성은 간과되고 있다. AI 트래픽은 전통적인 네트워크 트래픽과 달리 GPU 간 대량의 동기화된 데이터 교환이 필요하며, 작은 패킷 손실도 GPU 효율에 큰 영향을 미친다. 특히 추론 워크로드가 엣지와 클라우드 전역으로 분산되면서 네트워크 가시성과 최적화가 AI 성공의 핵심 요소가 되고 있다. 기업들은 네트워크를 AI 스택의 필수 구성 요소로 인식하고, 분산 추론을 위한 네트워크 전략과 가시성 확보에 투자해야 한다.
https://www.kentik.com/blog/your-ai-strategy-has-a-blind-spot-the-network/
#aiinfrastructure #networking #gpu #inference #edgecomputing
Enterprises are pouring billions into GPUs and AI compute, but most are overlooking the infrastructure that connects it all. Justin Ryburn, field CTO at Kentik, makes the case that the network is the most underestimated variable in whether AI initiatives succeed or fail.
Architecting on Cloudflare
이 글은 Cloudflare의 개발자 플랫폼(Workers, Durable Objects, D1, R2, Workers AI 등)을 중심으로 클라우드 아키텍처 설계와 평가 방법론을 제시한다. 저자는 AWS, Azure, GCP와 비교해 Cloudflare가 제공하는 글로벌 배포, 즉각적 확장, 콜드 스타트 없는 실행 환경 등 기술적 장점을 강조하며, 실제 운영 경험을 바탕으로 한 한계와 적합성 평가 기준도 솔직하게 다룬다. 이 책은 클라우드 아키텍처에 익숙한 개발자, 솔루션 아키텍트, 기술 리더들이 Cloudflare를 기존 하이퍼스케일러 대비 검토하고 도입 여부를 판단하는 데 실질적 도움을 준다.
https://architectingoncloudflare.com/
#cloudflare #serverless #edgecomputing #developerplatform #cloudarchitecture
Future-proof your network with AMD EPYC 8005 Server CPUs! 🚀
Optimized for vRAN and open architectures, these processors deliver up to 84 cores of performance-per-watt leadership. Reduce operational costs, enhance 5G LDPC decoding, and scale efficiently from the rugged edge to the cloud.
At CTCservers, we provide the AMD-powered infrastructure your business needs to innovate without overspending. 📡
Read More: https://www.ctcservers.com/blogs/amd-epyc-8005-vran-efficiency/
Error 500 en Cloudflare Pages: cómo resolverlo
¿Tu sitio en Cloudflare Pages devuelve 500 en algunas páginas pero el build fue exitoso? Diagnosticá y solucioná el error 500 Cloudflare Pages con bisec...
https://donweb.news/error-500-cloudflare-pages-solucionar/
#cloudflarepages #error500 #debugging #deploy #edgecomputing
Основные события и обновления в сфере децентрализованных сетей на май 2026 года:
### Matrix и экосистема
* **Matrix Community Summit 2026:** Главное событие года пройдет в Берлине с **21 по 25 мая** в пространстве c-base. Основной фокус — «физический слой» сотрудничества: хакатоны, воркшопы по улучшению протокола и празднование Towel Day (25 мая).
* **Технические апдейты:** В начале мая представлены новые предложения (MSC), включая **MSC4460** (расширяемые события) и **MSC4458** (обработка входящего JSON в API сервер-сервер). Улучшена работа мостов: исправлены ошибки загрузки ключей устройств в mautrix и решены проблемы с тайм-аутами больших медиафайлов.
* **Безопасность:** Интегрированы новые иконки статуса сквозного шифрования (E2EE) «с первого взгляда» и автоматическая фильтрация ссылок через фреймворк Maubot.
### Yggdrasil и Mesh-сети
* **Оптимизация маршрутизации:** В последних сборках (апрель-май 2026) акцент сделан на использовании фильтров Блума для оптимизации поиска пиров и кэширования маршрутов. Это критично для масштабирования сети до уровня «интернета вещей».
* **Yggdrasil Jumper:** Проект активно развивается для решения проблем с NAT-busting, что ранее было «бутылочным горлышком» для новых узлов.
* **Инфраструктура:** Протокол всё чаще рассматривается как база для Edge Computing, благодаря криптографической идентификации узлов и нативной поддержке IPv6.
### Глобальные тренды и Open Source
* **LF Decentralized Trust:** В конце апреля Linux Foundation объявила о вступлении 10 новых членов (включая Espresso Systems и Horizen). Основной вектор на 2026 год — стандартизация токенизированных активов и децентрализованная идентификация (Identity).
* **Data Mesh:** Рынок децентрализованного управления данными показывает резкий рост. Основной тренд — переход от централизованных «озер данных» к доменным архитектурам, где владение данными распределено между участниками сети.
* **Развитие узлов:** В крупных проектах (например, Pi Network) запущены дорожные карты по массовому расширению глобальных нод для обеспечения устойчивости к цензуре и разделения нагрузки.
* #Matrix
* #Yggdrasil
* #MeshNetwork
* #Decentralization
* #OpenSource
* #DataMesh
* #EdgeComputing
* #P2P
* #E2EE
* #Web3
LAWS: A new transform operation turning LLM inference into cheap cache lookups
LAWS는 실제 작업 부하에서 학습하는 자기 검증형 파라미터화된 캐시 아키텍처로, 신경망 추론, 로보틱스, 엣지 컴퓨팅에 적용된다. 이 아키텍처는 입력 공간을 확장하는 전문가 함수 라이브러리를 구축하며, 추론 오차를 배포 시점에 검증 가능하게 한다. LAWS는 기존 Mixture-of-Experts와 키-값 캐시 기법을 일반화하며, 더 높은 표현력을 가진다. 또한, 작업 부하 엔트로피에 따른 전문가 라이브러리 성장, 다중 유닛 학습 가속, OTA 업데이트 대역폭 제한 등 다양한 이론적 결과를 제시한다. LLM 추론과 로봇 제어, 다중 에이전트 엣지 배포에 유망한 새로운 접근법이다.
We introduce LAWS (Learning from Actual Workloads Symbolically), a self-certifying inference caching architecture that builds a growing library of certified expert functions from deployment observations. Each expert covers a region of input space defined by a node in the Probabilistic Language Trie (PLT) of the base model and carries a formal error bound holding uniformly over all inputs. The central result is a self-certification theorem: for any input x, the LAWS approximation error is bounded by epsilon_fit + 2*Lambda(W)*C_E, where Lambda(W) is the model Lipschitz constant, C_E is the maximum embedding diameter, and epsilon_fit is the expert training error -- all checkable at deployment time without ground truth. We prove that LAWS generalizes both Mixture-of-Experts and KV prefix caching as special cases and is strictly more expressive than any fixed-K MoE or finite cache. Further results include a monotone hit rate theorem (any-match routing ensures coverage only increases), an expert library growth rate of O(2^H log N) where H is workload entropy, a fleet learning convergence theorem with Omega(K) speedup for K-unit fleets, and an over-the-air update bandwidth bound. We conjecture that LAWS is acquisition-optimal among stationary online caching algorithms and that the effective Lipschitz constant on the training distribution grows polynomially rather than exponentially in depth. Applications are developed for LLM inference, robotic control, and multi-agent edge deployment.
#Cloudflare announced the closed beta of Flagship - a feature flag service built directly into its global edge platform.
Teams can control feature rollouts and experiment without redeploying code, while evaluating flags locally in Cloudflare Workers instead of calling external flag services.
Learn more ⇨ https://bit.ly/4wdUHQL
#InfoQ #DevOps #ContinuousDelivery #LowLatency #EdgeComputing
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