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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
arXiv8/12/2026
Recently

Constructing Dynamic Master Logic Models as Knowledge Graphs for Complex System Diagnostics Using Retrieval-Augmented Large Language Models

Dynamic Master Logic (DML) provides a hierarchical framework for representing system behavior by linking functional objectives to underlying structural elements. However, DML construction typically relies on expert interpretation of technical documentation, limiting scalability for complex systems. This study presents a framework for automated construction of DML models from system descriptions and their representation as Knowledge Graphs (KG-DML), using Retrieval-Augmented Generation and Large Language Models as enabling tools. Authors: Saman Marandi, Yu-Shu Hu, Mohammad Modarres.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Dynamic Master Logic (DML) provides a hierarchical framework for representing system behavior by linking functional objectives to underlying structural elements.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv8/12/2026
Recently

Class Activation Mapping in Explainable Computer Vision: A Method-Centered Review of CNN, Transformer, and Foundation-Model-Era Visual Explanations

Class activation mapping (CAM) is one of the most widely used visual explanation families in explainable artificial intelligence. Its purpose is intuitive: it converts internal model evidence into a heatmap that highlights the image regions, convolutional channels, tokens, or patches that support a target class or concept. Since the first CAM formulation in 2016, the field has moved far beyond global-average-pooled CNN classifiers. Authors: AmirHossein Eshghi, Hamid Saadatfar, Seyyed Ali Hoseini.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Class activation mapping (CAM) is one of the most widely used visual explanation families in explainable artificial intelligence.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
arXiv8/10/2026
Recently

From Values to Benchmarks: Evaluating Large Language Models for Governmental Use in Dutch

Large language models are increasingly being deployed in governmental settings, yet few existing evaluation frameworks jointly reflect the values of public administration and the linguistic requirements of non-English contexts. We present the "Grip on LLMs" framework, a systematic evaluation suite for Dutch governmental use developed in collaboration with domain experts from a major Dutch municipal organisation. Through an advisory board process, user research, and a survey of the users of a civil-servant chatbot, we identify six evaluation dimensions (factuality, honesty, social bias, energy consumption, cost, and training data transparency) and operationalise them into a benchmark suite covering more than 30 multilingual and Dutch-specific models. Authors: Laurens Samson, Iva Gornishka, Gossa Lô.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Large language models are increasingly being deployed in governmental settings, yet few existing evaluation frameworks jointly reflect the values of public administration and the linguistic requirements of non-English contexts.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv8/10/2026
Recently

GENCO - A Unified Neural Solver Embedded in a Development Framework for Steady-State Grid Analysis

Foundation models are transforming business workflows and boosting productivity, yet they remain largely absent from engineering domains such as power system analysis, where strict physical consistency must be enforced. We present GENCO (GEometric Neural Corrective Optimizer), a unified neural solver for steady-state transmission grid analysis that handles power flow (PF), optimal power flow (OPF), and state estimation (SE) within a single architecture and shared network representation. To support advances in neural power system solvers, we introduce the open-source GridFM Development Framework, which standardizes synthetic data generation and training in a low-code environment. Authors: Alban Puech, Matteo Mazzonelli, Tamara R. Govindasamy.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Foundation models are transforming business workflows and boosting productivity, yet they remain largely absent from engineering domains such as power system analysis, where strict physical consistency must be enforced.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv8/11/2026
Recently

Capturing Uncertainty in Human Motion for Representation Learning in Soccer

This paper presents a self-supervised representation learning framework for understanding 3D skeleton-based human motion in soccer, using future motion prediction as the learning objective. Since human motion is inherently uncertain, accounting for multiple plausible futures is essential for capturing the underlying motion dynamics and learning effective representations. To this end, we introduce a conditioning module for motion prediction that models a probabilistic distribution over discretized future motions in 3D Euclidean space, learning multimodality with explicit supervision from future trajectories. Authors: Yizhou Xu, Lars Bretzner, Tiesheng Wang.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: presents a self-supervised representation learning framework for understanding 3D skeleton-based human motion in soccer, using future motion prediction as the learning objective.

Primary paperarxivcs.CV
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv8/12/2026
Recently

The Role Specialization Model (RSM): Coordinating LLM-Based Tools in Agentic Software Development - An Exploratory Case Study

0), in which autonomous agents manage full development life cycles under human supervision. 5 backend), Gemini CLI, and Qwen Code (local execution via Ollama), are coordinated according to a role-distribution framework proposed in this work as the Role Specialization Model (RSM). Three research questions guide the study: (RQ1) how can LLM-based tools with distinct capabilities be coordinated through the RSM in a real development workflow; (RQ2) what deviations from the planned role distribution emerge during RSM execution and what factors explain them; and (RQ3) how does the resulting product compare against the ISO/IEC 25010 quality model. Authors: Carlos Alberto Fernández-y-Fernández, Jorge R. Aguilar-Cisneros.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: 0), in which autonomous agents manage full development life cycles under human supervision.

Primary paperarxivcs.SE
Original
Automation / Agentic Systems
arXiv8/12/2026
Recently

VAKRA: Evaluating Multi-Hop Reasoning Across APIs and Retrieval Under Tool-Use Policies

Agents deployed in enterprise settings must reason across structured APIs and document collections, yet existing benchmarks evaluate these capabilities in isolation. We introduce VAKRA (eValuating API and Knowledge Retrieval Agents), a benchmark of over 8,000 executable APIs across 62 domains with tasks spanning three settings of increasing difficulty: diverse API interaction styles, multi-hop reasoning over structured APIs, and multi-source reasoning with natural-language tool-use policy constraints. Correctness is verified by re-executing predicted tool calls against live APIs, accommodating multiple valid paths. Authors: Ankita Rajaram Naik, Anupama Murthi, Benjamin Elder.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Agents deployed in enterprise settings must reason across structured APIs and document collections, yet existing benchmarks evaluate these capabilities in isolation.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv8/12/2026
Recently

An Agentic Workflow for Legacy HPC Modernization: Converting the Two-Electron-Integral Core of GAMESS

Modernizing legacy Fortran is a problem of volume: the transformations are individually routine, but the codebases can be enormous, and across much of computational science the work simply goes undone. We propose an agentic workflow that takes this work on at production scale, and we set out to measure how far such delegation can reach. In this work, three prompt-specialized agent roles operate under a version-controlled specification that the agents themselves authored and revised, while humans hold a small number of gates. Authors: Yuzhong Shen, Masha Sosonkina, Peng Xu.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Modernizing legacy Fortran is a problem of volume: the transformations are individually routine, but the codebases can be enormous, and across much of computational science the work simply goes undone.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv8/12/2026
Recently

DreamFly: Causal Memory and Receding-Horizon Diffusion Planning for Aerial Vision-Language Navigation

Aerial vision-language navigation (VLN) requires an embodied agent to integrate visual evidence over time, plan future actions, and determine when it has reached a navigation goal under partial observability. Although recent VLA models offer a promising perception-to-action paradigm, adapting them to aerial navigation remains challenging due to limited historical context, short planning horizons, and unreliable implicit termination. To address these challenges, we propose DreamFly, a diffusion-based aerial VLN framework built on Dream-VLA. Authors: Yan Deng, Fei Xu.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Aerial vision-language navigation (VLN) requires an embodied agent to integrate visual evidence over time, plan future actions, and determine when it has reached a navigation goal under partial observability.

Primary paperarxivcs.CV
Original
Automation / Agentic Systems
OpenAI Blog8/12/2026
Recently

From assistance to execution: How enterprises put AI to work

OpenAI research reveals how enterprises are adopting agentic AI, using ChatGPT and Codex, and how frontier firms are pulling ahead in AI adoption.

Why it matters

Read this for the official technical update in Automation / Agentic Systems: OpenAI research reveals how enterprises are adopting agentic AI, using ChatGPT and Codex, and how frontier firms are pulling ahead in AI adoption.

Official sourceCompany
Original

Archived section

Research Papers · 5

Research Papers
arXiv8/10/2026
Recently

Generative AI for Encrypted Traffic Analysis: Synthetic Dataset Generation and Classifier Evaluation

Network traffic analysis faces significant challenges with encrypted communications, primarily due to limited visibility into packet contents and the inherent imbalance in available datasets, particularly for anomalous traffic patterns. This paper addresses these challenges by exploring Generative AI (GAI) techniques to create realistic and balanced synthetic encrypted traffic datasets. Our approach incorporates feature analysis, clustering-based data generation, and comprehensive classifier evaluation to ensure synthetic data quality. Authors: Harshil Patel, Himanshu Garg, Aswani Kumar Cherukuri.

Why it matters

Read this for the paper's specific claim in Research Papers: Network traffic analysis faces significant challenges with encrypted communications, primarily due to limited visibility into packet contents and the inherent imbalance in available datasets, particularly for anomalous traffic patterns.

Primary paperarxivcs.CR
Original
Research Papers
Microsoft Research Blog8/12/2026
Recently

MindTopo reveals VLMs' spatial reasoning abilities

A path, a fence, a knot. MindTopo sets a new benchmark for testing how AI understands topological relationships and highlights new opportunities to strengthen spatial reasoning and planning. The post MindTopo reveals VLMs' spatial reasoning abilities appeared first on Microsoft Research.

Why it matters

Read this for the official technical update in Research Papers: MindTopo sets a new benchmark for testing how AI understands topological relationships and highlights new opportunities to strengthen spatial reasoning and planning.

Official sourceResearch Blog
Original
Research Papers
arXiv8/10/2026
Recently

A Bird's-Eye View on Security Considerations in RFCs

Request for comments (RFCs) are Internet standards, memorandums, and related technical documents about core Internet protocols made via and released by the Internet Engineering Task Force (IETF). In the early 1990s each RFC was required to have a section for security considerations. The present work examines these sections. Authors: Jukka Ruohonen, Qusai Ramadan.

Why it matters

Read this for the paper's specific claim in Research Papers: Request for comments (RFCs) are Internet standards, memorandums, and related technical documents about core Internet protocols made via and released by the Internet Engineering Task Force (IETF).

Primary paperarxivcs.CR
Original
Research Papers
arXiv8/11/2026
Recently

Statistically-Secure Bit Commitment and Coin Flipping Protocols Based on Quantum Hardware Assumptions

Bit commitment is impossible to achieve with unconditional security, even in quantum cryptogra- phy. We show that statistically secure bit commitment, satisfying both hiding and binding, can be constructed from hybrid locked physical unclonable functions (HLPUFs), a hardware primitive that combines classical hardware tokens and quantum communication. Our protocol uses these hardware assumptions in a novel and non-trivial way to achieve the first mistrustful two-party cryptographic protocol based on hybrid hardware modules. Authors: Roo Dunnill, Mina Doosti.

Why it matters

Read this for the paper's specific claim in Research Papers: Bit commitment is impossible to achieve with unconditional security, even in quantum cryptogra- phy.

Primary paperarxivquant-ph
Original
Research Papers
arXiv8/10/2026
Recently

WhichTok? Comparing Three TikTok Data Acquisition Tools

TikTok's global growth has made it a prime platform for both entertainment and political discourse, prompting increased social science research. However, this rapidly evolving research field faces a fundamental reproducibility crisis. TikTok's opaque algorithmic systems hinder researchers from drawing meaningful empirical inferences, while the lack of standardized data collection methods compounds these challenges. Authors: Gayoung Jeon, Cameron Moy, Silvia Teliz.

Why it matters

Read this for the paper's specific claim in Research Papers: TikTok's global growth has made it a prime platform for both entertainment and political discourse, prompting increased social science research.

Primary paperarxivcs.SI
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv8/12/2026
Recently

Digital Twin Networks for 6G Wireless Systems: Architecture, Enabling Technologies, Intelligent Control, and Open Challenges

The transition to the Sixth Generation (6G) of mobile networks requires proactive and deterministic orchestration to satisfy the stringent key performance indicators of future services, including ultra-reliable low-latency communications, enhanced mobile broadband, and massive machine-type communications. Digital Twin Networks (DTN) have recently emerged as a foundational technology to meet these demands, offering real-time and high-fidelity virtual replicas of the physical network. Although the current literature explores DTNs conceptually, a gap exists in the coverage of technical classification and computational feasibility evaluations. Authors: Charalampos Oikonomidis, Emmanouel T. Michailidis, Nikolaos I. Miridakis.

Why it matters

Read this for the paper's specific claim in Embedded Systems: The transition to the Sixth Generation (6G) of mobile networks requires proactive and deterministic orchestration to satisfy the stringent key performance indicators of future services, including ultra-reliable low-latency communications, enhanced mobile broadband, and massive machine-type communications.

Primary paperarxiveess.SY
Original
Embedded Systems
Hackster.io8/13/2026
Recently

WCH Electronics' CH32V407 Packs Vector Extensions for a Speed Boost — Plus Optional PSRAM

WCH Electronics has launched a new entry in its popular CH32 family of 32-bit RISC-V architecture microcontrollers, the CH32V407 — expandable to include additional RAM as the CH32V467. "CH32V407 is an industrial-grade interconnected microcontroller based on the QingKe RISC-V core," WCH Electronics says of the device. " WCH's CH32 range has become popular among makers for offering high performance at a low cost, and uses the free and open source RISC-V instruction set architecture — though the particular implementation, QingKe, is proprietary.

Why it matters

Read this for the engineering context in Embedded Systems: WCH Electronics has launched a new entry in its popular CH32 family of 32-bit RISC-V architecture microcontrollers, the CH32V407 — expandable to include additional RAM as the CH32V467.

Trusted source
Original
Embedded Systems
arXiv8/12/2026
Recently

NetlistBench: Evaluating LLM Reliability in SPICE Netlist Recognition and Manipulation

Large Language Models (LLMs) are increasingly used in circuit design workflows, yet their reliability on simulator-facing SPICE netlist recognition and manipulation remains poorly understood and is rarely separated from high-level design reasoning. Although netlists are textual, they encode structured circuit objects through topology and parameters. We present NetlistBench, a structure-verified benchmark for SPICE netlist recognition and manipulation. Authors: Jiarui Ma, Jianghan Wang, Yuheng Ma.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Large Language Models (LLMs) are increasingly used in circuit design workflows, yet their reliability on simulator-facing SPICE netlist recognition and manipulation remains poorly understood and is rarely separated from high-level design reasoning.

Primary paperarxiveess.SY
Original
Embedded Systems
arXiv8/12/2026
Recently

Co-constructing sociotechnical AI governance: participatory system mapping using algorithm registers

Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services. Yet potential publics differ in their expectations of what should be made transparent and how, as well as in their interest in and ability to parse the information currently published in the registers. Moreover, it remains unclear how these instruments can represent the sociotechnical systems in which these algorithms are embedded, and how system-level transparency can facilitate accountability. Authors: Íñigo de Troya, Maurus Enbergs, Neelke Doorn.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services.

Primary paperarxivcs.CY
Original
Embedded Systems
Hackster.io8/12/2026
Recently

Sweet Freedom!

On the outside, vending machines may be covered with bright colors, cute graphics, and flashing lights, but on the inside, you'll find industrial computers, robotics, sensors, databases, and network-connected software. This makes them fun reverse engineering targets for hardware hackers, especially when manufacturers tightly control how owners are allowed to use the hardware. That's exactly the situation the creator behind Block's Retro Repairs found himself in after purchasing a commercial automated cotton candy vending machine.

Why it matters

Read this for the engineering context in Embedded Systems: On the outside, vending machines may be covered with bright colors, cute graphics, and flashing lights, but on the inside, you'll find industrial computers, robotics, sensors, databases, and network-connected software.

Trusted source
Original

Archived section

Computer Systems · 5

Computer Systems
arXiv8/12/2026
Recently

The Ingestion Tax: Adopting File-Backed Weights in Tensor Frameworks

Open-weight models can occupy a middle capacity regime: active weights fit in DRAM as cached file pages, but a second framework-owned representation does not fit or must be refilled as layers run, so low-batch decode rereads the weights every token. On integrated and coherent-memory systems the checkpoint's file pages already occupy a GPU-readable domain, yet accelerator-loading paths still copy them into framework-owned allocations. We call this the ingestion tax: the OS holds the bytes as clean, evictable file pages, the architecture makes them GPU-readable, and only the framework's ownership model stands between the two. Authors: Yuan Si, Yufeng Lin, Daming Li.

Why it matters

Read this for the paper's specific claim in Computer Systems: Open-weight models can occupy a middle capacity regime: active weights fit in DRAM as cached file pages, but a second framework-owned representation does not fit or must be refilled as layers run, so low-batch decode rereads the weights every token.

Primary paperarxivcs.OS
Original
Computer Systems
AWS Architecture Blog8/11/2026
Recently

Scaling patterns for self-organizing multi-agent clusters with Kiro

Learn how to coordinate AI agents through shared state in Amazon S3 instead of a central orchestrator. Deploy and observe self-organizing agent clusters on Amazon EC2 with the open-source kiro-flock reference implementation.

Why it matters

Read this for the official technical update in Computer Systems: Learn how to coordinate AI agents through shared state in Amazon S3 instead of a central orchestrator.

Official sourceAmazon EC2Expert (400)
Original
Computer Systems
AWS Architecture Blog8/12/2026
Recently

Reducing Text2SQL latency with parameterized query templates

Learn how parameterized query templates reduced Text2SQL latency by 80% and cut token consumption by over 50%. This post covers the architecture behind an intelligent caching layer that uses semantic similarity to match user questions to SQL templates, bypassing expensive LLM calls.

Why it matters

Read this for the official technical update in Computer Systems: Learn how parameterized query templates reduced Text2SQL latency by 80% and cut token consumption by over 50%.

Official sourceAmazon BedrockAWS Lambda
Original
Computer Systems
arXiv8/11/2026
Recently

You Only Charge Once 2.0: A End-to-End Analog Computing-in-Memory Architecture with Reconfigurable Switched Capacitors

Analog Computing-in-Memory (ACiM) accelerates deep neural networks by keeping weights inside memory arrays and executing dot products in the analog domain. However, modern ACiM accelerators are often limited by the "ADC wall": analog-to-digital converters consume a large fraction of energy and area, while bit-sliced execution repeatedly invokes these converters. Existing designs reduce this cost with low-resolution readout or time multiplexing, but they either lose output fidelity or introduce serialization overhead. Authors: Zihao Xuan, Yewen Li, Jia Chen.

Why it matters

Read this for the paper's specific claim in Computer Systems: Analog Computing-in-Memory (ACiM) accelerates deep neural networks by keeping weights inside memory arrays and executing dot products in the analog domain.

Primary paperarxivcs.AR
Original
Computer Systems
arXiv8/11/2026
Recently

SCOUT: Symmetric Consensus Outlier Detection for Failure Localization in LLM Pre-Training

In LLM pre-training, synchronization propagates rank-local stalls, slowdowns, and numerical errors into job-wide symptoms, obscuring their origin. Existing diagnosis often relies on in-process monitors that cannot report after the trainer blocks or terminates, or on post-mortem logs that preserve only synchronized symptoms; offline health tests lose the workload and operating conditions that triggered the failure. We present SCOUT, a unified runtime failure-localization framework built on one design principle: identify outliers through strict-majority consensus among equivalent replicas. Authors: Zhuang Wang.

Why it matters

Read this for the paper's specific claim in Computer Systems: In LLM pre-training, synchronization propagates rank-local stalls, slowdowns, and numerical errors into job-wide symptoms, obscuring their origin.

Primary paperarxivcs.DC
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv8/12/2026
Recently

VICBench: A Multi-Language Benchmark for Code Vulnerability Detection

Evaluating security vulnerability detection tools requires benchmark datasets with vulnerability-inducing commits (VICs) - the commits that first introduce vulnerabilities into codebases. VICs are essential for determining the full range of vulnerable software versions. Existing vulnerability datasets suffer from limited programming language coverage, restricted patch complexity, and narrow project scope. Authors: Jin Lu, Xuening Han, Yang Zhong.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Evaluating security vulnerability detection tools requires benchmark datasets with vulnerability-inducing commits (VICs) - the commits that first introduce vulnerabilities into codebases.

Primary paperarxivcs.CR
Original
Developer Tools / Open Source
Raspberry Pi News8/13/2026
Recently

Get started with LiteRT on Raspberry Pi

Install and run high-performance on-device AI using the LiteRT CLI tool on Raspberry Pi. The post Get started with LiteRT on Raspberry Pi appeared first on Raspberry Pi.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Install and run high-performance on-device AI using the LiteRT CLI tool on Raspberry Pi.

Official sourceRaspberry Pi 5Raspberry Pi AI
Original
Developer Tools / Open Source
GitHub Blog8/12/2026
Recently

Write your first prompt with the GitHub Copilot app

Learn how to write your first prompt in the GitHub Copilot app, choose the right context and model, and start your first task with confidence. The post Write your first prompt with the GitHub Copilot app appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Learn how to write your first prompt in the GitHub Copilot app, choose the right context and model, and start your first task with confidence.

Official sourceAI & MLGitHub Copilot
Original
Developer Tools / Open Source
Vercel Blog8/12/2026
Recently

DeepSeek V4 Pro now runs updated weights on AI Gateway

DeepSeek V4 Pro now runs on updated weights on AI Gateway. deepseek/deepseek-v4-pro To use the updated DeepSeek V4 Pro, set model to in the. AI Gateway will route to providers with the new weights:deepseek/deepseek-v4-pro-0813AI SDK To run V4 Pro in a coding agent, use to connect your agents to AI Gateway, then select in the agent's model configuration.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: DeepSeek V4 Pro now runs on updated weights on AI Gateway.

Official source
Original
Developer Tools / Open Source
Vercel Blog8/10/2026
Recently

Vercel Sandbox now runs on Vercel Managed Images

Today we are introducing Vercel Managed Images (VMI), a set of versioned, open-source base images you can use as-is or extend. vercel/sandbox Managed images replace Sandbox runtimes, which are now deprecated. Starting with version 3 of the Sandbox SDK, new sandboxes default to.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Today we are introducing Vercel Managed Images (VMI), a set of versioned, open-source base images you can use as-is or extend.

Official source
Original

Archived section

Cloud / Infrastructure · 5

Cloud / Infrastructure
arXiv8/12/2026
Recently

Machine Learning-Based Cyber Defense for Cloud Infrastructure: An Adaptive Deep Q-Network Architecture for Intelligent Intrusion Detection and Automated Threat Mitigation

With the increasing complexity of cyber assaults in cloud environments, adaptable security solutions are needed that can support real-time detection and autonomous response. In this paper, we propose a reinforcement learning-based dynamic cyber defense framework. We deploy a Deep Q-Network (DQN) to train effective defensive strategies to counteract the evolving cyberattacks. Authors: Md Yassir Mottalib, Md Yousuf, Eklachur Rahman Bhuiyan.

Why it matters

Read this for the paper's specific claim in Cloud / Infrastructure: With the increasing complexity of cyber assaults in cloud environments, adaptable security solutions are needed that can support real-time detection and autonomous response.

Primary paperarxivcs.CR
Original
Cloud / Infrastructure
CNCF Blog8/13/2026
Recently

LLMOps and platform engineering: Who should own the AI pipeline?

A few years ago, getting a model into production meant a data scientist, a DevOps engineer, and a narrow set of tools: train it, test it, ship it, watch the dashboards. Large language models broke that...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: A few years ago, getting a model into production meant a data scientist, a DevOps engineer, and a narrow set of tools: train it, test it, ship it, watch the dashboards.

Official sourceBlog
Original
Cloud / Infrastructure
Kubernetes Blog8/11/2026
Recently

How to Pretty-Print Your Kubernetes YAML as KYAML and Why You'd Want To

YAML has been the standard way to write Kubernetes manifests for years. Every example, tutorial, and configuration file you come across is written in it. The problem isn't that YAML is a bad format.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: YAML has been the standard way to write Kubernetes manifests for years.

Official source
Original
Cloud / Infrastructure
AWS Compute Blog8/12/2026
Recently

Burst to Region: Overflow AWS Outposts workloads to Amazon EC2

AWS Outposts brings AWS infrastructure into your data center with low latency and data locality. But an Outposts rack has fixed compute. Learn how to build a Burst to Region pattern that overflows workloads to Amazon EC2 in the parent Region when local capacity is exhausted.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: AWS Outposts brings AWS infrastructure into your data center with low latency and data locality.

Official sourceAdvanced (300)Amazon EC2
Original
Cloud / Infrastructure
NVIDIA Technical Blog8/12/2026
Recently

How to Choose Full-Stack Observability for NVIDIA AI Factories

AI infrastructure spans multiple layers, from compute and networking to storage, orchestration, and applications. When performance degrades, identifying the... AI infrastructure spans multiple layers, from compute and networking to storage, orchestration, and applications.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: AI infrastructure spans multiple layers, from compute and networking to storage, orchestration, and applications.

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Original