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Artificial Intelligence / Machine Learning · 5

Automation / Agentic Systems · 5

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Embedded Systems · 5

Computer Systems · 5

Developer Tools / Open Source · 5

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Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/17/2026
Recently

ToolSciVer: Multimodal Scientific Claim Verification with Visual Tool Augmented Reinforcement Learning

Multimodal Scientific Claim Verification (MSCV) requires models to verify scientific claims using visually grounded evidence from papers, including figures, tables, charts, and textual context. However, existing methods often fail because they struggle to locate decisive visual evidence, accurately read structured scientific visuals, and integrate multimodal observations into reliable reasoning. We introduce ToolSciVer, the first tool-augmented framework for MSCV to our knowledge. Authors: Binglin Zhou, Peng Shi, Ryo Kamoi.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Multimodal Scientific Claim Verification (MSCV) requires models to verify scientific claims using visually grounded evidence from papers, including figures, tables, charts, and textual context.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv7/17/2026
Recently

A Blueprint for Equilibrium-Based Differentiable Continuous-Variable Thermodynamic Computing

To address the escalating energy and latency demands of machine-learning workloads, we introduce a blueprint for an energy-efficient and fast thermodynamic computing stack that leverages stochastic analog processes in physical hardware. In this work, we focus on energy-based thermodynamic computing where the stochastic process is well described by Langevin dynamics with tunable energy potentials. The implementation of such potentials in physical hardware enables us to generate and sample from basic parameterized energy-based models. Authors: Owen Lockwood, Jérémy Béjanin, Joost Bus.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: To address the escalating energy and latency demands of machine-learning workloads, we introduce a blueprint for an energy-efficient and fast thermodynamic computing stack that leverages stochastic analog processes in physical hardware.

Primary paperarxivcs.LG
Original
Artificial Intelligence / Machine Learning
arXiv7/17/2026
Recently

Evaluating Open-Weight LLMs for Generating Structured Threat Information for Autonomous Vehicle Vulnerabilities

Connected and Autonomous Vehicles (CAVs) rely on interconnected software and hardware components, including sensors, Electronic Control Units, in-vehicle infotainment systems, and telematics units, where vulnerabilities can compromise assets, users, and vehicle operations. These vulnerabilities are commonly documented as plain text in the Common Vulnerabilities and Exposures (CVE) database; however, security practitioners require structured information about affected assets, types of weaknesses, and attack behaviors to effectively mitigate the risks from these vulnerabilities. To this end, we evaluate open-weight Large Language Models (LLMs) for generating Structured Threat Information Expression (STIX), a well-known structured format for representing threat information, for CAV-related CVEs. Authors: Md Erfan, Ahmed Ryan, Md Kamal Hossain Chowdhury.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Connected and Autonomous Vehicles (CAVs) rely on interconnected software and hardware components, including sensors, Electronic Control Units, in-vehicle infotainment systems, and telematics units, where vulnerabilities can compromise assets, users, and vehicle operations.

Primary paperarxivcs.CR
Original
Artificial Intelligence / Machine Learning
Netflix Tech Blog7/17/2026
Recently

In-House LLM Serving at Netflix

By AI Platform's Model Runtime team and Inference team Introduction Most organizations consume LLMs through hosted APIs. Netflix went further — we run the full stack ourselves, from model deployment through inference, inside our existing production environment rather than a separate ML silo. Some of those decisions weren't obvious, and a few revealed their trade-offs only under production load.

Why it matters

Read this for the engineering context in Artificial Intelligence / Machine Learning: By AI Platform's Model Runtime team and Inference team Introduction Most organizations consume LLMs through hosted APIs.

Trusted sourceaiplatform-engineering
Original
Artificial Intelligence / Machine Learning
MIT Technology Review7/20/2026
Recently

AI is more likely than humans to form biases when hiring

The next time you apply for a job, AI may screen your résumé before any human sees it. But there's good reason to question whether AI will judge you fairly. Researchers already know that LLMs pick up human biases from their training data.

Why it matters

Read this for the concrete reporting in Artificial Intelligence / Machine Learning: The next time you apply for a job, AI may screen your résumé before any human sees it.

Trusted sourceArtificial intelligenceAI
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/17/2026
Recently

SciForge: An AI-Native, Multimodal Workbench for Scientific Discovery

Scientific work increasingly spans heterogeneous artifacts -- papers, code, datasets, scientific file formats, model outputs, figures, manuscripts, and team decisions -- yet general-purpose AI assistants rarely preserve these objects as a coherent, auditable research state. We present SciForge, a multimodal research-native AI workbench that reserves the graphical interface for human judgment while search, parsing, model routing, workflow execution, plotting, writing, and presentation generation run as modular agent-accessible services. SciForge is built around five pillars: (i) goal-scoped scientific decision governance for goal-oriented research, with review gates and shared review surfaces; (ii) translate-then-reason for multimodal input, routing scientific objects through domain translators before the agent reasons; (iii) evidence governance for auditable traceability, linking claims to provenance chains and audit findings; (iv) collaborative team science for collaborative research, enabling multi-role decision governance, with shared team workspaces planned for future releases; and (v) real-world application scenarios for practical impact, demonstrated through eight end-to-end user cases, with flagship demonstrations including multi-day agentic research sprints for gene discovery, AI-guided de novo protein design, molecular optimization, and genome-to-BGC discovery. Authors: SciForge Team, Zhangyang Gao, Minghao Fang.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Scientific work increasingly spans heterogeneous artifacts -- papers, code, datasets, scientific file formats, model outputs, figures, manuscripts, and team decisions -- yet general-purpose AI assistants rarely preserve these objects as a coherent, auditable research state.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/17/2026
Recently

When Model Merging Rivals Joint Multi-Task Reinforcement Learning: A Task-Vector Geometry Analysis

Model merging is promoted as a substitute for joint multi-task training, yet in the reinforcement-learning setting this substitution is essentially never tested against the baseline it claims to replace: methods merge independently released agents precisely because a joint model is unavailable. We build the missing comparison. Training difficulty-1 and difficulty-2 Qwen3-8B specialists on the AppWorld agent benchmark with LOOP, we merge them (TIES, RAM+) and pit the result against a jointly trained model on the same data. Authors: S. Aaron McClendon.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Model merging is promoted as a substitute for joint multi-task training, yet in the reinforcement-learning setting this substitution is essentially never tested against the baseline it claims to replace: methods merge independently released agents precisely because a joint model is unavailable.

Primary paperarxivcs.LG
Original
Automation / Agentic Systems
arXiv7/17/2026
Recently

LLM-Powered Agentic AI for 5G/6G Networks: A Tutorial and Survey on Architectures, Protocols, and Standardization

Agentic Artificial Intelligence (AI), enabled by Large Language Models, marks a shift from rule-based automation toward autonomous, goal-driven control of Next-Generation Networks (NGNs). Existing surveys treat the two domains in isolation, leaving protocol integration, evaluation, and standardization alignment underexplored. To address this gap, a two-part tutorial-and-survey is presented. Authors: Mazene Ameur, Abdelkader Mekrache, Bouziane Brik.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Agentic Artificial Intelligence (AI), enabled by Large Language Models, marks a shift from rule-based automation toward autonomous, goal-driven control of Next-Generation Networks (NGNs).

Primary paperarxivcs.NI
Original
Automation / Agentic Systems
arXiv7/17/2026
Recently

Knowing the Self, Understanding the World: A Dual-Cognition Benchmark for UAV Spatio-temporal Reasoning with MLLMs

Multimodal large language models have achieved strong performance across diverse vision-language tasks, yet their capabilities in UAV scenarios remain insufficiently explored. Recent UAV-oriented benchmarks have begun to evaluate MLLMs in aerial scenarios, but they typically focus on scene understanding, event recognition, or navigation completion, rather than jointly assessing the dual-cognition capability required for UAV agents: reasoning about both the UAV's own state and the external environment in multiview spatio-temporal contexts. To address this gap, we present UAV-DualCog, a benchmark for aerial multiview spatio-temporal reasoning built on this dual-cognition perspective. Authors: Like Liu, Zhengzheng Xu, Haitao He.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Multimodal large language models have achieved strong performance across diverse vision-language tasks, yet their capabilities in UAV scenarios remain insufficiently explored.

Primary paperarxivcs.CV
Original
Automation / Agentic Systems
arXiv7/17/2026
Recently

PRISA: Proactive Infrastructure LiDAR Framework for Intersection Safety Assessment

Urban intersections are among the most hazardous locations in road networks, posing significant risks to vehicles and vulnerable road users (VRUs) such as pedestrians and cyclists. The complexity of multi-agent interactions demands continuous, real-time monitoring systems capable of anticipating conflicts before they escalate into crashes. We present PRISA, a modular infrastructure LiDAR framework leveraging privacy-preserving, low-light-robust roadside sensors for long-term traffic observation and real-time risk detection at the edge. Authors: Tam Bang, Hussam Abubakr, Emiliano de la Garza Villarreal.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Urban intersections are among the most hazardous locations in road networks, posing significant risks to vehicles and vulnerable road users (VRUs) such as pedestrians and cyclists.

Primary paperarxivcs.LG
Original

Archived section

Research Papers · 3

Research Papers
arXiv7/17/2026
Recently

Student Evaluation of Repeated AI Feedback Across a Semester of Writing

Generative AI is increasingly used for feedback in higher education, but evidence from repeated classroom use remains limited. This short paper analyses 2988 reflective essay-feedback-appraisal instances from 283 Estonian bachelor students across one semester. Students obtained and assessed feedback from a self-selected AI tool using a uniform prompt. Authors: Andres Karjus, Janika Leoste, Tiia Õun.

Why it matters

Read this for the paper's specific claim in Research Papers: Generative AI is increasingly used for feedback in higher education, but evidence from repeated classroom use remains limited.

Primary paperarxivcs.CY
Original
Research Papers
arXiv7/17/2026
Recently

Gasp: A DeFi Application Specic Rollup as a Consolidation Layer for All Assets

Gasp is a decentralized exchange designed as an application-specific Layer 2 (L2) rollup with omnichain connectivity, leveraging EigenLayer's restaked ETH for computation correctness and finalization. With a goal of being a consolidation layer for all crypto assets, the Gasp platform employs optimistic rollup technology to facilitate gas-free, native cross-chain swaps without reliance on traditional bridges, ensuring tokens retain their original L1 grade security. By combining an app-chain architecture with escape hatch mechanisms, Gasp guarantees withdrawal, while MEV minimization through Themis architecture reduces value extraction risks. Authors: Stanislav Vozarik, Mateusz Nowakowski, Shoeb Siddiqui.

Why it matters

Read this for the paper's specific claim in Research Papers: Gasp is a decentralized exchange designed as an application-specific Layer 2 (L2) rollup with omnichain connectivity, leveraging EigenLayer's restaked ETH for computation correctness and finalization.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/17/2026
Recently

DoSQ: A Cross-Layer Denial of Service Quality Attack by Exploiting Side Channels in 5G NR

The 3rd Generation Partnership Project (3GPP)'s Fifth Generation New Radio (5G NR) is critical to supporting mission-critical services., cross-layer). The 5G gNB broadcasts resource scheduling information for the legitimate UEs over the air interface, with a prevailing assumption that this surface alone reveals nothing useful about a user device. Authors: Mahmudul Hassan Ashik, Moinul Hossain.

Why it matters

Read this for the paper's specific claim in Research Papers: The 5G gNB broadcasts resource scheduling information for the legitimate UEs over the air interface, with a prevailing assumption that this surface alone reveals nothing useful about a user device.

Primary paperarxivcs.CR
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/17/2026
Recently

A New Implementation of NeoSLAM and a Comparative Evaluation with RatSLAM

This paper presents a new implementation of the NeoSLAM algorithm. The proposed version is a complete rewrite of NeoSLAM into a modular architecture using modern frameworks that, together, enable real-time execution with minimal discarding of input data. This work also provides a comparative evaluation between NeoSLAM and RatSLAM across three datasets under varying environmental conditions. Authors: Joao Victor T. Borges, Fabio Coelho, Paulo Padrao.

Why it matters

Read this for the paper's specific claim in Embedded Systems: presents a new implementation of the NeoSLAM algorithm.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv7/17/2026
Recently

CLIFE: Camera-LiDAR Fusion Framework for Edge-Deployable Roadside VRU Perception

Reliable roadside perception of vulnerable road users (VRUs) remains challenging under occlusions, variable lighting, and diverse weather conditions, particularly under strict edge-computing and latency constraints. Existing multi-sensor fusion systems rely on cloud or server-grade infrastructure, creating a deployment gap at real-world intersections. We present CLIFE, an edge-native camera-LiDAR fusion framework that integrates targetless online calibration and lightweight late-fusion tracking entirely on a single embedded device, without cloud offloading. Authors: Tam Bang, Hoang H. Nguyen, Lei Cheng.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Reliable roadside perception of vulnerable road users (VRUs) remains challenging under occlusions, variable lighting, and diverse weather conditions, particularly under strict edge-computing and latency constraints.

Primary paperarxivcs.CV
Original
Embedded Systems
arXiv7/17/2026
Recently

The Internet of Things for Smart Manufacturing: A Review

The modern manufacturing industry is investing in new technologies such as the Internet of Things (IoT), big data analytics, cloud computing and cybersecurity to cope with system complexity, increase information visibility, improve production performance, and gain competitive advantages in the global market., a cyber-physical system tightly integrating manufacturing enterprises in the physical world with virtual enterprises in cyberspace. To a great extent, realizing the full potential of cyber-physical systems depends on the development of new methodologies on the Internet of Manufacturing Things (IoMT) for data-enabled engineering innovations. Authors: Hui Yang, Soundar Kumara, Satish Bukkapatnam.

Why it matters

Read this for the paper's specific claim in Embedded Systems: , a cyber-physical system tightly integrating manufacturing enterprises in the physical world with virtual enterprises in cyberspace.

Primary paperarxiveess.SY
Original
Embedded Systems
Hackster.io7/17/2026
Recently

NVIDIA Unveils Smaller, More Efficient Jetson Modules

Autonomous robots are rapidly moving beyond research labs and into warehouses, factories, stores, and other real-world environments. But running the sophisticated AI models needed to perceive surroundings, understand instructions, and make decisions requires a lot of computing power. NVIDIA is attempting to address that challenge with two new Jetson modules that bring its Blackwell-powered Thor architecture to smaller, more power-efficient edge AI systems.

Why it matters

Read this for the engineering context in Embedded Systems: Autonomous robots are rapidly moving beyond research labs and into warehouses, factories, stores, and other real-world environments.

Trusted source
Original
Embedded Systems
Hackster.io7/18/2026
Recently

Embedded Arena Uses Hardware Feedback to Perfect Edge AI Models

AI has become quite good at writing code, answering questions, and solving complex problems. But when it comes to deploying AI algorithms onto tiny microcontrollers, even the most advanced models have been hitting a wall. This is because it is not just about writing code — strict real-world constraints involving memory, power consumption, temperature, and hardware compatibility have to be met as well.

Why it matters

Read this for the engineering context in Embedded Systems: AI has become quite good at writing code, answering questions, and solving complex problems.

Trusted source
Original

Archived section

Computer Systems · 5

Computer Systems
AWS Architecture Blog7/17/2026
Recently

Eclipse Dataspace Components on AWS: Data sharing fundamentals

This three-part blog series guides you through implementing Eclipse Dataspace Components (EDC) on AWS, from foundational concept to production deployment. Part 1 establishes the theoretical foundation with IDSA standards, the Dataspace Protocol (DSP), and core EDC architecture.

Why it matters

Read this for the official technical update in Computer Systems: This three-part blog series guides you through implementing Eclipse Dataspace Components (EDC) on AWS, from foundational concept to production deployment.

Official sourceAmazon API GatewayAmazon Aurora
Original
Computer Systems
arXiv7/17/2026
Recently

Reducing Power Consumption of Embedded Dynamic Memories with ECCs

Gain-cell embedded dynamic random-access memory (GCRAM) offers dense and energy-efficient on-chip storage, but retention-time variations force frequent refresh operations to cover worst-case bits. Error-correction codes (ECCs) can alleviate this limitation by masking bit errors from weak cells and thereby reduce refresh cost. However, the trade-off between the additional access and logic energy introduced by ECCs and the power savings from longer refresh intervals is nontrivial, especially considering the wide range of available ECC options. Authors: Wenqing Song, Yifei Shen, Andreas Burg.

Why it matters

Read this for the paper's specific claim in Computer Systems: Gain-cell embedded dynamic random-access memory (GCRAM) offers dense and energy-efficient on-chip storage, but retention-time variations force frequent refresh operations to cover worst-case bits.

Primary paperarxivcs.IT
Original
Computer Systems
arXiv7/17/2026
Recently

Every Microsecond Matters: Achieving Near Speed-of-Light Latency in GPU Collectives

GPU collective communication is typically optimized for bandwidth, yet many emerging workloads are increasingly limited by latency. Long-context decode-heavy large language model (LLM) inference is a prime example, where serving large models requires multiple GPUs, and many small collectives lie directly on the critical path of token generation. Therefore, even microsecond of overhead can impact performance and cost. Authors: Siyuan Shen, Anton Korzh, John Bachan.

Why it matters

Read this for the paper's specific claim in Computer Systems: GPU collective communication is typically optimized for bandwidth, yet many emerging workloads are increasingly limited by latency.

Primary paperarxivcs.DC
Original
Computer Systems
arXiv7/17/2026
Recently

From Patterns to Parsers: Automatic Generation of Efficient Hardware Parsers for FPGAs

This work presents an open-source tool for automatically generating efficient hardware parsers from high-level specifications. It uses a parsing intermediate representation (PIR) that decouples application-specific frontends from a common register-transfer level (RTL) generation backend. The backend produces optimized, human-readable SystemVerilog, handling FSM generation, byte-alignment, and multi-cycle field straddling for arbitrary datapath widths. Authors: Tushar Garg, Andrew Boutros.

Why it matters

Read this for the paper's specific claim in Computer Systems: This work presents an open-source tool for automatically generating efficient hardware parsers from high-level specifications.

Primary paperarxivcs.AR
Original
Computer Systems
LWN.net7/17/2026
Recently

Building an Arch Linux aarch64 port for Holo Core (Collabora blog)

Collabora has published a blog post about its work with Valve on Holo Core, which is a port of Arch Linux to aarch64 to be used as the the operating system on Valve's 64-bit Arm Steam Frame gaming system. Collabora has released the sources, binary packages, and a container image for aarch64 devices. The post describes some of the challenges in porting Arch Linux to a new architecture, and what remains to be done: Whilst the infrastructure developed to this point is capable of building from first principles up until a point-in-time snapshot, the next step is to build this into a system which can track Arch Linux as it is developed.

Why it matters

Read this for the concrete reporting in Computer Systems: Collabora has published a blog post about its work with Valve on Holo Core, which is a port of Arch Linux to aarch64 to be used as the the operating system on Valve's 64-bit Arm Steam Frame gaming system.

Trusted source
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv7/17/2026
Recently

CADAQUES: A Cost-Aware Dual Architecture for Query-Efficient Autonomous Discovery

Autonomous discovery systems couple a resource that answers queries (a simulator, instrument, or analytic model) to an algorithm that selects what to query next. Most software frameworks for this loop inherit the control structure of numerical optimization: campaigns run for a fixed number of iterations, query costs are absent from the programming interface, and decision-making is treated as free. In practice, queries may differ in cost by orders of magnitude, and planners built on large language models or expensive surrogates consume resources of their own. Authors: Jorge Bravo-Abad.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Autonomous discovery systems couple a resource that answers queries (a simulator, instrument, or analytic model) to an algorithm that selects what to query next.

Primary paperarxivphysics.comp-ph
Original
Developer Tools / Open Source
arXiv7/17/2026
Recently

Comparison of Energy System Optimization Software and Evaluation of Selected Frameworks

Optimizing energy systems is a crucial step toward achieving a carbon-neutral future, with software tools playing a major role in the process. However, selecting the most suitable tool for specific optimization challenges can be complex, given the diverse objectives and requirements of various energy systems. In this study, we aim to address this issue by evaluating five preselected software tools-REMix, MTRESS, COMANDO, OEMOF, and HOMER PRO-to identify the scenarios for which they are most suitable. Authors: Pedro Caixeta, David Gawron, Hüseyin K. Çakmak.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Optimizing energy systems is a crucial step toward achieving a carbon-neutral future, with software tools playing a major role in the process.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
arXiv7/17/2026
Recently

JoyNexus: Service-Oriented Multi-Tenant Post-Training for VLA Models

The post-training of Vision-Language-Action (VLA) models is essential due to the diversity of simulators, robot embodiments, and task objectives. Existing compute services, whether offered as direct accelerator rental or batch-workload submission, typically allocate an exclusive set of GPU and CPU resources to a single tenant. While this paradigm maximizes client flexibility, it burdens users with infrastructure adaptation, and the fixed card-hour accounting model renders short or bursty workloads both expensive for tenants and inefficient for the service provider. Authors: Haoran Sun, Wentao Zhang, Junyang Hua.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: The post-training of Vision-Language-Action (VLA) models is essential due to the diversity of simulators, robot embodiments, and task objectives.

Primary paperarxivcs.DC
Original
Developer Tools / Open Source
arXiv7/17/2026
Recently

What Does It Take to Research with AI? A Rapid Review of Competencies to Train LLM-Literate Researchers

The growing adoption of Large Language Models in scientific research has created a need to understand what competencies researchers and graduate students require to use these tools critically and responsibly. 83). Eight competencies were identified. Authors: Danilo Monteiro Ribeiro, Ronnie de Souza Santos, Rodrigo Siqueira.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: The growing adoption of Large Language Models in scientific research has created a need to understand what competencies researchers and graduate students require to use these tools critically and responsibly.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
GitHub Engineering7/17/2026
Recently

The cost of saying yes has changed

The cost of writing code dropped; the cost of owning it didn't. A framework for deciding which changes are actually cheap in the AI era. The post The cost of saying yes has changed appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: The cost of writing code dropped; the cost of owning it didn't.

Official sourceCareer growthDeveloper skills
Original

Archived section

Cloud / Infrastructure · 4

Cloud / Infrastructure
CNCF Blog7/20/2026
Recently

Why goodput matters more than throughput for LLM serving

When we benchmark an LLM serving setup, the number almost everyone reaches for first is throughput: how many requests per second the system can push through. It is easy to measure, easy to compare, and it...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: When we benchmark an LLM serving setup, the number almost everyone reaches for first is throughput: how many requests per second the system can push through.

Official sourceBlog
Original
Cloud / Infrastructure
AWS Architecture Blog7/17/2026
Recently

Eclipse Dataspace Components on AWS: Cost optimization strategies

When you deploy Eclipse Dataspace Components (EDC) connectors on AWS, one of the first challenges you face is predicting and controlling the cost of the required infrastructure. Without clear benchmarks, it is difficult to make informed decisions about workload sizing, environment configuration, and long-term investment.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: When you deploy Eclipse Dataspace Components (EDC) connectors on AWS, one of the first challenges you face is predicting and controlling the cost of the required infrastructure.

Official sourceAmazon API GatewayAmazon Aurora
Original
Cloud / Infrastructure
arXiv7/17/2026
Recently

SQUIRO: A Framework for Security-Aware Quantum-Classical Scheduling on Kubernetes

Distributed infrastructure schedulers traditionally optimise capacity, locality, and cost, but provide limited support for security posture and emerging quantum-classical workloads. As hybrid quantum-classical computing becomes increasingly practical and post-quantum security requirements begin to affect infrastructure deployment, schedulers must jointly reason about heterogeneous compute resources, security constraints, and quantum backend characteristics. We present SQUIRO, a framework for security-aware quantum-classical scheduling based on a platform-independent Unified Scheduling Model (USM) and a six-step Scheduler Design Methodology (SDM) that together enable the derivation of concrete schedulers for Kubernetes, high-performance computing (HPC), and federated environments. Authors: Ignazio Pedone, Edoardo Giusto.

Why it matters

Read this for the paper's specific claim in Cloud / Infrastructure: Distributed infrastructure schedulers traditionally optimise capacity, locality, and cost, but provide limited support for security posture and emerging quantum-classical workloads.

Primary paperarxivcs.ET
Original
Cloud / Infrastructure
AWS Architecture Blog7/17/2026
Recently

Eclipse Dataspace Components on AWS: Architecture patterns in production

Running Eclipse Dataspace Components (EDC) connectors in production on AWS requires deliberate architecture decisions around isolation, managed services, and security layering. In Part 1 of this series, we covered the fundamentals of data space architectures and EDC per the International Data Space Association's (IDSA) standards. If you are new to EDC, we recommend starting there.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Running Eclipse Dataspace Components (EDC) connectors in production on AWS requires deliberate architecture decisions around isolation, managed services, and security layering.

Official sourceAmazon API GatewayAmazon Aurora
Original