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Artificial Intelligence / Machine Learning · 5

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Computer Systems · 5

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Cloud / Infrastructure · 5

Archived section

Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/22/2026
Recently

LKValues: Aligning Large Language Models with Sri Lankan Societal Values

Value alignment of Large Language Models (LLMs) has been shown to be culturally biased toward Western norms. This results in the mishandling of local values in multilingual societies such as Sri Lanka that have their unique cultural dynamics. Existing benchmarks overlook Sri Lankan-contextualized values in its official language Sinhala, hindering culturally sensitive evaluation and fine-tuning. Authors: Nethmi Muthugala, Supryadi, Surangika Ranathunga.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Value alignment of Large Language Models (LLMs) has been shown to be culturally biased toward Western norms.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv7/22/2026
Recently

FMRP-LEAN: A HIPAA-Compliant AI-Augmented LIMS Architecture for End-to-End Clinical Assay Workflow Optimization

Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual quality control (QC) reconciliation, and loosely integrated systems, resulting in limited state visibility, delayed reporting, and increased operational risk. These challenges are particularly pronounced in multi-day assays such as Luminex-based quantification of Fragile X Messenger Ribonucleoprotein (FMRP), where HIPAA-compliant data governance, deterministic workflow progression, and coordinated communication across laboratory and clinical teams are required. This paper presents FMRP-LEAN, a HIPAA-compliant, AI-augmented Laboratory Information Management System (LIMS) architecture that formalizes biospecimen lifecycle management through a finite-state workflow model with explicit transition guards and dwell-time observability. Authors: Eva McCord, Ernest Pedapati, Zag ElSayed.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual quality control (QC) reconciliation, and loosely integrated systems, resulting in limited state visibility, delayed reporting, and increased operational risk.

Primary paperarxivcs.HC
Original
Artificial Intelligence / Machine Learning
arXiv7/21/2026
Recently

InstructMixup: Instruction-Guided Salient Patch Editing for Robust Data Augmentation

In image and video technologies, data augmentation is widely used to improve the generalization of deep visual models, and mixup-based strategies that interpolate between samples have become the dominant approach. However, computing informative mixing regions adds substantial overhead, and blending content across different images frequently disrupts the semantic integrity of the resulting sample. We propose \our, a data augmentation method that constructs challenging yet label-consistent training samples entirely within a single visual sample. Authors: Khawar Islam, Arif Mahmood, Xin Jin.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: In image and video technologies, data augmentation is widely used to improve the generalization of deep visual models, and mixup-based strategies that interpolate between samples have become the dominant approach.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
arXiv7/20/2026
Recently

GigaPath-Flash and GigaTIME-Flash: Efficient Pathology Foundation Models for Whole-Slide and Tumor Microenvironment Analysis

Foundation models have emerged as a driving force in computational pathology, with the potential to transform cancer diagnosis, prognosis, and treatment selection by learning transferable representations from large-scale histopathology data. A growing landscape of pathology foundation models now spans diverse data sources, architectures, and downstream applications. However, most pretrained models operate only at the image-tile level, use restrictive licenses, and remain computationally expensive, limiting large-scale slide-level clinical and research use. Authors: Naoto Usuyama, Jeya Maria Jose Valanarasu, Sicong Yao.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Foundation models have emerged as a driving force in computational pathology, with the potential to transform cancer diagnosis, prognosis, and treatment selection by learning transferable representations from large-scale histopathology data.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
arXiv7/20/2026
Recently

EVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain Database

Large-scale scientific simulations generate volumetric data at rates that far outpace advances in storage and network bandwidth, making effective lossy compression increasingly critical. However, conventional compressors often struggle to preserve fine structural details at high compression ratios (CRs), and implicit neural representations (INRs) require costly per-volume optimization and produce models with fixed CRs. To respond, we present EVOLVE, an autoencoder (AE)-based volume-compression framework that targets high CRs for offline compression, with three key contributions. Authors: Kaiyuan Tang, Maizhe Yang, Chaoli Wang.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Large-scale scientific simulations generate volumetric data at rates that far outpace advances in storage and network bandwidth, making effective lossy compression increasingly critical.

Primary paperarxivcs.GR
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/22/2026
Recently

Distributed Motion Planning with Safety Guarantees for Self-Reconfiguring Robotic Boats

Aquatic self-reconfigurable robots must assemble into desired shapes while ensuring safe interactions among multiple agents. This paper proposes a hybrid framework that combines distributed Model Predictive Control (MPC) with Control Barrier Functions (CBFs) for multi-agent shape formation and reconfiguration. Given a desired shape and target assignment, a distributed MPC scheme, solved via the Alternating Direction Method of Multipliers (ADMM), computes coordinated trajectories through local optimization and information exchange. Authors: Alejandro Gonzalez-Garcia, Wei Wang, Wei Xiao.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Aquatic self-reconfigurable robots must assemble into desired shapes while ensuring safe interactions among multiple agents.

Primary paperarxivcs.RO
Original
Automation / Agentic Systems
arXiv7/22/2026
Recently

PoTRE: Test-Time Reasoning inspired by Cognitive Heterogeneity

While Large Language Models (LLMs) excel at many tasks, they frequently struggle with complex reasoning that requires long-horizon planning and iterative error correction. Furthermore, standard single-stream prompting proves brittle when models encounter novel abstractions or rigorous domain constraints. We introduce PoTRE (Poly-Topological Reasoning Ensembles), a heterogeneous framework that decouples inference into four agents: (1) Adversarial Refinement Agent, (2) Hierarchical strategic Planning Agent, (3) Spectrum Search Agent, and (4) Direct Chain Agent. Authors: Anmol Kankariya, Sercan Ö. Arık.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: While Large Language Models (LLMs) excel at many tasks, they frequently struggle with complex reasoning that requires long-horizon planning and iterative error correction.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/22/2026
Recently

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference

Recent work established that under active inference, linear-Gaussian state-space models lose their epistemic drive (any incentive to act so as to gain information) "under any circumstances". The epistemic term of the Expected Free Energy becomes constant: the agent flattens to a Kalman filter whose gain sequence is fixed in advance, regardless of action. The minimal departure that restores the drive is unknown; the only established route is control entering the dynamics multiplicatively; the observation side of this boundary is unexplored. Authors: Daniel Corva.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Recent work established that under active inference, linear-Gaussian state-space models lose their epistemic drive (any incentive to act so as to gain information) "under any circumstances".

Primary paperarxivq-bio.NC
Original
Automation / Agentic Systems
arXiv7/22/2026
Recently

The Ethics of Autonomous AI Agents for Offensive Security

LLM-driven autonomous agents are reshaping offensive security. Unlike traditional penetration-testing tooling -- deterministic, narrowly scoped, and operated by trained practitioners -- agentic security tools exhibit indeterminacy along three independent dimensions. First, their actions are drawn from a non-deterministic policy whose outputs resist both ex-ante and ex-post explanation, frustrating incident attribution and pre-deployment safety review. Authors: Andreas Happe, Jürgen Cito, Jasmin Wachter.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: LLM-driven autonomous agents are reshaping offensive security.

Primary paperarxivcs.CR
Original
Automation / Agentic Systems
GitHub Blog7/22/2026
Recently

Copilot vs. raw API access: What are you actually paying for?

Copilot now bills usage at listed API rates. Compare direct model access with the coding workflow, policy, and harness work around it. The post Copilot vs.

Why it matters

Read this for the official technical update in Automation / Agentic Systems: Compare direct model access with the coding workflow, policy, and harness work around it.

Official sourceAI & MLGitHub Copilot
Original

Archived section

Research Papers · 5

Research Papers
arXiv7/22/2026
Recently

Constant-time decoding of Gabidulin codes and their generalizations with application to RQC

Gabidulin codes are a rank metric analog of Reed-Solomon codes. Although these codes are used in different very efficient rank-based cryptosystems like the RQC cryptosystem or the Loidreau cryptosystem, there was no constant-time implementation of Gabidulin codes, when having a constant-time implementation is crucial for real-life development of cryptosystems. In this paper, we propose the first constant-time decoding algorithm of Augmented Gabidulin (AG) codes, a simple variation on Gabidulin codes where one adds zero columns to Gabidulin codes, and which contains the case of Gabidulin codes. Authors: Nicolas Aragon, Chloé Baïsse, Anthony Fraga.

Why it matters

Read this for the paper's specific claim in Research Papers: Gabidulin codes are a rank metric analog of Reed-Solomon codes.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/22/2026
Recently

Chained Attacks on Drone-Based Federated Learning: From Network Disruption to Device Impersonation

Edge Intelligence (EI) has emerged as a transformative model for mission-critical unmanned platforms, such as drone swarms, by enabling collaborative model training at the network periphery. However, the security of FL deployments depends on both network availability and robust client authentication mechanisms. This paper investigates a chained attack against drone-based FL systems that combines network-layer denial-of-service with credential-based impersonation. Authors: Suleiman Muhammad Sabo, Hamed Alkharsh, Peilin Li.

Why it matters

Read this for the paper's specific claim in Research Papers: Edge Intelligence (EI) has emerged as a transformative model for mission-critical unmanned platforms, such as drone swarms, by enabling collaborative model training at the network periphery.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/21/2026
Recently

PTSan: A Practical Memory Safety Sanitizer for C/C++ with Pointer-Object Authority

Memory safety errors remain the dominant source of severe vulnerabilities in C and C++. Pointer-based sanitizers provide stronger guarantees than location-based tools such as LLVM's ASan, but their overhead and compatibility limitations have constrained production use. We present PTSan, an LLVM sanitizer that makes pointer-based checking practical by storing an object identifier in each pointer's high bits and its bounds in a fixed-size runtime table. Authors: Eli Davis, Eric Lahtinen, Michael Gordon.

Why it matters

Read this for the paper's specific claim in Research Papers: Memory safety errors remain the dominant source of severe vulnerabilities in C and C++.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/20/2026
Recently

CutBackdoor: A Circuit Cut Triggered Backdoor Attack on Variational Quantum Algorithms

Variational Quantum Algorithms (VQAs) are a leading paradigm for near-term quantum computing, combining parameterized quantum circuits with classical optimization across quantum chemistry, combinatorial optimization, and quantum machine learning. Since real-world VQA deployments routinely require circuits that exceed available hardware capacity, quantum circuit cutting has become an indispensable execution strategy, and pre-trained parameters are increasingly distributed through public repositories, introducing supply-chain security risks that have received little attention. Prior quantum backdoor attacks either introduce detectable circuit modifications or depend on device-specific noise, and none consider circuit cutting as an attack surface. Authors: Ahatesham Bhuiyan, Hoang Ngo, Cheng Chu.

Why it matters

Read this for the paper's specific claim in Research Papers: Variational Quantum Algorithms (VQAs) are a leading paradigm for near-term quantum computing, combining parameterized quantum circuits with classical optimization across quantum chemistry, combinatorial optimization, and quantum machine learning.

Primary paperarxivquant-ph
Original
Research Papers
arXiv7/21/2026
Recently

SoK: Adversarial Robustness of the Variational Quantum Eigensolver via Red-Teaming

The Variational Quantum Eigensolver (VQE) is a leading algorithm for estimating molecular ground-state energies on near-term quantum hardware, with applications spanning quantum chemistry, materials science, and drug discovery. As VQE workloads are increasingly deployed through cloud-based ``VQE-as-a-service'' pipelines, they become exposed to adversaries such as compromised service components, malicious co-tenants, or insiders in the transpilation stack, any of which can corrupt results before they reach the user. A range of attacks on variational quantum circuits has been proposed, but each has been studied in isolation: some on quantum classifiers with accuracy-based metrics, others on variational quantum algorithms with energy-error metrics. Authors: Ahmed Azaz Humdoon, Cheng Chu, Lei Jiang.

Why it matters

Read this for the paper's specific claim in Research Papers: The Variational Quantum Eigensolver (VQE) is a leading algorithm for estimating molecular ground-state energies on near-term quantum hardware, with applications spanning quantum chemistry, materials science, and drug discovery.

Primary paperarxivquant-ph
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/22/2026
Recently

Closing the Lab-to-Store Gap: A Data-Efficient Post-Training and Experience-Driven Learning VLA Framework for Retail Humanoids

Closing the gap between benchmark performance and reliable real-world operation remains a central challenge for Vision-Language-Action (VLA) humanoid robots, which must handle execution errors, distribution shifts, and environmental variability. 6 foundation model. DEED comprises three key components: (1) a data-efficient post-training pipeline with control-frequency alignment, data curation, task-relevant visual highlighting, and reduced VLA dependence; (2) a real-world study of experience-driven refinement, adapted from RECAP via a text-based advantage prefix and a vision-language value function; and (3) a latent-space analysis tool for studying in- and out-of-distribution behavior. Authors: Roger Sala Sisó, Tiago Silvério, Jakob Sand.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Closing the gap between benchmark performance and reliable real-world operation remains a central challenge for Vision-Language-Action (VLA) humanoid robots, which must handle execution errors, distribution shifts, and environmental variability.

Primary paperarxivcs.RO
Original
Embedded Systems
Hackster.io7/22/2026
Recently

Firewall3D Aims to Protect Your 3D Printer Against Attacks from Malicious Firmware

Researchers at Texas A&M University's department of electrical and computer engineering have come up with a way to protect 3D printers from attacks via specially-crafted firmware updates that could exfiltrate data or even permanently damage the printer's hardware: Firewall3D. "As the 3D printing market continues to grow rapidly, with an estimated value exceeding $30 billion, cybersecurity risks and attacks targeting additive manufacturing systems are also increasing," co-authors Seyed Ali Ghazi Asgar and Narasimha Reddy explain by way of background to their project. "These attacks aim to sabotage printed components, steal intellectual property, or even physically damage the 3D printer itself.

Why it matters

Read this for the engineering context in Embedded Systems: Researchers at Texas A&M University's department of electrical and computer engineering have come up with a way to protect 3D printers from attacks via specially-crafted firmware updates that could exfiltrate data or even permanently damage the printer's hardware: Firewall3D.

Trusted source
Original
Embedded Systems
NVIDIA Technical Blog7/20/2026
Recently

Integrate NVIDIA Omniverse RTX Sensor Simulation Into Existing Apps

Developers building 3D, design, simulation, robotics, and industrial digital twin applications need ways to bring physical AI capabilities into the tools and... Developers building 3D, design, simulation, robotics, and industrial digital twin applications need ways to bring physical AI capabilities into the tools and services they already use. Many of these workflows already depend on OpenUSD scenes, simulation-ready (SimReady) assets, Blender-based workflows, CAD pipelines, or domain-specific app stacks.

Why it matters

Read this for the official technical update in Embedded Systems: Developers building 3D, design, simulation, robotics, and industrial digital twin applications need ways to bring physical AI capabilities into the tools and...

Official source
Original
Embedded Systems
IEEE Spectrum7/20/2026
Recently

SEM-Guided Low-kV FIB Finishing for Leading-Edge Semiconductor Failure Analysis

Discover how the ZEISS Crossbeam 750 FIBSEM sets a new benchmark for precise TEM lamella prep, tomography, and advanced nanofabrication. This delivers better resolution, better SNR, larger usable FOV, and shorter acquisition times. Learn how uninterrupted FIB milling will reduce damage and rework, accelerate time to TEM, and increase first pass success—so your FA, yield, and materials teams make faster, confident data driven decisions.

Why it matters

Read this for the concrete reporting in Embedded Systems: Discover how the ZEISS Crossbeam 750 FIBSEM sets a new benchmark for precise TEM lamella prep, tomography, and advanced nanofabrication.

Trusted sourceType-webinarSemiconductors
Original
Embedded Systems
Hackaday7/22/2026
Recently

V Formation Flying of Birds is Explained by a Minimal Wake–Vortex Model

Although it's commonly suspected that migratory birds fly in a 'V' formation due to this saving energy for the birds in the slipstream, understanding the exact aerodynamics behind this and …read more

Why it matters

Read this for the engineering context in Embedded Systems: Although it's commonly suspected that migratory birds fly in a 'V' formation due to this saving energy for the birds in the slipstream, understanding the exact aerodynamics behind this and …read more

Trusted sourceSciencebirds
Original

Archived section

Computer Systems · 5

Computer Systems
arXiv7/22/2026
Recently

DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems

While combinatorial optimization problems are central to many scientific and engineering applications, their solution remains challenging due to exponentially large search spaces. Variational quantum algorithms offer a promising route for tackling such problems, yet their practical performance is limited by repeated quantum circuit evaluations and classical parameter updates. In this work, we introduce DQAOA-GPT, a hybrid framework that integrates the distributed quantum approximate optimization algorithm (DQAOA), which decomposes a large optimization problem into smaller sub-problems, with GPT-based quantum circuit generation for solving those sub-problems. Authors: Seongmin Kim, Abhinav Rijal, Yuri Alexeev.

Why it matters

Read this for the paper's specific claim in Computer Systems: While combinatorial optimization problems are central to many scientific and engineering applications, their solution remains challenging due to exponentially large search spaces.

Primary paperarxivquant-ph
Original
Computer Systems
arXiv7/22/2026
Recently

PolySim: Deterministic Polynomial Surrogates for Cross-Modal Retrieval on CiM

Cross-modal retrieval on edge devices benefits from probabilistic embeddings that capture semantic uncertainty, but deploying them on compute-in-memory (CiM) hardware remains an open problem. The core difficulty is a sampling gap: probabilistic methods such as PCME rely on Monte Carlo sampling and nonlinear distance evaluation at inference, which are fundamentally incompatible with CiM crossbar arrays that support only deterministic, single-step matrix-vector multiplication. Few existing probabilistic retrieval methods can be executed on a conventional crossbar. Authors: Xinzhao Li, Charles Power, Pengyu Ren.

Why it matters

Read this for the paper's specific claim in Computer Systems: Cross-modal retrieval on edge devices benefits from probabilistic embeddings that capture semantic uncertainty, but deploying them on compute-in-memory (CiM) hardware remains an open problem.

Primary paperarxivcs.ET
Original
Computer Systems
arXiv7/20/2026
Recently

uSTM: A Lightweight and Efficient STM Supporting General Types and Deferred Aborts

Software Transactional Memory (STM) systems allow developers to more easily exploit multicore architectures by wrapping arbitrary sequential code in transactions that are executed concurrently. In recent years, the performance of STM systems has approached that of hand-tuned data structures through techniques that avoid unnecessary aborts and exploit the semantics of underlying data structures. Despite achieving excellent performance, most STM systems do not fully address the concerns they targeted in the first place: safety, usability, and generality. Authors: Zachary Kent, Guy Blelloch, André Costa.

Why it matters

Read this for the paper's specific claim in Computer Systems: Software Transactional Memory (STM) systems allow developers to more easily exploit multicore architectures by wrapping arbitrary sequential code in transactions that are executed concurrently.

Primary paperarxivcs.DC
Original
Computer Systems
arXiv7/21/2026
Recently

A Flexible Sparsity-Aware FPGA Accelerator with Column-Wise Compression for Efficient CNN Inference

Efficient acceleration of convolutional neural networks (CNNs) on resource-constrained platforms remains challenging due to the irregularity of sparsity patterns and the associated hardware overhead. While unstructured sparsity offers high model accuracy, it introduces significant inefficiencies in hardware mapping, whereas structured sparsity simplifies execution at the cost of reduced flexibility. This paper presents SparHiXcel-v2, a cost-effective and highly configurable FPGA-based CNN accelerator that achieves an improved balance between sparsity flexibility and hardware efficiency. Authors: Amirhossein Zarei, Shervin Vakili.

Why it matters

Read this for the paper's specific claim in Computer Systems: Efficient acceleration of convolutional neural networks (CNNs) on resource-constrained platforms remains challenging due to the irregularity of sparsity patterns and the associated hardware overhead.

Primary paperarxivcs.AR
Original
Computer Systems
CNCF Blog7/22/2026
Recently

Multi-Cluster databases on Kubernetes: Architecture and deployment

Introduction Running a database on Kubernetes is well understood. Running one that survives a complete regional failure, a corrupted control plane, or a severed network requires a fault-resistant architecture. This post walks through how to build...

Why it matters

Read this for the official technical update in Computer Systems: Introduction Running a database on Kubernetes is well understood.

Official sourceBlog
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv7/22/2026
Recently

Multi-Source and Cross-Scenario Strategy-Guided Code Optimization

Automated code optimization improves program performance by refactoring source code, and recent studies use LLMs to generate optimization patches. The newest approaches are strategy-guided: they summarize strategies from historical optimization commits as static analysis rules, and use these rules to match code locations for LLMs to optimize., different programming languages, but existing approaches can only formalize strategies for the scenario to which the source commit belongs. Authors: Yuwei Zhao, Qianyu Xiao, Ye Cui.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Automated code optimization improves program performance by refactoring source code, and recent studies use LLMs to generate optimization patches.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
Vercel Blog7/21/2026
Recently

How Searchable ships customer-requested features in 30 minutes on Vercel

Searchable on Vercel 5x increase in development velocity 100+ billion tokens processed Customer-requested features shipped in as little as 30 minutes Zero model SDK implementation or API key rotation with AI Gateway AI SDK AI Gateway Read more

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Searchable on Vercel 5x increase in development velocity 100+ billion tokens processed Customer-requested features shipped in as little as 30 minutes Zero model SDK implementation or API key rotation with AI Gateway AI SDK AI Gateway Read more

Official source
Original
Developer Tools / Open Source
Docker Blog7/22/2026
Recently

Runtime Enforcement, Not Runtime Advice

Explore governance at the runtime layer and learn why isolation, policy enforcement, and controlled tool access are becoming foundational for agentic systems.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Explore governance at the runtime layer and learn why isolation, policy enforcement, and controlled tool access are becoming foundational for agentic systems.

Official sourceCommunityAI Agent
Original
Developer Tools / Open Source
GitHub Blog7/22/2026
Recently

Next chapter: Restructuring GitHub's bug bounty program

GitHub is making some significant changes to its bug bounty program, shifting its focus to give researchers a better experience working with the GitHub team. The post Next chapter: Restructuring GitHub's bug bounty program appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: GitHub is making some significant changes to its bug bounty program, shifting its focus to give researchers a better experience working with the GitHub team.

Official sourcebug bountysecurity research
Original
Developer Tools / Open Source
LWN.net7/22/2026
Recently

Save and restore may be coming to GNOME

One of the features that users often miss when moving from X11 to Wayland is the ability to save and restore the position of windows between sessions. At GUADEC 2026, held in A Coruña, Spain, Adrian Vovk provided an overview of work that has gone into providing a platform-wide save and restore framework for GNOME. After two failed attempts at landing an API, he believes that the third try will be the one to succeed—though not in time for the upcoming GNOME 51 release due in October.

Why it matters

Read this for the concrete reporting in Developer Tools / Open Source: One of the features that users often miss when moving from X11 to Wayland is the ability to save and restore the position of windows between sessions.

Trusted source
Original

Archived section

Cloud / Infrastructure · 5

Cloud / Infrastructure
arXiv7/22/2026
Recently

Black-Box Performance Evaluation of Elastic Block Storage: Contract, Rate-Limiting Model, and Software Exploration

Elastic block storage (EBS) with the storage-compute disaggregated architecture is a key component in modern cloud infrastructure. EBS offers users storage resources in the form of elastic solid-state drives (ESSDs). Nonetheless, despite recent efforts that have documented EBS architectures from the provider's perspective, how ESSDs perform differently from local SSDs and how host software should adapt accordingly have not been sufficiently studied. Authors: Yingjia Wang, Ming-Chang Yang.

Why it matters

Read this for the paper's specific claim in Cloud / Infrastructure: Elastic block storage (EBS) with the storage-compute disaggregated architecture is a key component in modern cloud infrastructure.

Primary paperarxivcs.PF
Original
Cloud / Infrastructure
AWS Architecture Blog7/22/2026
Recently

Building a serverless AI assistant at Pelago: concept to care in two weeks

Healthcare organizations face a critical scaling challenge – how to maintain deeply personalized patient interactions as member bases grow, without overwhelming care teams or compromising quality.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Healthcare organizations face a critical scaling challenge – how to maintain deeply personalized patient interactions as member bases grow, without overwhelming care teams or compromising quality.

Official sourceCustomer SolutionsServerless
Original
Cloud / Infrastructure
CNCF Blog7/21/2026
Recently

Platform engineering for the agentic enterprise: Managing applications, resources, and AI agents

Platform engineering is evolving Platform engineering has become one of the defining disciplines of the cloud native era. As organizations embraced Kubernetes, microservices, GitOps, and distributed architectures, the complexity of building and operating software grew beyond...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Platform engineering is evolving Platform engineering has become one of the defining disciplines of the cloud native era.

Official sourceBlog
Original
Cloud / Infrastructure
AWS Blog7/20/2026
Recently

AWS Weekly Roundup: One-click Lambda setup prompt, OpenAI GPT-5.6 models on Bedrock, and more (July 20, 2026)

Last week, my team visited Seoul to meet AWS Korea User Group (AWSKRUG) leaders. AWSKRUG is the largest cloud developer community in Korea, with 20 meetup groups organized by topic and area that collectively host over 100 events each year, primarily in Seoul.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Last week, my team visited Seoul to meet AWS Korea User Group (AWSKRUG) leaders.

Official sourceAmazon BedrockAmazon Cognito
Original
Cloud / Infrastructure
Vercel Blog7/21/2026
Recently

Introducing the new Vercel Agent

Today we're expanding. It started by triaging alerts and reviewing your pull requests. Vercel Agent Because Vercel Agent is built into the platform that deploys and runs your app, when something changes in production, it's your first responder.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: It started by triaging alerts and reviewing your pull requests.

Official source
Original