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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
arXiv7/1/2026
Recently

Measuring the Gap Between Human and LLM Research Ideas

LLMs are increasingly used to brainstorm research ideas, but existing evaluations mostly judge individual ideas by novelty, feasibility, or expert preference. We instead ask: how far are current LLM-generated ideas from human researchers? To characterize this gap, we build a large-scale evaluation framework for ideation from high-quality human research papers. Authors: Ziyu Chen, Yilun Zhao, Arman Cohan.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: LLMs are increasingly used to brainstorm research ideas, but existing evaluations mostly judge individual ideas by novelty, feasibility, or expert preference.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv6/29/2026
Recently

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms

We present APRIL-MedSeg, a YAML-driven modular framework for 2D medical image segmentation. It provides a unified and extensible ecosystem that decomposes segmentation networks into reusable components. Also, the framework integrates a broad spectrum of advanced paradigms, including semi-supervised learning, domain adaptation, knowledge distillation, weakly supervised learning, and text-guided segmentation as well as foundation model support. Authors: Juntao Jiang, Jinsheng Bai, Linxuan Fan.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: We present APRIL-MedSeg, a YAML-driven modular framework for 2D medical image segmentation.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
arXiv6/29/2026
Recently

Optimization Dynamics Imprint Semantic Specificity in Contrastive Embedding Norms

Contrastive embedding models trained with scale-invariant losses are typically paired with distance metrics like cosine similarity, effectively ignoring embedding magnitudes. However, surprisingly, empirical studies reveal that despite this, these "discarded" norms seem to correlate with semantic properties such as concept specificity, token frequency, and human uncertainty. In this work, we provide a formal theoretical framework explaining this phenomenon. Authors: Ziwei Su, Junyu Ren, Victor Veitch.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Contrastive embedding models trained with scale-invariant losses are typically paired with distance metrics like cosine similarity, effectively ignoring embedding magnitudes.

Primary paperarxivstat.ML
Original
Artificial Intelligence / Machine Learning
Meta Engineering7/1/2026
Recently

Meta's AI Storage Blueprint at Scale

Over the past several years, model capabilities and training dataset sizes have experienced exponential growth. During the past year or so, the time between new-frontier-model releases has gone down from months to weeks. Reliable and fast access to storage is important to both the speed and computational cost of this AI innovation.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: Over the past several years, model capabilities and training dataset sizes have experienced exponential growth.

Official sourceData Center EngineeringData Infrastructure
Original
Artificial Intelligence / Machine Learning
arXiv6/29/2026
Recently

LeVo 2: Stable and Melodious Song Generation via Hierarchical Representation Modeling and Progressive Post-Training

Full-length song generation must preserve coherence and musicality, render detailed vocal and accompaniment acoustics, and follow lyrics and prompts. Existing language model-based systems face a structural trade-off: mixed-token modeling preserves vocal-instrument coordination but obscures track-specific details, whereas dual-track prediction improves acoustics but requires longer sequences and weakens global planning. We present LeVo 2, a hybrid LLM-Diffusion framework for controllable full-length song generation. Authors: Shun Lei, Huaicheng Zhang, Dapeng Wu.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Full-length song generation must preserve coherence and musicality, render detailed vocal and accompaniment acoustics, and follow lyrics and prompts.

Primary paperarxivcs.SD
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/1/2026
Recently

Cheap Code, Costly Judgment: A Case Study on Governable Agentic Software Engineering

Generative AI is shifting software engineering from a practice organized around scarce implementation effort toward one organized around abundant, low-cost code production. This shift changes the central engineering problem: not whether AI can generate useful code, but how engineers organize architectures, tools, evidence, and feedback loops so that AI-mediated development remains inspectable, correctable, and maintainable. We study this problem through a first-person case study: a 12-week development effort in which a single expert software engineer used frontier AI coding agents to build a document accessibility remediation system. Authors: James C. Davis, Paschal C. Amusuo, Tanmay Singla.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Generative AI is shifting software engineering from a practice organized around scarce implementation effort toward one organized around abundant, low-cost code production.

Primary paperarxivcs.SE
Original
Automation / Agentic Systems
arXiv7/1/2026
Recently

AGC-Bench: Measuring Artificial General Creativity

, visual, writing, science), and if it is psychometrically separable from general intelligence. Both questions now apply to LLMs, but a unified benchmark of AI creativity remains elusive. We introduce AGC-Bench, an artificial general creativity benchmark built from a systematic review of the AI creativity literature (3,101 papers screened, 497 benchmarks identified), paired with an agentic harness that converts idiosyncratic codebases into HELM-standardized benchmarks. Authors: Roger Beaty, Vijeta Deshpande, Clin K. Y. Lai.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: , visual, writing, science), and if it is psychometrically separable from general intelligence.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/1/2026
Recently

Adversarial Pragmatics for AI Safety Evaluation: A Benchmark for Instruction Conflict, Embedded Commands, and Policy Ambiguity

Safety evaluations for language models increasingly depend on judgments about ambiguous natural-language behaviour: whether a model has followed an instruction, refused appropriately, complied with a policy, resisted an embedded command, or misreported progress in an agentic task. Existing benchmarks often compress these distinctions into pass/fail labels, obscuring whether failures arise from capability limits, policy ambiguity, instruction conflict, scaffold failure, or unstable evaluator judgments. This paper introduces adversarial pragmatics as a benchmark and annotation protocol for evaluating model behaviour under instruction conflict, embedded commands, quotation, scope ambiguity, deixis, indirect speech acts, and multi-turn agent transcripts. Authors: Brett Reynolds.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Safety evaluations for language models increasingly depend on judgments about ambiguous natural-language behaviour: whether a model has followed an instruction, refused appropriately, complied with a policy, resisted an embedded command, or misreported progress in an agentic task.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/1/2026
Recently

Are Performance-Optimization Benchmarks Reliably Measuring Coding Agents?

Repository-level performance-optimization benchmarks such as GSO, SWE-Perf and SWE-fficiency evaluate coding agents by applying patches to real repositories and comparing runtime against unoptimized baselines and official reference patches. Their leaderboard scores are increasingly used as evidence of coding-agent progress, but those scores can conflate runtime instability, benchmark-specific scoring rules, and how many tasks are already solved by at least one public submission. We audit these issues across the three benchmarks. Authors: Zhi Chen, Zhensu Sun, Yuling Shi.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Repository-level performance-optimization benchmarks such as GSO, SWE-Perf and SWE-fficiency evaluate coding agents by applying patches to real repositories and comparing runtime against unoptimized baselines and official reference patches.

Primary paperarxivcs.SE
Original
Automation / Agentic Systems
arXiv7/1/2026
Recently

Distributed Containment of a Compromised Agent through Repulsive Cages

UAV swarms and cyber-physical multi-agent systems are increasingly deployed in safety-critical missions that require coordinated motion, distributed decision making, and autonomy. A major security risk arises when a legitimate agent is hijacked and driven by adversarial high-level commands. Rather than focusing on detection and isolation of malicious agents, we exploit a structural property common in autonomous platforms: low-level collision-avoidance modules are typically implemented as independent safety layers and may remain active even under high-level compromise. Authors: Luigi Petruzziello, Camilla Fioravanti, Gabriele Oliva.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: UAV swarms and cyber-physical multi-agent systems are increasingly deployed in safety-critical missions that require coordinated motion, distributed decision making, and autonomy.

Primary paperarxiveess.SY
Original

Archived section

Research Papers · 5

Research Papers
arXiv6/29/2026
Recently

Concept Catalyst: Exploring Scrutable Interfaces to Structure K-12 Teacher Interactions with Generative AI

Purpose: This paper explores how to align AI-based tools with teachers' classroom needs by using scrutable interfaces -- interfaces that link an easily manipulable knowledge representation to an underlying AI model, so users can change the system's outputs without understanding its details. It provides an in-depth discussion and example of a scrutable interface that structures teachers' interactions with generative AI. This study aims to expand how and where scrutable interfaces are used in AI-based tools to support teachers, who have not been historically targeted in the design of scrutable systems. Authors: Gennie Mansi, Sunni Newton, Roxanne Moore.

Why it matters

Read this for the paper's specific claim in Research Papers: Purpose: This paper explores how to align AI-based tools with teachers' classroom needs by using scrutable interfaces -- interfaces that link an easily manipulable knowledge representation to an underlying AI model, so users can change the system's outputs without understanding its details.

Primary paperarxivcs.HC
Original
Research Papers
arXiv6/29/2026
Recently

Between Zeros and Ones: Behavioral Characterization Beyond Binary Labeling Across Public ICS Datasets

Intrusion detection in Industrial Control Systems (ICS) is typically evaluated on a small set of public benchmarks using binary ``normal'' versus ``attack'' labels, a practice that can mask the behavioral diversity of cyber-physical attacks. To address this limitation, we propose a behavioral characterization framework that maps raw multivariate process traces into five interpretable physical primitives: drift, spike, oscillation, repetition, and switching. We apply the framework to three widely used ICS benchmarks, namely, SWaT, WADI, and HAI, and show that attack windows exhibit clear behavioral shifts relative to normal operation while the three datasets occupy largely distinct regions of the behavioral space, revealing both cross-dataset bias and intra-dataset diversity. Authors: Konstantinos E. Kampourakis, Vyron Kampourakis, Georgios Spathoulas.

Why it matters

Read this for the paper's specific claim in Research Papers: Intrusion detection in Industrial Control Systems (ICS) is typically evaluated on a small set of public benchmarks using binary ``normal'' versus ``attack'' labels, a practice that can mask the behavioral diversity of cyber-physical attacks.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/1/2026
Recently

Detecting Adversarial Evasion Attacks Against Autoencoder-Based Network Intrusion Detection Systems

Evasion attacks deliberately manipulate input to an ML-based system to produce an incorrect prediction while the manipulated input still appears benign. The PANDA framework has demonstrated that adversarial examples developed for the vision domain can be transferred to the network domain by converting packet sequences into invertible grayscale images, enabling gradient-based attacks such as masked FGSM against autoencoder-based network intrusion detection systems (NIDS). These attacks manipulate the NIDS anomaly score without altering the underlying attack semantics, leaving defenders without a straightforward way to distinguish between benign flows and carefully perturbed malicious traffic. Authors: Niklas Bunzel, Ashim Siwakoti.

Why it matters

Read this for the paper's specific claim in Research Papers: Evasion attacks deliberately manipulate input to an ML-based system to produce an incorrect prediction while the manipulated input still appears benign.

Primary paperarxivcs.CR
Original
Research Papers
arXiv6/29/2026
Recently

The Role of Vehicles in Digital Forensic Investigations: A Structured Synthesis of Digital Vehicle Forensic Characteristics

Modern vehicles are cyber-physical, networked systems that may contain valuable digital traces for accident reconstruction, crime investigation, warranty analysis, and cybersecurity incident response. However, digital vehicle forensics (DVF) remains less mature than computer, mobile, and cloud forensics because relevant data is distributed across in-vehicle components, mobile devices, manufacturer back ends, third-party services, and physical evidence. This article addresses this gap through a structured synthesis of academic literature, standards, and practitioner-oriented sources. Authors: Kevin Mayer.

Why it matters

Read this for the paper's specific claim in Research Papers: Modern vehicles are cyber-physical, networked systems that may contain valuable digital traces for accident reconstruction, crime investigation, warranty analysis, and cybersecurity incident response.

Primary paperarxivcs.CR
Original
Research Papers
arXiv6/29/2026
Recently

A Lightweight Post-Quantum Authentication Framework for 5G Base Station Bootstrapping

The absence of authenticated bootstrapping between User Equipments (UEs) and Base Stations (BSs) in 5G leaves System Information Block (SIB) broadcasts unprotected, enabling fake BS attacks, man-in-the-middle interception, and spoofed emergency alerts. Prior efforts such as Public Key Infrastructure (PKI)-based certificate chains, token-based schemes, and identity-based signatures either impose overhead exceeding 5G's strict packet-size constraints or lack post-quantum (PQ) security. Direct NIST-PQC integration is infeasible: ML-DSA requires 34 fragmented SIB1 packets and up to 5,282,ms end-to-end delay, and FN-DSA still requires 13 fragments and up to 1,920,ms. Authors: Saleh Darzi, Mirza Masfiqur Rahman, Imtiaz Karim.

Why it matters

Read this for the paper's specific claim in Research Papers: The absence of authenticated bootstrapping between User Equipments (UEs) and Base Stations (BSs) in 5G leaves System Information Block (SIB) broadcasts unprotected, enabling fake BS attacks, man-in-the-middle interception, and spoofed emergency alerts.

Primary paperarxivcs.CR
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/1/2026
Recently

Sensorless Four-Channel Control Architecture Using Inverse Dynamics Modeling for Human-Scale Bilateral Teleoperation

The four-channel teleoperation architecture is a well-established framework for achieving transparency in bilateral systems. However, its performance in human-scale teleoperation is limited by high inertia, modeling challenges, and reliance on noisy and costly force/torque sensors. This paper introduces a sensorless four-channel architecture based on inverse dynamics modeling. Authors: Amir Noohian, Dylan Miller, Justin Valentine.

Why it matters

Read this for the paper's specific claim in Embedded Systems: The four-channel teleoperation architecture is a well-established framework for achieving transparency in bilateral systems.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv7/1/2026
Recently

FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model

Current work on robot furniture assembly mostly focuses on toy-scale settings or single-arm manipulation. We introduce FurnitureVLA, the first systematic study of real-scale bimanual furniture assembly using Vision-Language-Action models (VLAs). We formalize the task, develop a scalable simulation pipeline for expert data generation and evaluation, and build a VR teleoperation system for single-operator bimanual control to collect high-quality real-world demonstrations. Authors: Chenyang Ma, Yue Yang, Radu Corcodel.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Current work on robot furniture assembly mostly focuses on toy-scale settings or single-arm manipulation.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv7/1/2026
Recently

GPU-Parallel Linearization Error Bounds for Real-Time Robust Optimal Control of Nonlinear and Neural Network Dynamics

This paper studies real-time robust optimal control for uncertain nonlinear systems, where linear time-varying (LTV) approximations make planning tractable but require sound linearization error bounds (LEBs) to guarantee robust constraint satisfaction. We develop tight, differentiable, GPU-parallel LEBs for LTV approximations of nonlinear and neural network (NN) dynamics. For analytic dynamics, we introduce path-based Hessian bounds that are tighter than standard interval methods. Authors: Jeffrey Fang, Keyi Shen, Anutam Srinivasan.

Why it matters

Read this for the paper's specific claim in Embedded Systems: studies real-time robust optimal control for uncertain nonlinear systems, where linear time-varying (LTV) approximations make planning tractable but require sound linearization error bounds (LEBs) to guarantee robust constraint satisfaction.

Primary paperarxiveess.SY
Original
Embedded Systems
NVIDIA Technical Blog6/30/2026
Recently

Designing GPU-Accelerated Query Engines with NVIDIA GQE

GPU-accelerated query engines are often constrained by memory and I/O bandwidth. NVIDIA hardware advances—including high bandwidth memory (HBM), NVIDIA... GPU-accelerated query engines are often constrained by memory and I/O bandwidth.

Why it matters

Read this for the official technical update in Embedded Systems: GPU-accelerated query engines are often constrained by memory and I/O bandwidth.

Official source
Original
Embedded Systems
Hackster.io6/30/2026
Recently

Arduino Drops Three New Modulino Modules

Nothing slows down circuit prototyping more than interfacing different types of hardware with your chosen development platform. Locating all of the right drivers and wiring everything up correctly takes us out of the fast-paced flow of building and forces us to focus on little details. No matter what we're building, these details aren't the important part — they are just a distraction.

Why it matters

Read this for the engineering context in Embedded Systems: Nothing slows down circuit prototyping more than interfacing different types of hardware with your chosen development platform.

Trusted source
Original

Archived section

Computer Systems · 5

Computer Systems
arXiv6/29/2026
Recently

SubEdge: A Subscriber-Centric Edge Computing Subsystem in 6G Networks for AI

Beyond traditional connectivity, 6G is envisioned to transform mobile networks into a distributed fabric that provides native integrated communication, computing, and intelligence services., robots, autonomous vehicles, and smart glasses) require real-time inference from individualised, manufacturer-specific models that cannot be executed on-board nor shared across subscribers, making per-subscriber edge compute the necessary complement to per-subscriber connectivity. Existing Network for AI (Net4AI) architectures provision compute for application providers through shared deployments and do not address per-subscriber provisioning. Authors: Abdirazak Ali Asir Rage, Riccardo Pozza, Rahim Tafazolli.

Why it matters

Read this for the paper's specific claim in Computer Systems: , robots, autonomous vehicles, and smart glasses) require real-time inference from individualised, manufacturer-specific models that cannot be executed on-board nor shared across subscribers, making per-subscriber edge compute the necessary complement to per-subscriber connectivity.

Primary paperarxivcs.NI
Original
Computer Systems
arXiv6/29/2026
Recently

COSM: A Cooperative Scheduling Framework for Concurrent PIM and CPU Execution on Mobile Devices

The development of on-device large language models (LLMs) is driven by the need for privacy and fast response times. Energy-intensive data transfer on mobile devices makes Processing-in-Memory (PIM) an effective solution. Due to stringent DRAM cost constraints, limited physical footprint on circuit boards, and the interaction between applications and LLMs, it is imperative for the CPU and PIM to operate concurrently within a shared memory space. Authors: Yilong Zhao, Fangxin Liu, Onur Mutlu.

Why it matters

Read this for the paper's specific claim in Computer Systems: The development of on-device large language models (LLMs) is driven by the need for privacy and fast response times.

Primary paperarxivcs.AR
Original
Computer Systems
LWN.net7/1/2026
Recently

Efficient access to local storage for BPF programs

When a BPF program is used to filter or redirect packets in the networking subsystem, the program will often want to associate data with each packet as it moves through the kernel. The kernel's local BPF storage API, which associates extra data with some kernel objects, provides a way to do that. ) Amery Hung and Jakub Sitnicki led two sessions at the 2026 Linux Storage, Filesystem, Memory-Management, and BPF Summit about how to make accesses to local storage data more efficient.

Why it matters

Read this for the concrete reporting in Computer Systems: When a BPF program is used to filter or redirect packets in the networking subsystem, the program will often want to associate data with each packet as it moves through the kernel.

Trusted source
Original
Computer Systems
AWS Architecture Blog6/29/2026
Recently

Dual-token authentication for Nakama game servers with Amazon Cognito on AWS

In this post, you learn how to configure an Amazon Cognito User Pool for SRP-based game client authentication with no client secret. You will implement a Go runtime hook that validates Cognito JWTs and bridges player identity to Nakama sessions.

Why it matters

Read this for the official technical update in Computer Systems: In this post, you learn how to configure an Amazon Cognito User Pool for SRP-based game client authentication with no client secret.

Official sourceAmazon CloudFrontAmazon Cognito
Original
Computer Systems
arXiv7/1/2026
Recently

All-out Attack: Optimal Block Withholding Under Pay-Per-Share Scheme

Classical Block Withholding (BWH) attacks have been extensively studied in block-dependent reward schemes, where pool members are compensated upon a block discovery within the pool. However, most contemporary mining pools operate under share-based scheme wherein participants are paid immediately upon submission of valid shares. In this paper, we analyze BWH under Pay-Per-Share (PPS) and Full-PPS (FPPS) schemes for Nakamoto-style blockchains and prove that these mechanisms are not incentive compatible -- contrary to claims in prior literature. Authors: Mustafa Doger, Sennur Ulukus.

Why it matters

Read this for the paper's specific claim in Computer Systems: Classical Block Withholding (BWH) attacks have been extensively studied in block-dependent reward schemes, where pool members are compensated upon a block discovery within the pool.

Primary paperarxivcs.CR
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv7/1/2026
Recently

Theoria: Rewrite-Acceptability Verification over Informal Reasoning States

When should an AI system's answer be trusted? Formal proof assistants offer certainty but cannot reach most of the problem distribution; scalar LLM judges offer coverage but produce opaque scores that cannot be audited after the fact and are subject to the same coherence issues as any LLM. We present Theoria, a verification architecture that closes this gap. Authors: Ben Slivinski, Michael Saldivar.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: When should an AI system's answer be trusted?

Primary paperarxivcs.AI
Original
Developer Tools / Open Source
Vercel Blog6/30/2026
Recently

Enforce consistent code for agents and humans with konsistent

konsistent is a CLI linter for TypeScript codebases that enforces structural conventions, giving agents and humans the consistent context they need to implement features correctly. json Read more Do all files matching pattern X export functions Y and Z? Does every folder that has file X also have file Y?

Why it matters

Read this for the official technical update in Developer Tools / Open Source: konsistent is a CLI linter for TypeScript codebases that enforces structural conventions, giving agents and humans the consistent context they need to implement features correctly.

Official source
Original
Developer Tools / Open Source
Docker Blog7/1/2026
Recently

Why AI Agents Need Isolation

Learn why AI agent isolation matters, how Docker SBX enables safer AI workflows, and how Sandbox Kits help. Written by Docker Captain Karan Verma.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Learn why AI agent isolation matters, how Docker SBX enables safer AI workflows, and how Sandbox Kits help.

Official sourceCommunityAI Agent
Original
Developer Tools / Open Source
GitHub Blog7/1/2026
Recently

6 security settings every GitHub maintainer should enable this week

These six free settings will not make your project unhackable. Nothing will. What they will do is close the easy doors.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: These six free settings will not make your project unhackable.

Official sourceApplication securityMaintainers
Original
Developer Tools / Open Source
LWN.net6/29/2026
Recently

Open source maintainership in the age of AI (Kubernetes blog)

The Kubernetes project has published a blog post explaining its AI policy: The main problem is that AI has made generating code fast but there has been very little improvement in maintaining code bases. In this post, we will highlight the ways the Kubernetes community is adapting to the world of AI assisted coding. The first step of this journey was to develop an AI policy.

Why it matters

Read this for the concrete reporting in Developer Tools / Open Source: The Kubernetes project has published a blog post explaining its AI policy: The main problem is that AI has made generating code fast but there has been very little improvement in maintaining code bases.

Trusted source
Original

Archived section

Cloud / Infrastructure · 5

Cloud / Infrastructure
Cloudflare Blog7/1/2026
Recently

Announcing the Monetization Gateway: charge for any resource behind Cloudflare via x402

We're opening the waitlist for our Monetization Gateway, which will allow you to charge for any web page, dataset, API, or MCP tool behind Cloudflare. The charges will settle in stablecoins over the x402 open protocol, with no payments stack of your own to build.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: We're opening the waitlist for our Monetization Gateway, which will allow you to charge for any web page, dataset, API, or MCP tool behind Cloudflare.

Official sourceContent Independence DayAI Bots
Original
Cloud / Infrastructure
AWS Architecture Blog6/29/2026
Recently

Lessons learned from scaling to 1 million Lambda functions

In this post, we share our journey and the lessons learned from building and running a fully serverless, multi-account software as a service (SaaS) platform at scale. We'll explore why true scale-to-zero is critical, how we handle quota management, why engaging AWS service teams early saved us from outages, and which unexpected practices emerged once we scaled from thousands to over a million functions.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: In this post, we share our journey and the lessons learned from building and running a fully serverless, multi-account software as a service (SaaS) platform at scale.

Official sourceCustomer SolutionsServerless
Original
Cloud / Infrastructure
CNCF Blog6/30/2026
Recently

Dragonfly v2.5.0 is released

0 is released! Thanks to all of the contributors who made this Dragonfly release happen. New features and enhancements Direct repository downloads from Hugging Face and ModelScope Dragonfly Client now supports directly downloading model repositories...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Thanks to all of the contributors who made this Dragonfly release happen.

Official sourceBlog
Original
Cloud / Infrastructure
AWS Blog6/30/2026
Recently

Accelerate your infrastructure deployments by up to 4x with AWS CloudFormation Express mode

AWS CloudFormation speeds up infrastructure deployment with Express mode, enabling AI agents and developers to receive deployment confirmation in seconds and iterate faster. Available in all commercial Regions at no additional cost.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: AWS CloudFormation speeds up infrastructure deployment with Express mode, enabling AI agents and developers to receive deployment confirmation in seconds and iterate faster.

Official sourceAWS CloudFormationLaunch
Original
Cloud / Infrastructure
AWS Architecture Blog6/29/2026
Recently

Preventing data exfiltration in machine learning environments with Amazon SageMaker AI

In this post, we demonstrate how iBusiness implemented a three-layered security architecture using Amazon SageMaker AI, virtual private cloud (VPC) endpoints, and Amazon WorkSpaces Secure Browser to prevent data exfiltration while maintaining data scientist productivity. You can adapt this approach to build secure machine learning environments that balance strict data protection with team scalability.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: In this post, we demonstrate how iBusiness implemented a three-layered security architecture using Amazon SageMaker AI, virtual private cloud (VPC) endpoints, and Amazon WorkSpaces Secure Browser to prevent data exfiltration while maintaining data scientist productivity.

Official sourceAmazon SageMaker AIAmazon SageMaker Studio
Original