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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

Cloud / Infrastructure · 5

Archived section

Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/16/2026
Recently

Self-Evolving Human-Centered Framework for Explainable Depression Symptom Annotation

Annotation quality is a major bottleneck in building reliable and explainable artificial intelligence (XAI) systems for mental health research. In depression-related datasets, labels are often assigned without structured evidence, symptom-level justification, or traceable alignment with the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR), limiting both transparency and downstream model interpretability. We propose a self-evolving, expert-in-the-loop annotation framework for Major Depressive Disorder (MDD) that combines large language model (LLM)-assisted labeling with expert verification. Authors: Hoang-Loc Cao, Van Pham, Truong Thanh Hung Nguyen.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Annotation quality is a major bottleneck in building reliable and explainable artificial intelligence (XAI) systems for mental health research.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv7/16/2026
Recently

teLLMe Why (Ain't Nothing but a Jam): Exploratory Causal Analysis of Urban Driving Data

Traffic agencies now have access to large volumes of video-derived data for studying safety and congestion. " difficult to answer. We present teLLMe, a system for exploratory causal analysis of urban driving datasets. Authors: Qiwei Li, Jorge Ortiz.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Traffic agencies now have access to large volumes of video-derived data for studying safety and congestion.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv7/16/2026
Recently

HoloGeo: Mitigating Landmark Bias in Geo-localization via Evidence-Driven Reasoning

Recent advances in Vision-Language Models (VLMs) have significantly improved image geo-localization, yet existing models remain susceptible to landmark bias, causing them to overlook geographical cues or form spurious correlations, ultimately resulting in inaccurate localization. To systematically investigate this issue, we first design two quantitative metrics, Bias Intensity (BI) and Bias Harmfulness (BH), to characterize the impact of landmarks exerted on model reasoning, and establish a comprehensive benchmark, LandmarkBias-3K. To mitigate landmark bias, we further propose an evidence-driven reasoning framework, HoloGeo, to improve the reliability of geo-localization. Authors: Pengcheng Zhou, Xuanyu Liu, Yanchen Yin.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Recent advances in Vision-Language Models (VLMs) have significantly improved image geo-localization, yet existing models remain susceptible to landmark bias, causing them to overlook geographical cues or form spurious correlations, ultimately resulting in inaccurate localization.

Primary paperarxivcs.CV
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
arXiv7/15/2026
Recently

Earthquaker-AI: A Retrieval-Augmented Generation Framework with Rubric-Based Assessment for Primary School Earthquake Education

This paper presents Earthquaker-AI, a hybrid educational framework building upon a previously implemented educational robotics project by integrating a conversational AI assistant based on Retrieval-Augmented Generation. It aims to enhance earthquake preparedness and conscious action among primary-school students. The system extends the award-winning STEM project Earthquaker moving from mechanical simulation with Lego WeDo2 to cognitive and metacognitive processing. Authors: Xanthi Kokkinou, Chaido Mizeli, Nafsika Koulaxidou.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: presents Earthquaker-AI, a hybrid educational framework building upon a previously implemented educational robotics project by integrating a conversational AI assistant based on Retrieval-Augmented Generation.

Primary paperarxivcs.AI
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/16/2026
Recently

Setup Complete, Now You Are Compromised: Weaponizing Setup Instructions Against AI Coding Agents

AI coding agents set up projects by reading documentation and installing the dependencies it lists, without verifying their names, sources, or known vulnerabilities. By editing only a README, requirements file, or Makefile, an attacker can redirect the agent to an untrusted registry, a known-vulnerable version, or a wrong-but-plausible name: documentation becomes a vector for code execution. We present the first systematic evaluation of package-install-time supply-chain attacks delivered through ordinary project-setup documentation across production coding-agent harnesses, probing frontier models on twelve scenarios in five attack classes, grounded in documented incidents. Authors: Aadesh Bagmar, Pushkar Saraf.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: AI coding agents set up projects by reading documentation and installing the dependencies it lists, without verifying their names, sources, or known vulnerabilities.

Primary paperarxivcs.CR
Original
Automation / Agentic Systems
arXiv7/16/2026
Recently

SciDiagramEdit: Learning to Edit Scientific Diagrams from Paper Revisions

Editing the figures in a research paper is a routine and time-consuming part of everyday research practice: authors relabel components, rearrange panels, and restyle visuals as they revise their manuscripts. Automating this editing workflow under a natural-language instruction, however, is challenging, because a scientific figure is a dense infographic in which heterogeneous visual elements such as schematics, plots, photos, captions, and arrows are composed under a tight visual grammar to advance a specific argument. To address this, we present SciDiagramEdit, a benchmark and skill-evolution framework that learns from natural paper revisions and operates on the figure's editable vector source, where users can inspect and co-edit individual primitives alongside the agent. Authors: Yasheng Sun, Zezi Zeng, Yifan Yang.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Editing the figures in a research paper is a routine and time-consuming part of everyday research practice: authors relabel components, rearrange panels, and restyle visuals as they revise their manuscripts.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/16/2026
Recently

ARMOR++: Agentic Orchestration of a Multi-Domain Primitive Set for Transferable Attacks on Deepfake Detectors

The reliability of deepfake detectors frequently degrades under black-box adversarial transfer, as these models often rely on fragile, architecture-dependent forensic cues. Existing transfer attacks often lack semantic awareness and struggle to maintain effectiveness under strict no-query constraints, particularly when perturbations are transferred from convolutional surrogates to transformer-based targets. To address these limitations, this paper introduces ARMOR++, a robust multi-agent framework designed for high-transferability deepfake evasion. Authors: Christos Korgialas, Gabriel Lee Jun Rong, Dion Jia Xu Ho.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: The reliability of deepfake detectors frequently degrades under black-box adversarial transfer, as these models often rely on fragile, architecture-dependent forensic cues.

Primary paperarxivcs.CV
Original
Automation / Agentic Systems
arXiv7/16/2026
Recently

AutoSynthesis: An agentic system for automated meta-analysis

Evidence synthesis is crucial for turning primary research into reliable knowledge for science, medicine, education, and policy. Yet, quantitative evidence synthesis remains largely manual and difficult to scale. Here, we introduce AutoSynthesis, an end-to-end multi-agent system for automated meta-analysis. Authors: Moein Taherinezhad, Sebastian Maier, Gerardo Vitagliano.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Evidence synthesis is crucial for turning primary research into reliable knowledge for science, medicine, education, and policy.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv7/16/2026
Recently

Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents

Security-agent evaluations commonly measure peak offensive capability under generous inference budgets, emphasizing vulnerability discovery, exploit development, penetration testing, and CTF completion. Such measurements are useful but incomplete: in operational security, every reasoning step, tool call, telemetry query, and enrichment request consumes budget. We evaluate language-model security agents through this cost-success lens on offensive Cybench challenges and defensive Splunk BOTS v1 investigation challenges. Authors: Paul Kassianik, Blaine Nelson, Yaron Singer.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Security-agent evaluations commonly measure peak offensive capability under generous inference budgets, emphasizing vulnerability discovery, exploit development, penetration testing, and CTF completion.

Primary paperarxivcs.CR
Original

Archived section

Research Papers · 4

Research Papers
arXiv7/15/2026
Recently

HORCRUX: A Complete PQC RISC-V eXtension Architecture

This work presents a compact RISC-V extension for Post-Quantum Cryptography (PQC) called HORCRUX, which provides a unified Instruction-Set Extension (ISE) supporting all NIST-approved PQC algorithms. HORCRUX addresses the difficult trade-off between crypto-agility, high performance, and low resource consumption in constrained environments, a balance typically missing in hardware extensions that focus on limited PQC subsets. By targeting shared kernels across ML-KEM, MLDSA, SLH-DSA, HQC, and Falcon, the extension introduces new RISC-V instructions executed by a resource-efficient, tightly coupled coprocessor. Authors: Alessandra Dolmeta, Valeria Piscopo, Michael Hutter.

Why it matters

Read this for the paper's specific claim in Research Papers: This work presents a compact RISC-V extension for Post-Quantum Cryptography (PQC) called HORCRUX, which provides a unified Instruction-Set Extension (ISE) supporting all NIST-approved PQC algorithms.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/16/2026
Recently

DataShield: Uncovering Risky Fine-Tuning Data Across LLMs Through Consensus Subspace Alignment

Fine-tuning large language models (LLMs) on domain-specific datasets has become a standard paradigm for adapting LLMs to specialized applications. However, recent work has shown that even fine-tuning on benign task-specific data can substantially weaken the safety capabilities of LLMs. While existing efforts have made progress in identifying data responsible for safety degradation, they usually rely on a single mean vector computed over a specific model with its tokenizer to represent the safety direction, which limits both the effectiveness and transferability of their risk assessment measures. Authors: Zefeng Wu, Weiwei Qi, Jielong Chen.

Why it matters

Read this for the paper's specific claim in Research Papers: Fine-tuning large language models (LLMs) on domain-specific datasets has become a standard paradigm for adapting LLMs to specialized applications.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/16/2026
Recently

Automated Template-free Synthesis of Instruction-Centric Leakage Contracts for Black-Box CPUs

Side-channel attacks pose a significant security threat for modern computing platforms, because they exploit subtle discrepancies in CPU behaviors to leak sensitive information. To model the information leaked by a CPU via microarchitectural side-channels, recent work proposed leakage contracts: an ISA-level security abstraction that provides the foundations for secure CPU programming. Unfortunately, due to the complexity of current microarchitectures, devising a leakage contract for a CPU requires extensive manual effort and thus modern CPUs lack dedicated leakage contracts. Authors: Elvira Moreno, Tiziano Marinaro, Ryan Williams.

Why it matters

Read this for the paper's specific claim in Research Papers: Side-channel attacks pose a significant security threat for modern computing platforms, because they exploit subtle discrepancies in CPU behaviors to leak sensitive information.

Primary paperarxivcs.CR
Original
Research Papers
Apple Machine Learning Research7/15/2026
Recently

Doubly Sub-linear Interactive Proofs of Proximity

We study doubly sub-linear interactive proofs of proximity (dsIPPs): proofs that are ultra-fast to generate, and can be used to prove approximate assertions about a huge input. Proof generation is ultra-fast in the sense that it only requires reading a small (sub-linear) portion of the input. Approximate verification of the proof is even faster (reading an even smaller portion of the input).

Why it matters

Read this for the official technical update in Research Papers: We study doubly sub-linear interactive proofs of proximity (dsIPPs): proofs that are ultra-fast to generate, and can be used to prove approximate assertions about a huge input.

Official source
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/16/2026
Recently

Assessing Physical Frailty and Fall-Risk Indicators with Social Robots: An in situ Evaluation with Older Adults

Frailty assessments are crucial to evaluate the risk of adverse events and the health and social care needs of older adults, yet their administration remains resource-intensive and typically relies on coarse clinical outcomes, such as task completion times, which may overlook biomechanical indicators of functional decline. To address this, we present a robotic framework that guides older adults through standardised frailty and fall-risk tests while capturing clinical scores and additional frailty-related metrics, offering a deeper insight into a user's condition. The system uses a Behaviour Tree architecture that coordinates perception, decision-making, interaction, and measurement modules. Authors: Aniol Civit, Antonio Andriella, Alba Martínez.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Frailty assessments are crucial to evaluate the risk of adverse events and the health and social care needs of older adults, yet their administration remains resource-intensive and typically relies on coarse clinical outcomes, such as task completion times, which may overlook biomechanical indicators of functional decline.

Primary paperarxivcs.RO
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
Hackaday7/18/2026
Recently

Spidery Drone Goes Near-invisible By Spinning Really, Really Fast

Researchers demonstrate that something interesting happens when a small drone with a spindly airframe spins at a high speed: it very nearly turns invisible.

Why it matters

Read this for the engineering context in Embedded Systems: Researchers demonstrate that something interesting happens when a small drone with a spindly airframe spins at a high speed: it very nearly turns invisible.

Trusted sourcedrone hacksaircraft
Original
Embedded Systems
Hackaday7/17/2026
Recently

Wireless LCD Streaming for the ANENG AN870 Multimeter

Having the information shown on the display of a digital multimeter also recorded off-screen can be incredibly useful, but unless the device exposes something like SCPI on a network interface, …read more

Why it matters

Read this for the engineering context in Embedded Systems: Having the information shown on the display of a digital multimeter also recorded off-screen can be incredibly useful, but unless the device exposes something like SCPI on a network interface, …read more

Trusted sourceReverse EngineeringTool Hacks
Original
Embedded Systems
Raspberry Pi News7/15/2026
Recently

Run Ultralytics YOLO on Raspberry Pi with OpenVINO

A practical guide to deploying Ultralytics YOLO computer vision models on Raspberry Pi with OpenVINO. The post Run Ultralytics YOLO on Raspberry Pi with OpenVINO appeared first on Raspberry Pi.

Why it matters

Read this for the official technical update in Embedded Systems: A practical guide to deploying Ultralytics YOLO computer vision models on Raspberry Pi with OpenVINO.

Official sourceRaspberry Pi AIAI
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
arXiv7/16/2026
Recently

Campaign Diagrams: Visualizing the March Through the Phases of a Workload

We present campaign diagrams, a visualization technique for phase-level analysis of resource utilization and bottlenecks in modern workloads. Existing tools have a trade-off: rooflines aggregate a workload into a single point and lose all notion of time, while profilers and traces expose fine-grained events but obscure what bounds performance. Instead, a campaign diagram depicts compute throughput and memory bandwidth utilization, compute and memory traffic volume, and latency in a single figure. Authors: Toluwanimi O. Odemuyiwa, John D. Owens, Michael Pellauer.

Why it matters

Read this for the paper's specific claim in Computer Systems: We present campaign diagrams, a visualization technique for phase-level analysis of resource utilization and bottlenecks in modern workloads.

Primary paperarxivcs.PF
Original
Computer Systems
arXiv7/16/2026
Recently

Don't Predict, Prioritize: Rethinking GPU Reliability Assessment

The reliability of Graphics Processing Units (GPUs) is a criticalbottleneck for modern large-scale AI infrastructure, where a sin-gle node failure can disrupt synchronous training jobs and causesignificant financial losses. Through an in-depth analysis of telemetry data from a productioncluster, we find that major GPU failures, including Double Bit Er-rors (DBEs) and GPU Lost events, exhibit strong stochasticity andlow signal-to-noise ratios in time-series telemetry, which makesconventional time-based prediction ineffective. This insight motivates a paradigm shift: instead of attempting topredict the absolute timing of a failure, we propose a more robustapproach focused on ranking nodes by their relative failure risk. Authors: Difeng Ma, Changhua Pei, Yuanwei Lu.

Why it matters

Read this for the paper's specific claim in Computer Systems: The reliability of Graphics Processing Units (GPUs) is a criticalbottleneck for modern large-scale AI infrastructure, where a sin-gle node failure can disrupt synchronous training jobs and causesignificant financial losses.

Primary paperarxivcs.DC
Original
Computer Systems
AWS Architecture Blog7/16/2026
Recently

Prioritize your AWS Health alerts using AWS User Notifications

If you run critical workloads on AWS, such as a contact center on Amazon Connect Customer, database workloads on Amazon Relational Database Service (Amazon RDS), or hybrid connectivity through AWS Direct Connect, service health events demand your attention. But not all events are equal.

Why it matters

Read this for the official technical update in Computer Systems: If you run critical workloads on AWS, such as a contact center on Amazon Connect Customer, database workloads on Amazon Relational Database Service (Amazon RDS), or hybrid connectivity through AWS Direct Connect, service health events demand your attention.

Official sourceAWS HealthAWS User Notifications
Original
Computer Systems
AWS Compute Blog7/17/2026
Recently

Introducing self-managed Amazon S3 buckets for AWS Lambda function code

If you manage Lambda functions at scale, you've likely hit the 75 GB code storage limit or explained to your security team why deployment artifacts live in an S3 bucket you don't control. Today, we're announcing self-managed Amazon S3 buckets for AWS Lambda deployment packages.

Why it matters

Read this for the official technical update in Computer Systems: If you manage Lambda functions at scale, you've likely hit the 75 GB code storage limit or explained to your security team why deployment artifacts live in an S3 bucket you don't control.

Official sourceAmazon Simple Storage Service (S3)AWS Lambda
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv7/16/2026
Recently

Navigating the Socio-Technical Complexity Challenge in Quantum Software Ecosystems

Quantum computing environments are composed of heterogeneous layers spanning hardware, software development kits, and applications. Practitioners curating these environments face a fragmented and rapidly evolving landscape with few principled guides for navigation. This paper presents a framework for evaluating quantum computing environment choices through a socio-technical lens, developed using Design Science Research methodology. Authors: Ronja Heikkinen, Santiago Núñez-Corrales, Vlad Stirbu.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Quantum computing environments are composed of heterogeneous layers spanning hardware, software development kits, and applications.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
arXiv7/16/2026
Recently

MM-IssueLoc: A Controlled Benchmark for Evaluating Visual Evidence in Multimodal Repository-Level Issue Localization

Real repository issues routinely include visual evidence such as screenshots, error dialogs, rendered UI states, and logs, yet repository-level issue localization is evaluated mostly as a text-only task. Existing multimodal SE benchmarks evaluate end-to-end repair, entangling localization with patch synthesis and obscuring whether visual input helped, hurt, or was ignored. We introduce MM-IssueLoc, a controlled benchmark and evaluation protocol for repository-level localization with visual evidence. Authors: Shaoxiong Zhan, Shi Hu, Boyu Feng.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Real repository issues routinely include visual evidence such as screenshots, error dialogs, rendered UI states, and logs, yet repository-level issue localization is evaluated mostly as a text-only task.

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
Developer Tools / Open Source
Vercel Blog7/16/2026
Recently

Runtime logs now show cache reasons

Runtime logs now show a Cache Reason explaining why a request wasn't a fresh cache hit, for example a time-based or tag-based revalidation. Use cache reasons to debug misses and improve your hit rate. Cache reasons appear for any response the CDN can cache, including ISR, Partial Prerendering, and functions that set a header with directives like.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Runtime logs now show a Cache Reason explaining why a request wasn't a fresh cache hit, for example a time-based or tag-based revalidation.

Official source
Original
Developer Tools / Open Source
GitHub Blog7/15/2026
Recently

GitHub for Beginners: Your roadmap to mastering the GitHub essentials

New to GitHub? This beginner's guide explains version control, repositories, and pull requests—plus everything else you need to start working confidently on GitHub. The post GitHub for Beginners: Your roadmap to mastering the GitHub essentials appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: This beginner's guide explains version control, repositories, and pull requests—plus everything else you need to start working confidently on GitHub.

Official sourceDeveloper skillsGitHub
Original

Archived section

Cloud / Infrastructure · 5

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
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
Cloud / Infrastructure
CNCF Blog7/16/2026
Recently

Running a self-hosted LLM in Kubernetes with vLLM

Running large language model (LLM) workloads in-house is one of several patterns teams adopt alongside managed API services. Managed API services are convenient and well suited to many workloads. Self-hosting is a complementary option that some...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Running large language model (LLM) workloads in-house is one of several patterns teams adopt alongside managed API services.

Official sourceBlog
Original
Cloud / Infrastructure
AWS Architecture Blog7/15/2026
Recently

How bitdrift scaled to 121 million concurrent gRPC connections on Amazon CloudFront for live telemetry sporting events

When 121 million mobile devices establish persistent gRPC connections to your origin infrastructure within seconds of a live broadcast, the routing policy behind your DNS records matters far more than it does at normal traffic levels.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: When 121 million mobile devices establish persistent gRPC connections to your origin infrastructure within seconds of a live broadcast, the routing policy behind your DNS records matters far more than it does at normal traffic levels.

Official sourceAmazon CloudFrontNetworking & Content Delivery
Original
Cloud / Infrastructure
Microsoft Azure Blog7/15/2026
Recently

Azure Databricks delivers proven business value

Microsoft Azure Databricks delivers the first-party advantage of Databricks on Microsoft—and for customers, that advantage shows up as real, measurable value. It is the same Databricks platform your teams already know, co-engineered with Microsoft and delivered as a native Azure service, so it fits naturally into the Microsoft tools, identity, and governance your organization already runs. The post Azure Databricks delivers proven business value appeared first on Microsoft Azure Blog.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Microsoft Azure Databricks delivers the first-party advantage of Databricks on Microsoft—and for customers, that advantage shows up as real, measurable value.

Official sourceAI + machine learningAnalytics
Original