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Artificial Intelligence / Machine Learning · 5

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Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/14/2026
Recently

ViHoRec: A Quality-Controlled Vietnamese Hotel Recommendation Dataset and Cold-Start Benchmark

Recommender-system research for Vietnamese remains limited by the absence of a public, well-documented hotel interaction resource. Building such a resource is challenging for three reasons: cross-platform hotel names must be reconciled before interactions are comparable; quality must be audited with reproducible metrics rather than ad hoc cleaning; and public release must preserve privacy while remaining benchmarkable under realistic cold-start conditions. com, Traveloka, and Ivivu. Authors: Minh Hoang Nguyen.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Recommender-system research for Vietnamese remains limited by the absence of a public, well-documented hotel interaction resource.

Primary paperarxivcs.IR
Original
Artificial Intelligence / Machine Learning
arXiv7/14/2026
Recently

Real-time fall detection based on vision for low-power edge platforms

Falling detection is vital for elderly care and intelligent surveillance; however, prevailing vision-based approaches predominantly frame it as static pose classification or discrete temporal pattern matching, fundamentally overlooking the instability dynamics of the human support system. This paper proposes a physics-informed falling detection framework that recasts falling as a stability-loss event in a coupled dynamical system. We introduce a novel dual-LTC architecture comprising a Center-of-Mass (CoM) subsystem and a Base-of-Support (BoS) subsystem, both instantiated as Liquid Time-Constant (LTC) neural networks to continuously model inertial trajectory evolution and ground-contact adjustment through adaptive time constants, Physical interpretability of falling motion. Authors: Wenjun Xia, Zhicheng Peng, Haopeng Li.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Falling detection is vital for elderly care and intelligent surveillance; however, prevailing vision-based approaches predominantly frame it as static pose classification or discrete temporal pattern matching, fundamentally overlooking the instability dynamics of the human support system.

Primary paperarxivq-bio.NC
Original
Artificial Intelligence / Machine Learning
arXiv7/13/2026
Recently

A Durability and Cross-Language Transfer Benchmark for a Validated Teaching-Feedback Classification Protocol

Institutions collect far more open-ended teaching-evaluation feedback than they read. A prior study introduced a validated protocol for classifying such comments by thematic category and sentiment, built from a documented annotation guide, an intra-annotator reliability measurement, stratified cross-validation, and a held-out evaluation on a Spanish institutional corpus with a frozen-encoder design. Two questions limit its reuse: whether a protocol fixed to 2019-era frozen embeddings stays competitive as representation methods advance, and whether it transfers to a second language. Authors: Esteban U. Vega Barajas.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Institutions collect far more open-ended teaching-evaluation feedback than they read.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
NVIDIA Technical Blog7/14/2026
Recently

Lessons From the Leaderboard: What 5,000+ Kagglers Taught Us About Improving AI Reasoning

The NVIDIA Nemotron Model Reasoning Challenge invited the Kaggle community to explore a focused question: What techniques can improve reasoning accuracy when... The NVIDIA Nemotron Model Reasoning Challenge invited the Kaggle community to explore a focused question: What techniques can improve reasoning accuracy when everyone starts from the same open model, benchmark, infrastructure and evaluation constraints? The response was massive.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: The NVIDIA Nemotron Model Reasoning Challenge invited the Kaggle community to explore a focused question: What techniques can improve reasoning accuracy when...

Official source
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Artificial Intelligence / Machine Learning
arXiv7/13/2026
Recently

Invariant Learning Dynamics of Transformers in Inductive Reasoning Tasks

We present a theoretical framework to explain the emergence of inductive reasoning abilities in Transformer language models. While previous works on Transformer learning dynamics have so far been mostly tied to specific tasks, we study a generalized class of inductive tasks that unifies several synthetic tasks known in the literature, including in-context n-grams and multi-hop reasoning. In this class, we theoretically prove that the training dynamics of attention models can be confined to a highly interpretable, low-dimensional invariant manifold. Authors: Tiberiu Musat, Tiago Pimentel, Nicholas Zucchet.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: We present a theoretical framework to explain the emergence of inductive reasoning abilities in Transformer language models.

Primary paperarxivcs.LG
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/14/2026
Recently

Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction

Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, where direct paper-to-repository comparison is prone to hallucination. However, constructing paper-specific rubrics requires substantial expert effort, limiting the scalability of benchmarks such as PaperBench. In this work, we present, to our knowledge, the first systematic meta-evaluation of LLM-generated rubrics for paper reproduction. Authors: Hanhua Hong, Yizhi Li, Jiaoyan Chen.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, where direct paper-to-repository comparison is prone to hallucination.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/14/2026
Recently

Knowledge- and Gradient-Guided Reinforcement Learning for Parametrized Action Markov Decision Processes

In this paper, we study Reinforcement Learning in Parametrized Action Markov Decision Processes (PAMDP), where each decision consists of a symbolic action and numerical parameters. In such settings Reinforcement Learning algorithms typically determine parameters with one-shot estimators, which makes their training sample inefficient., rules, safety constraints, or expert heuristics) is available, it is rarely directly used to increase the sample-efficiency of training Reinforcement Learning agents. Authors: Jonas Ehrhardt, René Heesch, Oliver Niggemann.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: In this paper, we study Reinforcement Learning in Parametrized Action Markov Decision Processes (PAMDP), where each decision consists of a symbolic action and numerical parameters.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/14/2026
Recently

A Multi-Agent System for Autonomous, Fine-Tuning-Free Clinical Symptom Detection: Development and Validation Study

Clinical notes contain many of the signs and symptoms that bring patients to care, yet this information rarely reaches structured fields. Existing extraction approaches either rely on context-insensitive rules that generate false positives or on supervised models that require substantial fine-tuning. We present Pythia, a multi-agent system that autonomously writes and optimizes extraction prompts for clinical concepts without manual prompt engineering or fine-tuning. Authors: Cameron Cagan, Pedram Fard, Jiazi Tian.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Clinical notes contain many of the signs and symptoms that bring patients to care, yet this information rarely reaches structured fields.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/14/2026
Recently

PalmClaw: A Native On-Device Agent Framework for Mobile Phones

Large Language Model (LLM) agents have moved beyond generating responses to executing multi-step tasks by calling tools, observing the results, and iteratively deciding the next action. Most agent systems run on desktops or servers, which support tool use and task automation. Mobile devices are also important agent environments because they are widely accessible and contain users' data, sensors, and daily-use applications. Authors: Hongru Cai, Yongqi Li, Ran Wei.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Large Language Model (LLM) agents have moved beyond generating responses to executing multi-step tasks by calling tools, observing the results, and iteratively deciding the next action.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/14/2026
Recently

Do AI Agents Know When a Task Is Simple? Toward Complexity-Aware Reasoning and Execution

Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they rarely ask how much effort a task actually requires. They often follow a maximum-context-first strategy--re-reading files and dependencies they have already seen--turning a one-line edit into a small code-base audit. We argue the missing capability is task-aware execution-scope estimation: judging a task's difficulty, the information it truly needs, and the shortest reliable path before committing budget. Authors: Junjie Yin, Xinyu Feng.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they rarely ask how much effort a task actually requires.

Primary paperarxivcs.AI
Original

Archived section

Research Papers · 5

Research Papers
arXiv7/14/2026
Recently

GraphPolaris: A System for Query, Analysis, and Visualization of Graph Databases

Graph databases are increasingly adopted as alternatives to tabular, aggregation-focused data models used in business intelligence (BI) systems such as Tableau, Power BI, and Looker. They capture complex relationships between entities, processes, and events, enabling analysis of information propagation in networks. As a result, graph analysis is central to applications such as fraud detection, social influence analysis, and supply chain resilience. Authors: Michael Behrisch, Sjoerd Vink, Leonardo Christino.

Why it matters

Read this for the paper's specific claim in Research Papers: Graph databases are increasingly adopted as alternatives to tabular, aggregation-focused data models used in business intelligence (BI) systems such as Tableau, Power BI, and Looker.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/14/2026
Recently

Sensing the properties of virtual objects without physical feedback

People who have interacted with simulated worlds and simulated objects in extended reality (XR) often have a sense that they can 'feel' the objects being simulated despite them not being physical. Our sense of touch is essential for how we 'feel' the physical world, however, there is an open question as to what it means to 'feel' virtual objects when interacting with them in immersive digital environments. In prior research, we have reported that participants often describe a subjective experience of 'feeling' the properties of simulated molecular objects while using interactive molecular dynamics in extended reality (iMD-XR), a field-based interaction paradigm for manipulating real-time simulations of molecular objects without haptic feedback. Authors: Rhoslyn Roebuck Williams, Harry J. Stroud, Luis E. Toledo.

Why it matters

Read this for the paper's specific claim in Research Papers: People who have interacted with simulated worlds and simulated objects in extended reality (XR) often have a sense that they can 'feel' the objects being simulated despite them not being physical.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/13/2026
Recently

Supporting Reflection in LLM-based Exploratory Search

Large Language Models (LLMs) can make exploratory search more efficient but may undermine the reflection and iterative sensemaking needed in unfamiliar domains. Existing LLM tools often prioritize rapid answers over supporting users in tracking how their understanding evolves and how well their strategies align with their goals. We present TrailLM, a system that helps users reconstruct and revisit their exploration paths to support reflection and metacognitive engagement during information seeking. Authors: Giulia Di Fede, Salvatore Andolina.

Why it matters

Read this for the paper's specific claim in Research Papers: Large Language Models (LLMs) can make exploratory search more efficient but may undermine the reflection and iterative sensemaking needed in unfamiliar domains.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/14/2026
Recently

CD-MED: Cross-Domain Multimodal Emotion Descriptor for Visual Comparison of Digital Objects

Digital objects express emotions through different modalities. For example, a movie may include visual scenes, audio, dialogue, and facial expressions, while a song may contain melody, rhythm, lyrics, and vocal tone. Because existing emotion recognition models are usually modality-specific, it is difficult to compare such objects directly. Authors: Elnara Kadyrgali, Muragul Muratbekova, Pakizar Shamoi.

Why it matters

Read this for the paper's specific claim in Research Papers: Digital objects express emotions through different modalities.

Primary paperarxivcs.HC
Original
Research Papers
Microsoft Research Blog7/13/2026
Recently

Verifying Rust cryptography in SymCrypt, from standards to code

Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.

Why it matters

Read this for the official technical update in Research Papers: Cryptographic code supports vital protections in modern computing systems.

Official sourceResearch Blog
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/14/2026
Recently

ChunkFlow: Towards Continuity-Consistent Chunked Policy Learning

Vision-language action (VLA) models increasingly adopt chunked action heads to satisfy real-time constraints; however, this introduces boundary jitter: overlapping regions between consecutive chunks often yield inconsistent predictions, degrading temporal coherence and the task success rate. Existing methods, such as inference-time blending, merely reweight mismatched proposals without correcting underlying errors, leading to residual accumulation under biased or noisy histories. We propose ChunkFlow, a seam-aware training-and-execution framework for chunked policies that aligns chunk structure with boundary execution. Authors: Zhao Yang, Yinan Shi, Mingyuan Yao.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Vision-language action (VLA) models increasingly adopt chunked action heads to satisfy real-time constraints; however, this introduces boundary jitter: overlapping regions between consecutive chunks often yield inconsistent predictions, degrading temporal coherence and the task success rate.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv7/14/2026
Recently

UR-VC: Unsupervised Robotic Value Correction for Time-Derived Progress Proxies

Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect task completion, making the quality of these signals critical. Since such dense labels are rarely available at scale, normalized time within a demonstration is often used as a scalable substitute: later frames are treated as higher progress. However, this time-derived label is only a noisy proxy for physical task progress. Authors: Lirui Zhao, Modi Shi, Li Chen.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect task completion, making the quality of these signals critical.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv7/14/2026
Recently

DenseReward: Dense Reward Learning via Failure Synthesis for Robotic Manipulation

Reinforcement learning holds great promise for improving robot policies beyond the limits of imitation learning. However, its practical adoption remains bottlenecked by the lack of reliable vision-language reward models that provide dense and informative feedback. Two key challenges remain: acquiring diverse failure data at scale and obtaining fine-grained reward signals beyond sparse trajectory-level success labels. Authors: Yu Fang, Wanxi Dong, Jiaqi Liu.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Reinforcement learning holds great promise for improving robot policies beyond the limits of imitation learning.

Primary paperarxivcs.RO
Original
Embedded Systems
Hackster.io7/14/2026
Recently

This DIY E Ink Display Brings Local Bird Sightings to Your Wall

Birdwatching involves a lot more than a pair of binoculars these days. Apps can identify birds by sight or sound, online databases track sightings from around the world, and AI can help classify species. But despite all of that technology, there is still something special about the traditional illustrated field guides used by generations of bird enthusiasts.

Why it matters

Read this for the engineering context in Embedded Systems: Birdwatching involves a lot more than a pair of binoculars these days.

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Original
Embedded Systems
Hackster.io7/13/2026
Recently

Finally, True Privacy for Voice Assistants

Speaking is one of the fastest ways to communicate with a computer, but it comes with an obvious drawback: everyone nearby can hear what you are saying. Whether you are dictating notes in a coffee shop, issuing commands on a train, or asking an AI assistant sensitive questions at work, privacy disappears the moment you open your mouth. Researchers have explored everything from lip reading to electromyography (EMG) in an attempt to solve that problem.

Why it matters

Read this for the engineering context in Embedded Systems: Speaking is one of the fastest ways to communicate with a computer, but it comes with an obvious drawback: everyone nearby can hear what you are saying.

Trusted source
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Archived section

Computer Systems · 5

Computer Systems
arXiv7/14/2026
Recently

Proceedings of HLPP 2026: 19th International Symposium on High-Level Parallel Programming and Applications

This volume contains the ten peer-reviewed papers presented at HLPP 2026, the 19th International Symposium on High-Level Parallel Programming and Applications, held on 9-10 July 2026 at the Institut Henri Poincare in Paris, France. The symposium covers high-level approaches to parallel programming: programming models, languages, libraries, algorithmic skeletons, compilers, and runtime systems for multi-core, GPU, and distributed platforms. The 2026 edition extended this scope towards artificial intelligence, with new topics on the parallel programming and performance of AI systems and on AI-assisted generation of parallel code, and opened with a dedicated session on parallelism and AI. Authors: Chong Li, Corinne Ancourt, Gaétan Hains.

Why it matters

Read this for the paper's specific claim in Computer Systems: This volume contains the ten peer-reviewed papers presented at HLPP 2026, the 19th International Symposium on High-Level Parallel Programming and Applications, held on 9-10 July 2026 at the Institut Henri Poincare in Paris, France.

Primary paperarxivcs.DC
Original
Computer Systems
arXiv7/13/2026
Recently

Can LLMs Perform Deep Technical Comprehension of Computer Architecture Papers?

Can large language models perform deep technical comprehension of computer architecture papers -- not summarization, but structured critique that names the core mechanism, surfaces buried assumptions, and connects a contribution beyond its own scope? We study Gauntlet, an open-source pipeline that analyzes a paper through five independent expert-persona reviewers and an adversarial synthesis stage. On 20 ISCA 2025 and HPCA 2026 papers, ten researchers each wrote their own analyses and then judged, for papers other than their own, the human analysis against Gauntlet's. Authors: Nishant Aggarwal, Ayushi Dubal, Sreeraj Kannakarankodi.

Why it matters

Read this for the paper's specific claim in Computer Systems: Can large language models perform deep technical comprehension of computer architecture papers -- not summarization, but structured critique that names the core mechanism, surfaces buried assumptions, and connects a contribution beyond its own scope?

Primary paperarxivcs.CY
Original
Computer Systems
arXiv7/13/2026
Recently

HiFi-LLP: High-Fidelity, Low-Cost Latency Predictors with Confidence for Robust HW-NAS

With deep neural networks (DNNs) increasingly deployed on edge devices, hardware (HW)-aware optimization techniques--such as HW-aware compression and HW-aware neural architecture search (HW-NAS)--have become essential. These methods rely on real feedback from the target hardware to tailor DNN architectures for efficient deployment. While the search can be parallelized, latency measurements via hardware-in-the-loop (HIL) remain a bottleneck due to their sequential nature. Authors: Shambhavi Balamuthu Sampath, Behzad Shomali, Nael Fasfous.

Why it matters

Read this for the paper's specific claim in Computer Systems: With deep neural networks (DNNs) increasingly deployed on edge devices, hardware (HW)-aware optimization techniques--such as HW-aware compression and HW-aware neural architecture search (HW-NAS)--have become essential.

Primary paperarxivcs.LG
Original
Computer Systems
CNCF Blog7/14/2026
Recently

Is a Pod the right deployment unit for an AI agent?

When we first started building kagent, we didn't run every agent in its own Kubernetes Pod, Service, and ServiceAccount. Instead, agents were simply executed inside the kagent runtime. It was the simplest architecture possible: one runtime...

Why it matters

Read this for the official technical update in Computer Systems: When we first started building kagent, we didn't run every agent in its own Kubernetes Pod, Service, and ServiceAccount.

Official sourceBlog
Original
Computer Systems
Kubernetes Blog7/14/2026
Recently

Building a Custom Metrics Exporter for Kubernetes

Kubernetes ships with built-in awareness of CPU and memory, but most real-world scaling decisions depend on signals that live entirely outside that narrow window: how many messages are waiting in a queue, how long the last batch job took, how many active WebSocket connections a pod is holding. When the built-in metrics are not enough, a metrics exporter bridges that gap. This post walks through writing one from scratch, packaging it as a container, and wiring it into a cluster so that Prometheus — and ultimately the HorizontalPodAutoscaler — can consume it.

Why it matters

Read this for the official technical update in Computer Systems: Kubernetes ships with built-in awareness of CPU and memory, but most real-world scaling decisions depend on signals that live entirely outside that narrow window: how many messages are waiting in a queue, how long the last batch job took, how many active WebSocket connections a pod is holding.

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Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv7/14/2026
Recently

MetaInfer: A Knowledge Only LLM Inference Engine Generator SKILL Toolbox

As LLM technology advances, the space of model families, compute hardware, quantization schemes, parallelization strategies, and specialized optimization kernels continues to expand, sharply increasing the code complexity and maintenance cost of general-purpose inference frameworks. Conventional software engineering uses multiple layers of abstraction to support diverse application scenarios, but these abstractions also increase system complexity and may introduce additional performance overhead. This paper presents metainfer, an 'LLM-as-Compiler' approach in which users specify only the runtime constraints of an inference program. Authors: Zhenwen Miao, Honglin Wang, Mingheng Mi.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: As LLM technology advances, the space of model families, compute hardware, quantization schemes, parallelization strategies, and specialized optimization kernels continues to expand, sharply increasing the code complexity and maintenance cost of general-purpose inference frameworks.

Primary paperarxivcs.MA
Original
Developer Tools / Open Source
arXiv7/14/2026
Recently

Deep4ge: DNN Training Trajectories for Fault Detection and Diagnosis

Deep learning systems often fail due to subtle implementation faults that alter training behavior. Recent work has studied how to detect and diagnose such failures from changes observed across training epochs. However, the software engineering community still lacks a public dataset of per-epoch training runs with documented fault history, feature extraction details, and clear reuse support for fault detection and diagnosis tasks. Authors: Sigma Jahan.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Deep learning systems often fail due to subtle implementation faults that alter training behavior.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
arXiv7/14/2026
Recently

Toward Localizing and Repairing Bias in Transformer Attention Heads

Transformer language models are increasingly used as software components, yet biased outputs remain difficult to localize and repair inside the model. Existing fairness testing and repair methods largely operate at the input-output or retraining level, while recent work suggests that bias-related behavior can concentrate in a small set of attention heads. This paper studies whether attention heads can be localized and repaired through a targeted inference-time intervention. Authors: Sigma Jahan.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Transformer language models are increasingly used as software components, yet biased outputs remain difficult to localize and repair inside the model.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
Vercel Blog7/13/2026
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Chat SDK adds X adapter support

X adapter Teams can build bots that reply to public mentions and hold direct message conversations through the X API v2 and the. X Activity API Likes are the only supported reaction, and responses post once on completion since X has no native streaming.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: X adapter Teams can build bots that reply to public mentions and hold direct message conversations through the X API v2 and the.

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Developer Tools / Open Source
Vercel Blog7/12/2026
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Manage Vercel Flags targeting rules from the CLI

You can now manage targeting rules for through the. Vercel FlagsVercel CLIvercel flags rules Rules you create from the CLI use the same model as the dashboard. Conditions can target or reusable, outcomes can serve a single variant, a weighted split, or a progressive rollout, and rules evaluate top to bottom.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: You can now manage targeting rules for through the.

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Archived section

Cloud / Infrastructure · 5

Cloud / Infrastructure
Netflix Tech Blog7/13/2026
Recently

Building Service Topology at Scale: Architecture, Challenges, and Lessons Learned

By Parth Jain, Rakesh Sukumar, Yingwu Zhao, Renzo Sanchez-Silva & Nathan Fisher A deep dive into the engineering challenges of building a real-time service dependency map at Netflix scale: from streaming architectures and distributed aggregation pipelines to time-travel queries and the methodology that made it work. Introduction In our first post, we introduced the problem: engineers at Netflix needed a unified, real-time view of service dependencies to troubleshoot faster, understand blast radius, and navigate our distributed architecture. We described our multi-source approach, combining eBPF network flows, IPC metrics, and distributed tracing into physically separate graph layers that can be queried independently or merged into a comprehensive view.

Why it matters

Read this for the engineering context in Cloud / Infrastructure: By Parth Jain, Rakesh Sukumar, Yingwu Zhao, Renzo Sanchez-Silva & Nathan Fisher A deep dive into the engineering challenges of building a real-time service dependency map at Netflix scale: from streaming architectures and distributed aggregation pipelines to time-travel queries and the methodology that made it work.

Trusted sourcebackend-developmentdistributed-systems
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Cloud / Infrastructure
AWS Architecture Blog7/14/2026
Recently

How Mapfre USA modernized fraud claims with Amazon EMR Serverless

Insurance fraud remains a significant challenge for the insurance industry because fraudulent claims can increase loss costs, reduce trust, and consume investigation capacity that could otherwise be focused on serving customers. Traditional fraud detection approaches typically rely on rules-based controls, manual investigation triggers, historical claim patterns, and structured-data-only analysis.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Insurance fraud remains a significant challenge for the insurance industry because fraudulent claims can increase loss costs, reduce trust, and consume investigation capacity that could otherwise be focused on serving customers.

Official sourceAmazon EMRAmazon Managed Workflows for Apache Airflow (Amazon MWAA)
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Cloud / Infrastructure
Kubernetes Blog7/13/2026
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Kubernetes Dashboard to Headlamp: A Step-by-Step Guide

1. Before you start: know what is changing Kubernetes Dashboard and Headlamp both show what is running in a cluster, but they work differently. When Headlamp runs on the desktop, it uses your existing kubeconfig to connect to one or more clusters and can be extended with plugins.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Before you start: know what is changing Kubernetes Dashboard and Headlamp both show what is running in a cluster, but they work differently.

Official source
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Cloud / Infrastructure
AWS Blog7/13/2026
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AWS Weekly Roundup: AWS Builder Center at 1 year, Network Scanning in Security Hub, Loom for AWS, and more (July 13, 2026)

AWS Builder Center turned one year old last week. Launched on July 9, 2025, the platform has grown from a community hub with Wishlist voting, community profiles, and a toolbox into a full ecosystem with sandbox environments, workshops, Spaces, and a Builders' Library.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: AWS Builder Center turned one year old last week.

Official sourceAmazon AuroraAmazon Elastic Container Service
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Cloud / Infrastructure
AWS Architecture Blog7/13/2026
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Unlocking the future of video data: March Networks cloud storage on AWS

Enterprise video surveillance is operating at an unprecedented scale as organizations across retail, banking, quick-service restaurants (QSR), convenience stores, and transportation networks generate petabytes of video data across thousands of distributed locations.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Enterprise video surveillance is operating at an unprecedented scale as organizations across retail, banking, quick-service restaurants (QSR), convenience stores, and transportation networks generate petabytes of video data across thousands of distributed locations.

Official sourceAmazon Simple Storage Service (S3)Customer Solutions
Original