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Artificial Intelligence / Machine Learning · 5

Automation / Agentic Systems · 5

Research Papers · 5

Embedded Systems · 5

Computer Systems · 5

Developer Tools / Open Source · 5

Cloud / Infrastructure · 5

Archived section

Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/28/2026
Recently

Large Language Model for Operations Research Formulation Selection in Multi-Warehouse Inventory Allocation

Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matches heterogeneous instance-level regimes induced by demand concentration, inventory imbalance, replenishment scale, service constraints, and forecast volatility. We study this issue as instance-wise operations research (OR) formulation selection, where each allocation instance is assigned to a solver-executable formulation from a candidate OR expert library. We propose a solver-guided large language model (LLM) framework for OR formulation selection, in which each OR expert corresponds to a MIP formulation encoding a distinct allocation priority. Authors: Jintao Xu, Yingzheng Ma, Jiong Dong.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matches heterogeneous instance-level regimes induced by demand concentration, inventory imbalance, replenishment scale, service constraints, and forecast volatility.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv7/28/2026
Recently

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models

Tabular Foundation Models (TFMs) have emerged as novel approaches for tabular predictive tasks, demonstrating competitive predictive performance to ensemble tree-based models. Most TFMs are trained and evaluated on independent and identically distributed data, but this assumption changes in real-world scenarios due to distribution shifts, which compromise the robustness of models. Limited research has been conducted of TFMs under distribution shifts. Authors: Malena Loza, David Chushig-Muzo, Eva Milara.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Tabular Foundation Models (TFMs) have emerged as novel approaches for tabular predictive tasks, demonstrating competitive predictive performance to ensemble tree-based models.

Primary paperarxivcs.LG
Original
Artificial Intelligence / Machine Learning
arXiv7/27/2026
Recently

ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding

Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric challenge: models must absorb knowledge from heterogeneous 2D and 3D medical images, and evaluation protocols must align with radiologists' clinical practice and provide an accurate, fine-grained and factualness-driven assessment. In this paper, we introduce ClinFusion, a vision-centric MLLM designed for holistic medical understanding that systematically addresses these limitations. We propose a compositional and cascaded vision encoder architecture featuring a Cascade Spatial-Aware Locality Fusion operator that unifies diverse 2D and native 3D medical image understanding within a fused encoder. Authors: Hangjie Yuan, Yichen Qian, Zhiwei Tang.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric challenge: models must absorb knowledge from heterogeneous 2D and 3D medical images, and evaluation protocols must align with radiologists' clinical practice and provide an accurate, fine-grained and factualness-driven assessment.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
IEEE Spectrum7/27/2026
Recently

Why AI-Driven Cognitive Systems Are Redefining Radar and Electronic Warfare

An overview of how mode-agile threats challenge static library radar/EW systems, and how AI/ML cognitive architectures enable adaptive, real-time countermeasures. What Attendees will Learn Why mode-agile threats render static library systems ineffective — Explore how wartime reserve modes and mode-agile emitters deploy unexpected frequencies, modulation techniques, and hopping schemes that cannot be matched against traditional threat databases, leaving legacy electronic protect, attack, and support systems unable to respond. How AI/ML techniques power cognitive radar/EW systems — Understand the roles of artificial neural networks (ANN), deep neural networks (DNN), fuzzy logic, and genetic algorithms in enabling autonomous threat classification, signal de-interleaving, and real-time countermeasure generation without human intervention.

Why it matters

Read this for the concrete reporting in Artificial Intelligence / Machine Learning: An overview of how mode-agile threats challenge static library radar/EW systems, and how AI/ML cognitive architectures enable adaptive, real-time countermeasures.

Trusted sourceType-whitepaperElectronic-warfare
Original
Artificial Intelligence / Machine Learning
Apple Machine Learning Research7/27/2026
Recently

Memory Efficient Audio Synthesis with Decoupled Temporal Depth Diffusion Transformers

Siri Expressive Voices synthesize rich, configurable speech in real time and entirely on device, powered by AFM 3 Core Advanced, Apple's most powerful on-device foundation model. This work presents the memory-efficient audio synthesis architecture behind that capability: a detokenizer that converts the semantic audio tokens emitted by the foundation model into high-fidelity audio within the tight compute and memory budget of the Apple Matrix Coprocessor (AMX).

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: Siri Expressive Voices synthesize rich, configurable speech in real time and entirely on device, powered by AFM 3 Core Advanced, Apple's most powerful on-device foundation model.

Official source
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/28/2026
Recently

Who is scientific code for? Maintaining human-readable landmarks in agent-written code

Scientific research involving code has long rested on the assumption that at least one person understands why the code exists. As scientists adopt coding agents, this assumption is breaking down. Drawing on an ongoing contextual inquiry of scientific programmers working with agentic tools (four cases to date), a survey of over 800 scientific programmers, and my own analysis workflows, this position piece describes how scientists are inventing personal conventions, "landmarking strategies", for marking which artifacts in a codebase are meant for human understanding and which are context for agents. Authors: Elle O'Brien.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Scientific research involving code has long rested on the assumption that at least one person understands why the code exists.

Primary paperarxivcs.HC
Original
Automation / Agentic Systems
arXiv7/28/2026
Recently

Distributing Security Controls Through Harness Engineering

AI coding agents are being adopted at historic speed, yet security and risk concerns remain the primary barrier to scaling agentic AI across organizations. Existing security controls for coding agents are not systematically distributed to engineering teams, and vendor-native solutions introduce ecosystem dependencies that may not suit every deployment context. This paper investigates whether off-the-shelf security controls can be implemented on commercial AI coding agents and scaled to a distributed user base via a custom agent harness. Authors: William Robert Gore.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: AI coding agents are being adopted at historic speed, yet security and risk concerns remain the primary barrier to scaling agentic AI across organizations.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/28/2026
Recently

RSIBench-Data: Benchmarking Data-Centric Research for Recursive Self-Improvement

Recursive self-improvement requires turning evidence of model failures into better models. Data-centric post-training research entails diagnosing capability gaps, designing and validating training-data strategies, and learning from checkpoint feedback. Can LLM agents automate this loop? Authors: Fanqing Meng, Lingxiao Du, Qiguang Chen.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Recursive self-improvement requires turning evidence of model failures into better models.

Primary paperarxivcs.SE
Original
Automation / Agentic Systems
arXiv7/28/2026
Recently

\textscIH-Benchmark: A Conflict-Centered Benchmark for Instruction-Hierarchy Robustness in LLM Applications

When a language model receives conflicting instructions from different priority levels, which one does it actually follow? This question lies at the heart of reliable LLM deployment. Existing benchmarks answer this only partially, often focusing on a single hierarchy edge or adapting public datasets with limited tool-use coverage. Authors: Conor McCauley, Zeliang Kan, Jason Martin.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: When a language model receives conflicting instructions from different priority levels, which one does it actually follow?

Primary paperarxivcs.CR
Original
Automation / Agentic Systems
arXiv7/28/2026
Recently

VetClaw: An Edge-Cloud Multimodal Agentic System for Veterinary Disease Screening

We present VetClaw, an edge-cloud multimodal agentic system for early veterinary disease screening. VetClaw uses a camera module as an edge sensing device and sends captured images, together with optional symptom descriptions, to a server-hosted vision-language model for zero-shot disease classification. The system separates agent interaction from workflow orchestration: OpenClaw provides scheduling, tool access, user interaction, and notification services on the edge device, while LangGraph manages the stateful screening workflow, including input validation, image transmission, model invocation, safety checks, conditional routing, failure handling, and structured logging. Authors: Syed Mhamudul Hasan, Anas AlSobeh, Hussein Zangoti.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: We present VetClaw, an edge-cloud multimodal agentic system for early veterinary disease screening.

Primary paperarxivcs.CV
Original

Archived section

Research Papers · 5

Research Papers
arXiv7/28/2026
Recently

LLM4OSC: Profile-Bound Natural Language Control with Deterministic Validation for Open Sound Control

Open Sound Control (OSC) is the dominant wire protocol for real-time parametric control in professional audio, live performance, and virtual production. Large language models can emit plausible OSC, but they hallucinate addresses, mishandle type tags, and fail under paraphrase- unacceptable in show-critical contexts. We present LLM4OSC, a local-first architecture in which models propose structured intent JSON over a human-reviewed device profile, and deterministic code validates, clamps, and encodes before any UDP send. Authors: Yuan-Yi Fan.

Why it matters

Read this for the paper's specific claim in Research Papers: Open Sound Control (OSC) is the dominant wire protocol for real-time parametric control in professional audio, live performance, and virtual production.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/27/2026
Recently

Designing Within the Lines: Practitioners' Perspectives and Visualisation Tool Evaluation in the Arabic Context

Design guidelines and best practices serve as references that support designers throughout the visualisation design process. While considerable effort has identified the elements that contribute to effective data visualisations, little attention has been paid to how language (scripts and reading direction), tool support, and cultural context also shape design decisions. As a result, assumptions of homogeneity persist, with visualisation practices predominantly benefiting users of English and left-to-right (LTR) scripts while overlooking the needs of over two billion Arabic script users. Authors: Muna Alebri, Noëlle Rakotondravony, Yassine Bechqito.

Why it matters

Read this for the paper's specific claim in Research Papers: Design guidelines and best practices serve as references that support designers throughout the visualisation design process.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/27/2026
Recently

Modeling Local Exploit Hazard - A Bayesian Framework for Quantifying Exploit Risk and Operational Efficiency

This paper presents a local exploit hazard model: a Bayesian framework that converts the global probabilities produced by an exploit likelihood model (ELM), such as the Exploit Prediction Scoring System (EPSS), into a daily exploit hazard rate for an organization's own assets. The model measures the exploit-prevention effectiveness of deployed controls as a probability distribution. That distribution is seeded from a subject-matter-expert opinion pool and updated through Beta-Binomial inference from telemetry, breach-and-attack simulation, or penetration testing, then applied to ELM scores by attack-vector alignment. Authors: Stephen Shaffer, Laura Voicu.

Why it matters

Read this for the paper's specific claim in Research Papers: presents a local exploit hazard model: a Bayesian framework that converts the global probabilities produced by an exploit likelihood model (ELM), such as the Exploit Prediction Scoring System (EPSS), into a daily exploit hazard rate for an organization's own assets.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/28/2026
Recently

From Role Prompt to Infinite Thinking: Exploiting Persona Conditioning for Inference Cost Attacks in LLMs

LLMs are increasingly deployed in real-world applications, making inference efficiency and service reliability critical concerns due to their substantial computational costs. However, the autoregressive generation mechanism of LLMs enables malicious prompts to manipulate generation behaviors, inducing excessive token generation that amplifies computational consumption and threatens service efficiency. Existing methods mainly rely on adversarial suffixes or explicit extension instructions, which introduce detectable behaviors and limit their applicability. Authors: Zhiyi Mou, Wangze Ni, Tianfang Xiao.

Why it matters

Read this for the paper's specific claim in Research Papers: LLMs are increasingly deployed in real-world applications, making inference efficiency and service reliability critical concerns due to their substantial computational costs.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/28/2026
Recently

E-MagDiP: Electro-Magnetic based Differential Privacy for EEG based Community Sensing

EEG-based community sensing programs are emerging globally as a tool to leverage aggregated brain data to gain insights into attentiveness of students and employees. But these programs raise privacy concerns because EEG signals contain sensitive personal information. Differential Privacy (DP) can protect individuals while preserving aggregate statistics yet applying DP to EEG data is challenging as it requires user-level noise generation, which increases power and latency. Authors: Ayanga Imesha Kumari Kalupahana, Vishruti Ranjan, Li-Shiuan Peh.

Why it matters

Read this for the paper's specific claim in Research Papers: EEG-based community sensing programs are emerging globally as a tool to leverage aggregated brain data to gain insights into attentiveness of students and employees.

Primary paperarxivcs.CR
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/28/2026
Recently

SAM3D-Guided Object-Centric Representation Alignment for Vision-Language-Action Models

Vision-Language-Action (VLA) models have shown strong potential for general robot manipulation, but most existing models rely on 2D visual-language backbones and lack fine-grained 3D understanding of target objects, especially under occlusion, pose variation, scale changes, and precise spatial interaction. We propose an object-centric 3D representation alignment framework built upon π_0, using SAM3D as a frozen 3D teacher to provide target-object 3D priors during training. Specifically, we localize task-relevant objects with object recognition models, generate corresponding object masks, and use SAM3D to extract dense object-level 3D representations, which are aligned with intermediate visual features of π_0. Authors: Zonghe Liu, Shanyuan Jie, Xiaoquan Sun.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Vision-Language-Action (VLA) models have shown strong potential for general robot manipulation, but most existing models rely on 2D visual-language backbones and lack fine-grained 3D understanding of target objects, especially under occlusion, pose variation, scale changes, and precise spatial interaction.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv7/28/2026
Recently

πR^2: Reactive Real-time Flow Policies

Generalist manipulation policies increasingly take the form of action-chunking flow policies built on large pretrained backbones. Such chunks run open-loop, so the policy cannot react to sensory input arriving mid-execution, sacrificing reactivity. Replanning more often would restore it, but the perception-to-action pipeline (a large backbone plus multiple denoising steps) is too slow: this latency forbids frequent replanning and leaves committed actions stale, making such policies ill-suited for dynamic, closed-loop control. Authors: Sungjae Park, Shubham Tulsiani.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Generalist manipulation policies increasingly take the form of action-chunking flow policies built on large pretrained backbones.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv7/28/2026
Recently

S2A2: Audio-Visual Imitation Learning for Manipulation Tasks Using Acoustic Spatial Information

Acoustic information provides rich cues about object location, material properties, and changes caused by contact or motion. This paper introduces a new set of acoustic-aware manipulation tasks for imitation learning, in which robots must use auditory cues to determine manipulation targets. These tasks require sound source localization and identification for active exploration in robotic manipulation. Authors: Kaneyoshi Hiratsuka, Benjamin Yen, Ryosuke Kojima.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Acoustic information provides rich cues about object location, material properties, and changes caused by contact or motion.

Primary paperarxivcs.RO
Original
Embedded Systems
NVIDIA Technical Blog7/26/2026
Recently

NVIDIA Nemotron 3 Ultra Leads Open Models on Accuracy and Efficiency in Agentic RTL Coding

Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware... Modern chip design is increasingly limited by engineering time.

Why it matters

Read this for the official technical update in Embedded Systems: Modern chip design is increasingly limited by engineering time.

Official source
Original
Embedded Systems
NVIDIA Technical Blog7/28/2026
Recently

Developing Healthcare Robotics with GPU-Native Medical Physics Simulation

Unlike autonomous driving or industrial robotics, healthcare robotics can't rely on internet-scale data collection or unlimited real-world experimentation... Unlike autonomous driving or industrial robotics, healthcare robotics can't rely on internet-scale data collection or unlimited real-world experimentation. Every demonstration requires specialized equipment, clinical expertise, and access to patients or laboratory environments.

Why it matters

Read this for the official technical update in Embedded Systems: Unlike autonomous driving or industrial robotics, healthcare robotics can't rely on internet-scale data collection or unlimited real-world experimentation...

Official source
Original

Archived section

Computer Systems · 5

Computer Systems
arXiv7/27/2026
Recently

A Heterogeneous Neural Network Accelerator for End-to-End Multitask RF Signal Recognition

This paper presents a heterogeneous neural network accelerator for multi-task RF signal recognition, supporting automatic modulation recognition (AMR), hardware-Trojan covert channel (HT-CC) detection, and GNSS jamming classification. We introduce a compact attention-enhanced convolutional neural network (CNN) combined with LSDec, a learnable streaming decimator that enables adaptive temporal downsampling and flexible input lengths. The hardware architecture integrates a novel dual-pipeline, fused convolution-pooling engine with DMA-based streaming to minimize memory traffic and latency. Authors: Zhifan Song, Haralampos-G. Stratigopoulos, Hassan Aboushady.

Why it matters

Read this for the paper's specific claim in Computer Systems: presents a heterogeneous neural network accelerator for multi-task RF signal recognition, supporting automatic modulation recognition (AMR), hardware-Trojan covert channel (HT-CC) detection, and GNSS jamming classification.

Primary paperarxivcs.AR
Original
Computer Systems
arXiv7/27/2026
Recently

Denial of Deadline: Network-Driven Accuracy Collapse in Distributed Inference Pipelines

Inference systems increasingly combine a fast path that returns predictions within the application's latency deadline together with a higher-accuracy slow path that runs higher-compute methods on stronger, remote hardware, so its results can be returned on time and combined with the fast path predictions. Across several application domains, we abstract this inference architecture as a fast path, a slow path, and a coordination layer with two functions: a router that invokes the slow path and a merger that decides whether to incorporate its returned predictions., Yo-Yo bursts, can exploit contention at shared resources along the slow path to push benign users' slow-path predictions past their latency deadlines. Authors: Jhonatan Tavori, Gur-Eyal Sela, Ion Stoica.

Why it matters

Read this for the paper's specific claim in Computer Systems: Inference systems increasingly combine a fast path that returns predictions within the application's latency deadline together with a higher-accuracy slow path that runs higher-compute methods on stronger, remote hardware, so its results can be returned on time and combined with the fast path predictions.

Primary paperarxivcs.NI
Original
Computer Systems
arXiv7/28/2026
Recently

Hermes: Low Tail-Latency Via Prefix Consensus

Leader-based BFT protocols finalize through their leaders: a view whose leader is crashed or slow finalizes nothing, and the timeout that ends it admits no good setting. A conservative timeout turns every crashed leader into a long stall; an aggressive one voids the views of leaders that are merely slow. Either way the expired view is wasted, and this trade-off, not the good case, governs tail latency. Authors: Alejandro Ranchal-Pedrosa, Dakai Kang, Neil Giridharan.

Why it matters

Read this for the paper's specific claim in Computer Systems: Leader-based BFT protocols finalize through their leaders: a view whose leader is crashed or slow finalizes nothing, and the timeout that ends it admits no good setting.

Primary paperarxivcs.DC
Original
Computer Systems
arXiv7/28/2026
Recently

MDTransformer: A Hardware-Software Co-Design of Mode-Division Photonic Transformer Accelerator with Inverse-Designed Coherent Crossbar

Recently, photonic transformer accelerators (PTAs) have successfully achieved significant speedup and energy efficiency improvements over electronic accelerators for expediting Transformer inference. However, state-of-the-art rely on expensive multi-wavelength light generation and large dot-product units due to active phase-shifter components, thus making their approach inefficient and impractical. To address this, we propose MDTransformer, a novel hardware-software co-design of PTA based on mode-division optical dataflow and operations. Authors: Solomon Micheal Serunjogi, Rachmad Vidya Wicaksana Putra, Ayat Taha.

Why it matters

Read this for the paper's specific claim in Computer Systems: Recently, photonic transformer accelerators (PTAs) have successfully achieved significant speedup and energy efficiency improvements over electronic accelerators for expediting Transformer inference.

Primary paperarxivcs.AR
Original
Computer Systems
arXiv7/28/2026
Recently

Massively parallel numerical simulations with Julia

The Julia programming language aims to provide a modern approach to develop high-performance computing (HPC) applications. It tries to achieve this by combining a high-level, dynamic interface with just-in-time compilation to native machine code, thereby facilitating high developer productivity and native code performance at the same time. While this approach has already been shown to work well for serial applications, it is not clear if it readily translates to traditional, massively parallel HPC work loads. Authors: Simon Candelaresi, Benedict Geihe, Marco Artiano.

Why it matters

Read this for the paper's specific claim in Computer Systems: The Julia programming language aims to provide a modern approach to develop high-performance computing (HPC) applications.

Primary paperarxivmath.NA
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv7/28/2026
Recently

RepoReasoner: Evaluating Repository-Level Code Reasoning Ability of Long-Context Language Models

Recent large language models (LLMs) have shown strong performance on software engineering tasks, yet most existing benchmarks evaluate code reasoning at the function level, where all relevant information is localized. This setting fails to reflect real-world development, which requires reasoning across multiple files and complex dependency structures. We introduce RepoReasoner, a benchmark for evaluating repository-level code reasoning. Authors: Yanlin Wang, Suiquan Wang, Yanli Wang.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Recent large language models (LLMs) have shown strong performance on software engineering tasks, yet most existing benchmarks evaluate code reasoning at the function level, where all relevant information is localized.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
Vercel Blog7/27/2026
Recently

DeepsecBench: evaluating model performance in finding cybersecurity vulnerabilities

Last week, OpenAI evaluated two models on an exploit benchmark within an isolated sandbox. Guardrails were reduced for testing, and the models found a vulnerability in their environment, accessed the internet, and reached Hugging Face's production database. No human directed the action, but the breach is a clear example of how much more capable malicious attackers are when equipped with powerful AI models.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Last week, OpenAI evaluated two models on an exploit benchmark within an isolated sandbox.

Official source
Original
Developer Tools / Open Source
Vercel Blog7/26/2026
Recently

Run Claude Managed Agents with Chat SDK

Claude Managed AgentsChat SDK Claude Managed Agents handles the agent loop server-side, including the model, tools, session state, and sandboxed web research. Chat SDK gives that agent a chat interface through a single type-safe handler, with adapters that carry it to Slack, WhatsApp, and more. To see it work, a new builds a working research analyst you chat with in the browser.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Claude Managed AgentsChat SDK Claude Managed Agents handles the agent loop server-side, including the model, tools, session state, and sandboxed web research.

Official source
Original
Developer Tools / Open Source
Hackaday7/28/2026
Recently

Samsung's SmartThings API Terminates Free Access

If there's one constant in the world of commercial home automation solutions, it is that of decreasing availability and higher costs as time goes on.

Why it matters

Read this for the engineering context in Developer Tools / Open Source: If there's one constant in the world of commercial home automation solutions, it is that of decreasing availability and higher costs as time goes on.

Trusted sourcehome hacksNews
Original
Developer Tools / Open Source
CNCF Blog7/28/2026
Recently

CNCF and SlashData Report Finds Japan's Cloud Native Community Reaches Nearly 1 Million Developers

New research finds 100,000 of Japan's AI developers now leverage cloud native technologies Key Highlights: YOKOHAMA – KubeCon + CloudNativeCon Japan —July 29, 2026— The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud...

Why it matters

Read this for the official technical update in Developer Tools / Open Source: New research finds 100,000 of Japan's AI developers now leverage cloud native technologies Key Highlights: YOKOHAMA – KubeCon + CloudNativeCon Japan —July 29, 2026— The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud...

Official sourceAnnouncements
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Archived section

Cloud / Infrastructure · 5

Cloud / Infrastructure
CNCF Blog7/28/2026
Recently

Subaru Wins CNCF End User Case Study Contest for Accelerating AI Development with Cloud Native Infrastructure

New architecture reduced AI container image pull times by 60x while automating workflows for next-generation driver assistance systems Key Highlights YOKOHAMA – KUBECON + CLOUDNATIVECON JAPAN — July 29, 2026 — The Cloud Native Computing Foundation®...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: New architecture reduced AI container image pull times by 60x while automating workflows for next-generation driver assistance systems Key Highlights YOKOHAMA – KUBECON + CLOUDNATIVECON JAPAN — July 29, 2026 — The Cloud Native Computing Foundation®...

Official sourceAnnouncements
Original
Cloud / Infrastructure
arXiv7/28/2026
Recently

Does Runtime Topology Context Improve LLM-Generated Kubernetes Security Patches?

Kubernetes is central to the cloud-native ecosystem, orchestrating containerised workloads. Recent work suggests that large language models (LLMs) can automate cluster security remediation, generating configuration patches from Kubernetes Security Posture Management (KSPM) findings without human authoring. Such systems, however, prompt the model with each finding in isolation from the live service call graph, assuming general hardening knowledge suffices. Authors: Farooq Shaikh.

Why it matters

Read this for the paper's specific claim in Cloud / Infrastructure: Kubernetes is central to the cloud-native ecosystem, orchestrating containerised workloads.

Primary paperarxivcs.CR
Original
Cloud / Infrastructure
CNCF Blog7/29/2026
Recently

Your Kubernetes health checks are accidentally waking your services. Here's the fix.

Scale-to-zero breaks when health checks scale you back up. Learn how KubeElasti's ProbeResponse lets Kubernetes services stay genuinely idle — while keeping load balancers and uptime monitors happy. Scale-to-zero sounds perfect on paper.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Scale-to-zero breaks when health checks scale you back up.

Official sourceBlog
Original
Cloud / Infrastructure
Cloudflare Blog7/28/2026
Recently

Natural disasters and government interference: examining Q2 2026's major Internet disruption events

Cloudflare Radar tracked Internet disruptions driven by natural disasters, government-mandated shutdowns, and DNSSEC key rollovers over the last quarter. This post analyzes traffic telemetry to explain how these events impacted global connectivity.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Cloudflare Radar tracked Internet disruptions driven by natural disasters, government-mandated shutdowns, and DNSSEC key rollovers over the last quarter.

Official sourceAWSInternet Shutdown
Original
Cloud / Infrastructure
AWS Blog7/27/2026
Recently

AWS Weekly Roundup: Local Zone in Athens, Claude Opus 5 on AWS, Lambda durable execution for.NET, and more (July 27, 2026)

Last week I had the privilege of spending three days in São Paulo with technical builders from across Latin America, brought together for a regional tech event full of deep-dive sessions, hands-on workshops, and conversations with customers and partners.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Last week I had the privilege of spending three days in São Paulo with technical builders from across Latin America, brought together for a regional tech event full of deep-dive sessions, hands-on workshops, and conversations with customers and partners.

Official sourceAmazon BedrockAmazon Bedrock AgentCore
Original