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Artificial Intelligence / Machine Learning · 5

Automation / Agentic Systems · 5

Research Papers · 5

Embedded Systems · 5

Computer Systems · 5

Developer Tools / Open Source · 5

Cloud / Infrastructure · 5

Archived section

Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/23/2026
Recently

MedGame: Storytelling Gamification Empowered by Large Language Models for Medical Education

Large Language Models (LLMs) show promise for medical education, but most existing systems focus on localized interactions such as question answering or single-turn feedback, rather than organizing an entire clinical case into a decision-centered learning trajectory. We introduce MedGame, a framework that transforms static clinical cases into structured, executable storytelling games. MedGame uses a dual-engine design: a Medical Narrative Designer synthesizes case-grounded clinical storylines with states and decision nodes, while a Story Director converts them into dependency-aware multimodal orchestration plans rendered by our released interactive platform. Authors: Qian Wu, Xinrong Zhou, Zizhan Ma.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Large Language Models (LLMs) show promise for medical education, but most existing systems focus on localized interactions such as question answering or single-turn feedback, rather than organizing an entire clinical case into a decision-centered learning trajectory.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv7/23/2026
Recently

3D-Aware VLMs with Implicit and Explicit Geometries

Despite rapid progress, most existing vision-language models (VLMs) built from 2D visual inputs often struggle when handling various 3D tasks that require fine-grained spatial understanding and reasoning. To bridge this gap, we present VLM-IE3D, a unified framework that enhances the 3D spatial awareness of VLMs by equipping them with both implicit and explicit 3D geometries learned from RGB videos. Our VLM-IE3D introduces Implicit Geometry Tokens (IGTs) that capture high-level geometric priors from input videos, as well as complementary Explicit Geometry Tokens (EGTs) that encode detailed geometric structures from reconstructed 3D attributes. Authors: Wenhao Li, Xueying Jiang, Quanhao Qian.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Despite rapid progress, most existing vision-language models (VLMs) built from 2D visual inputs often struggle when handling various 3D tasks that require fine-grained spatial understanding and reasoning.

Primary paperarxivcs.CV
Original
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
arXiv7/23/2026
Recently

Surprisal Theory is Tautological (without Rational Grounding)

Surprisal theory holds that the human processing difficulty of a linguistic unit in context is an affine function of its surprisal under some language model. I argue this claim is a tautology without further constraint: for any non-negative difficulty measure over units in context, there exists a language model whose surprisal is an affine function of it under mild technical conditions. Therefore, because any pattern of difficulty is consistent with some language model, without an additional constraint on the language model, surprisal theory makes no falsifiable predictions. Authors: Ryan Cotterell.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Surprisal theory holds that the human processing difficulty of a linguistic unit in context is an affine function of its surprisal under some language model.

Primary paperarxivcs.CL
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/23/2026
Recently

Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems

Production AI agents' failures are less often due to an inability to reason well and more often because they cannot manage what is in their reasoning context: conversation histories, large prompts, large tool definitions, and ballooning tool outputs. Agents drown in their own accumulating history while paying a token cost that grows every turn, producing missing recalls within and across conversations. The incumbent response treats this as a storage-and-retrieval problem. Authors: Gaurav Dadhich.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Production AI agents' failures are less often due to an inability to reason well and more often because they cannot manage what is in their reasoning context: conversation histories, large prompts, large tool definitions, and ballooning tool outputs.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/23/2026
Recently

Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry

AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments. This democratization enables rapid local innovation, but it also creates a reliability gap: agents that appear to users as simple productivity artifacts may depend on changing models, tools, retrieval sources, permissions, prompts, schedules, and external services. These dependencies can cause silent degradation long after deployment, even when no user directly modifies the agent. Authors: Natan Levy, Harel Berger.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/23/2026
Recently

OpenForgeRL: Train Harness-native Agents in Any Environment

Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to external systems. While powerful, these complex harnesses also make agents hard to train end-to-end with open infrastructure, whose SFT/RL stacks cannot natively express stateful, multi-process harness inference. To address this, we present OpenForgeRL, an open-source framework for training harness-based agents end-to-end in diverse environments. Authors: Xiao Yu, Baolin Peng, Ruize Xu.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to external systems.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/23/2026
Recently

Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections

Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, which typically struggle with combinatorial action spaces, reliance on privileged information, or rigid agent designs. We propose Master-Agent Proto-plan System (MAPS), a hierarchical deep reinforcement learning (DRL) architecture in which a centralized Master agent generates a compact, continuous embedding, denoted as proto-plan, that encodes a global coordination strategy. Decentralized Worker agents integrate this embedding with local observations to execute vehicle-specific control, decoupling strategic intent from tactical execution and enabling independent optimization of each module. Authors: Gil Lifshits, Igal Bilik, Gilad Katz.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, which typically struggle with combinatorial action spaces, reliance on privileged information, or rigid agent designs.

Primary paperarxivcs.LG
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
arXiv7/23/2026
Recently

Where You Tap Matters: A Probe-and-Model Benchmark for Open-Set RF Fingerprinting

Radio Frequency Fingerprint Identification (RFFI) enables transmitter identification at the physical layer by learning device-specific impairments from received signals, yet the literature is inconsistent about where in the receiver chain those samples should be collected., carrier recovery, gain normalization, pulse shaping, and timing recovery, they can either tighten within-transmitter variability or suppress the features RFFI requires for classification. We present a systematic real-world evaluation of open-set, reconstruction-error RFFI using data collected at five probe points along a standard BPSK receiver chain. Authors: Gabriele Oligeri, Savio Sciancalepore, Ingrid Huso.

Why it matters

Read this for the paper's specific claim in Research Papers: , carrier recovery, gain normalization, pulse shaping, and timing recovery, they can either tighten within-transmitter variability or suppress the features RFFI requires for classification.

Primary paperarxivcs.CR
Original
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
arXiv7/23/2026
Recently

Sources of Inequity and Fairness Risks inWellbeing Sensing

, depression, cognitive load)., hospitals, universities), yet fairness research remains limited---primarily to post-hoc, identity-based comparisons of model performance. However, passive sensing combines heterogeneous sensing infrastructures, indirect behavioral inference, and longitudinal deployment---characteristics that, while not exclusive to the domain, are jointly pronounced here and raise two underexplored questions: (1) what additional sources of inequity arise from these characteristics, and (2) how do such inequities propagate beyond algorithmic audits across the system lifecycle? Authors: Han Zhang, Vedant Das Swain, Koustuv Saha.

Why it matters

Read this for the paper's specific claim in Research Papers: , hospitals, universities), yet fairness research remains limited---primarily to post-hoc, identity-based comparisons of model performance.

Primary paperarxivcs.HC
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
arXiv7/23/2026
Recently

Transparent by Design, Usable in Practice? A Formative Usability Study of a Conversational Product Advisor

Large language models can make conversational product advisors fluent but opaque. If they hide the logic behind a ranking and the evidence for a recommendation inside natural-language replies, they challenge users' ability to understand, trust, and steer the results. One response is to build transparency into the advisor. Authors: Kevin Schott, Dagmar Kern, Daniel Hienert.

Why it matters

Read this for the paper's specific claim in Research Papers: Large language models can make conversational product advisors fluent but opaque.

Primary paperarxivcs.HC
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/23/2026
Recently

Interoperability of Electric Drive Models using HELICS

Accurate modeling and simulation are essential for the effective design, testing, and evaluation of electric machine systems., C, MATLAB, Python) and the separation of components such as inverters and controllers across diverse environments. These challenges are amplified by the growing use of advanced simulation platforms like Hardware-in-the-Loop (HIL) and Controller-HIL, which require repeated adaptations for compatibility. Authors: Ajay Pratap Yadav.

Why it matters

Read this for the paper's specific claim in Embedded Systems: , C, MATLAB, Python) and the separation of components such as inverters and controllers across diverse environments.

Primary paperarxiveess.SY
Original
Embedded Systems
arXiv7/23/2026
Recently

AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on specialized hardware, centralized operators, or fixed task suites. We present AXIS, a growable community-driven data engine and benchmark for scalable robot learning, which enables browser-based teleoperation for large-scale demonstration collection, automatically generates and validates new manipulation tasks, and transforms community-collected demonstrations into training-ready data through automated success checking, quality filtering, trajectory smoothing, and visual and physics-based augmentation. The AXIS dataset currently contains 207 diverse tasks and 50K+ trajectories. Authors: Mengfei Zhao, Dihong Huang, Yikai Tang.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on specialized hardware, centralized operators, or fixed task suites.

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
Hackaday7/24/2026
Recently

Codeberg Bans Cryptocurrency and LLM-Generated Code Projects

Community-led open source project hosting site Codeberg has formally announced that projects whose code is largely or fully machine-generated through LLMs and other 'AI' tools will no longer be welcome.

Why it matters

Read this for the engineering context in Embedded Systems: Community-led open source project hosting site Codeberg has formally announced that projects whose code is largely or fully machine-generated through LLMs and other 'AI' tools will no longer be welcome.

Trusted sourceArtificial IntelligenceNews
Original
Embedded Systems
arXiv7/23/2026
Recently

Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation

Compositional generalization is essential for robot to follow diverse instructions. However, pretrained policies are known to take shortcuts, deferring to salient cues rather than grounding language., reusable semantic components such as color, verb, object, size, and spatial attribute. Authors: Yu Qi, Zhang Ye, Xinyi Xu.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Compositional generalization is essential for robot to follow diverse instructions.

Primary paperarxivcs.RO
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
AWS Architecture Blog7/22/2026
Recently

Automate custom PII detection at scale with Amazon Macie and Step Functions

Organizations in regulated industries like financial services, insurance, healthcare, and government ingest large volumes of data containing personally identifiable information (PII). Your applications, claims processing systems, partner data feeds, and internal workflows produce files that may include names, addresses, Social Security numbers, and domain-specific identifiers such as policy numbers, member IDs, and medical record numbers.

Why it matters

Read this for the official technical update in Computer Systems: Organizations in regulated industries like financial services, insurance, healthcare, and government ingest large volumes of data containing personally identifiable information (PII).

Official sourceAmazon MacieAWS Step Functions
Original
Computer Systems
LWN.net7/23/2026
Recently

An operations structure for swap devices

One of the ideas raised at the 2026 Linux Storage, Filesystem, Memory Management, and BPF Summit (LSFMM+BPF) was the creation of an operations structure for the swap subsystem. Like many parts of the kernel, the swap layer evolved over time, with pieces being added as needed; the end result of this evolution is rarely what one would expect had the subsystem been designed today. The interface between the swap layer and the devices it uses is just one example.

Why it matters

Read this for the concrete reporting in Computer Systems: One of the ideas raised at the 2026 Linux Storage, Filesystem, Memory Management, and BPF Summit (LSFMM+BPF) was the creation of an operations structure for the swap subsystem.

Trusted source
Original
Computer Systems
arXiv7/23/2026
Recently

Windowed-MTP: Removing the Full-Context Draft-KV Tax at Million-Token Context

Speculative decoding accelerates autoregressive generation by having a cheap draft propose tokens that a target verifies in parallel. Frontier models increasingly ship a built-in Multi-Token-Prediction (MTP/NEXTN) draft head under the assumption that the draft is negligibly cheap. At million-token context this breaks: an MTP draft head typically runs full attention over the entire KV cache at every draft step, so its read grows linearly with context and comes to dominate the draft cost -- precisely where speculation is most valuable. Authors: Alagappan Valliappan.

Why it matters

Read this for the paper's specific claim in Computer Systems: Speculative decoding accelerates autoregressive generation by having a cheap draft propose tokens that a target verifies in parallel.

Primary paperarxivcs.LG
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv7/23/2026
Recently

From Resource Flow to Executable Tests: Petri-Net-Guided LLM Test Generation for Concurrent Stateful Rust APIs

Concurrent stateful library APIs expose behavior through evolving resource ownership, lifecycle states, and competing interleavings. Large language models can synthesize executable Rust tests, but their outputs often violate API preconditions, remain shallow, or reduce concurrency to accidental sequential traces. Conversely, model-based and systematic testing techniques provide semantic control but commonly require substantial handwritten code to turn abstract scenarios into executable tests. Authors: Kaiwen Zhang, Guanjun Liu.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Concurrent stateful library APIs expose behavior through evolving resource ownership, lifecycle states, and competing interleavings.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
Hackster.io7/23/2026
Recently

Armaan Gomes and Friends Deliver Playable Doom on a Whole New Platform: A Custom RISC-V CPU

MIT electrical engineering and computer science student Armaan Gomes has led a team to port id Software's Doom to a platform it has definitely never been played on before: a custom homebrew processor, based around the free and open source RISC-V instruction set architecture. "Two weeks ago we successfully ran (crawled) Doom on a CPU we built from scratch (and then posted a video that got a few million views)," Gomes explains of the project. "To be honest, I still can't believe it.

Why it matters

Read this for the engineering context in Developer Tools / Open Source: MIT electrical engineering and computer science student Armaan Gomes has led a team to port id Software's Doom to a platform it has definitely never been played on before: a custom homebrew processor, based around the free and open source RISC-V instruction set architecture.

Trusted source
Original
Developer Tools / Open Source
NVIDIA Technical Blog7/23/2026
Recently

Debugging Ray Tracing Applications Using NVIDIA OptiX Toolkit

NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU. Applications using OptiX can fail in ways... NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU.

Official source
Original
Developer Tools / Open Source
GitHub Blog7/23/2026
Recently

The case for a cooldown: Why Dependabot now waits before issuing version updates

A new default three-day cooldown delays version update pull requests so maintainers and security researchers can address findings in a release before it gets into your code. The post The case for a cooldown: Why Dependabot now waits before issuing version updates appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: A new default three-day cooldown delays version update pull requests so maintainers and security researchers can address findings in a release before it gets into your code.

Official sourceSupply chain securityDependabot
Original
Developer Tools / Open Source
CNCF Blog7/24/2026
Recently

OpenTelemetry has graduated… Now what?

In case you missed it: OpenTelemetry (OTel) has officially achieved CNCF graduated status! It now stands proudly alongside amazing open source projects such as Kubernetes and Prometheus, to name just a few. It's been a long journey, and we're very...

Why it matters

Read this for the official technical update in Developer Tools / Open Source: In case you missed it: OpenTelemetry (OTel) has officially achieved CNCF graduated status!

Official sourceBlog
Original

Archived section

Cloud / Infrastructure · 5

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
LWN.net7/24/2026
Recently

De Vlieger: The Fedora 45 sausage factory

Fedora contributor Simon de Vlieger has published a blog post with a walkthrough of how the project turns source code and packages into the final release that users install on their systems. It follows the a package from a packager's git push to a composed release: ISOs, cloud images, container images, and OSTree deployments. The walkthrough describes how the Fedora 'sausage' is created as of Fedora 45, things change all the time; I hope to have time to update this document every cycle or every few cycles of Fedora releases so there's both history and people can find up to date information.

Why it matters

Read this for the concrete reporting in Cloud / Infrastructure: Fedora contributor Simon de Vlieger has published a blog post with a walkthrough of how the project turns source code and packages into the final release that users install on their systems.

Trusted source
Original
Cloud / Infrastructure
AWS Architecture Blog7/22/2026
Recently

Building multi-Region resiliency for AWS CloudFormation custom resource deployment

AWS CloudFormation is the foundational tool of infrastructure-as-code for thousands of organizations running workloads on AWS. But as teams push the boundaries of what CloudFormation can do natively, custom resources have emerged as a powerful extension mechanism that unlocks a broad range of possibilities.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: AWS CloudFormation is the foundational tool of infrastructure-as-code for thousands of organizations running workloads on AWS.

Official sourceAWS CloudFormationResilience
Original
Cloud / Infrastructure
AWS Architecture Blog7/22/2026
Recently

Architecting offline-first generative AI applications for edge deployments using AWS services

4 trillion annually because of unplanned downtime. This downtime is often worsened by a lack of skills to detect and resolve issues quickly.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: 4 trillion annually because of unplanned downtime.

Official sourceAmazon BedrockAmazon SageMaker AI
Original
Cloud / Infrastructure
Cloudflare Blog7/24/2026
Recently

BGP ORIGIN attribute manipulation and its impact on the Internet

By doing in-depth testing, we found nearly 70% of BGP paths experience ORIGIN attribute rewrites by transit providers seeking traffic advantages. We examine the global impact of this practice and argue for deprecating ORIGIN in route selection.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: By doing in-depth testing, we found nearly 70% of BGP paths experience ORIGIN attribute rewrites by transit providers seeking traffic advantages.

Official sourceBetter InternetBGP
Original