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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
arXiv8/5/2026
Recently

Item Response Theory for AI Safety

Language models differ in how safely they behave and these differences are measured by safety benchmarks. But aggregated benchmark scores are hard to trust and interpret, because benchmarks duplicate one another, correlate heavily, and models may sandbag when they detect evaluation. To address these issues, we draw on Item Response Theory (IRT), a statistical toolkit for measuring these latents from performance on items with inferred psychometric properties. Authors: Joshua Fonseca Rivera, Neil Shah, David Demitri Africa.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Language models differ in how safely they behave and these differences are measured by safety benchmarks.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv8/4/2026
Recently

DS@GT-ARC at eRisk 2026 Task 3: Sparse, Semantic, and LLM Reranking for ADHD Symptom Sentences

This paper describes our submissions to eRisk 2026 Task 3, ADHD Symptom Sentence Ranking. 1). Because no annotated training data were released for this first edition of the task, we relied on zero-shot experimentation, manual validation, and unsupervised or weakly guided retrieval pipelines. Authors: David Guecha.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: describes our submissions to eRisk 2026 Task 3, ADHD Symptom Sentence Ranking.

Primary paperarxivcs.CL
Original
Artificial Intelligence / Machine Learning
arXiv8/3/2026
Recently

WorldExam: Benchmarking World Models from Apparent Appearance to Inherent Reactivity

Controllable video generation models are increasingly being developed as world models. Accordingly, evaluating them in this role extends beyond the apparent appearance of generated videos to the inherent reactivity of the worlds they depict: the ability to infer from the scene state how the world should react and to generate plausible consequences not explicitly described in the input. Yet existing benchmarks mainly assess visual quality or explicit instruction fulfillment by checking whether requested actions and interaction outcomes are realized, leaving inherent reactivity underexamined. Authors: Yuxue Yang, Shuyao Shang, Jiahe Wang.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Controllable video generation models are increasingly being developed as world models.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
Meta Engineering8/3/2026
Recently

GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model

Meta's Generative Ads Recommendation Model (GEM), the foundation model behind ads recommendations across Instagram and Facebook, now trains at LLM scale on several thousand of the latest-generation GPUs. ] Read More... The post GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model appeared first on Engineering at Meta.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: Meta's Generative Ads Recommendation Model (GEM), the foundation model behind ads recommendations across Instagram and Facebook, now trains at LLM scale on several thousand of the latest-generation GPUs.

Official sourceAI ResearchData Infrastructure
Original
Artificial Intelligence / Machine Learning
OpenAI Blog8/4/2026
Recently

Third-party cyber evaluations involving OpenAI models

OpenAI explains recent third-party cybersecurity evaluation incidents and outlines new safeguards to strengthen AI model testing and evaluation.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: OpenAI explains recent third-party cybersecurity evaluation incidents and outlines new safeguards to strengthen AI model testing and evaluation.

Official source
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv8/5/2026
Recently

ArtAnno: Annotating Implicit Semantics in Artworks through LLM Agent-Driven Bidirectional Human-AI Augmentation

High-quality annotation of artworks is essential for computational art research, yet extracting implicit semantics remains challenging due to the reliance on culturally grounded meanings and deep contextual knowledge behind the images. Current AI-assisted annotation tools often lack assistance or rely on one-way workflows where experts have to perform extra manual calibrations to improve AI models, resulting in limited efficiency. To address this, we propose Bidirectional Human-AI Augmentation(BiHAA), a closed-loop framework in which skills and domain knowledge base evolve through real-time interaction and bidirectional HAI augmentation. Authors: Xiaoyan Gu, Yifang Wang, Wenqing Zheng.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: High-quality annotation of artworks is essential for computational art research, yet extracting implicit semantics remains challenging due to the reliance on culturally grounded meanings and deep contextual knowledge behind the images.

Primary paperarxivcs.HC
Original
Automation / Agentic Systems
arXiv8/5/2026
Recently

Argus: A General-Purpose Agentic Runtime for Long-Horizon Reasoning

Long-horizon reasoning requires an agentic runtime that can persist when evidence supports its current approach and pivot when measurements reveal failure, hidden constraints, or a misspecified objective. We present Argus, a persistent, self-evolving runtime in which Manager, Planner, Engineer, and Reviewer execute bounded missions over durable project state. Argus separates stable user intent from operational objectives, constraints, and verification criteria, and admits memories, skills, procedures, verifiers, routing decisions, and rejected routes only after role-owned review and, when available, task-native verification. Authors: Boxiu Li, Zimo Wen, Yijia Fan.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Long-horizon reasoning requires an agentic runtime that can persist when evidence supports its current approach and pivot when measurements reveal failure, hidden constraints, or a misspecified objective.

Primary paperarxivcs.AI
Original
Automation / Agentic Systems
arXiv8/5/2026
Recently

Spoken Function Calling: A New Perspective on Spoken Language Understanding for Large Audio Language Models

Spoken Language Understanding (SLU) is the core component of task-oriented dialogue systems and a pivotal link in achieving seamless human-agent interaction. While traditional SLU can effectively extract user semantics for closed-set tasks after in-domain supervised fine-tuning, it faces significant challenges in leveraging in-context learning for open-domain tasks due to its ambiguous rule definitions. This work proposes Spoken Function Calling (SFC), a novel semantic understanding perspective that optimizes semantic understanding with structured rule definitions, to evolve beyond traditional closed-set SLU. Authors: Yuezhang Peng, Yuxin Liu, Changfeng Gao.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Spoken Language Understanding (SLU) is the core component of task-oriented dialogue systems and a pivotal link in achieving seamless human-agent interaction.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
GitHub Blog8/4/2026
Recently

How the GitHub legal team used Copilot CLI to streamline their workflows

Learn how to build tools to simplify how you work—without writing a single line of code. The post How the GitHub legal team used Copilot CLI to streamline their workflows appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Automation / Agentic Systems: Learn how to build tools to simplify how you work—without writing a single line of code.

Official sourceAI & MLGitHub Copilot
Original
Automation / Agentic Systems
arXiv8/5/2026
Recently

OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling

Context lengths of language models (LMs) have dramatically increased, driven by the demands for in-context learning, self-improvement, and long-horizon agentic workflows. Existing long-context corpora, however, are dominated by books, academic articles, and code repositories, which are finite resources and often scarce in long-distance dependencies. In this work, we introduce OctoLong, a context engineering pipeline that instruments an AST parser, a language server backend, and a package manager to facilitate the recursive retrieval of code references, enabling the curation of dependency-rich code contexts of millions of tokens in length. Authors: Indraneil Paul, Falko Helm, Goran Glavaš.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Context lengths of language models (LMs) have dramatically increased, driven by the demands for in-context learning, self-improvement, and long-horizon agentic workflows.

Primary paperarxivcs.AI
Original

Archived section

Research Papers · 5

Research Papers
arXiv8/5/2026
Recently

Towards Decentralized Searcher Competition in MEV Markets

Centralization in maximal extractable value (MEV) markets is a significant concern for blockchain systems, as persistent concentration of economic power can weaken competition, reduce openness, and undermine the decentralization goals of permissionless protocols. While much of the existing analysis has focused on builders, validators, and block-building markets, this paper studies centralization from the perspective of searcher competition. We develop a heterogeneous model in which searchers differ in opportunity coverage and execution efficiency, and we analyze how auction design affects fairness, decentralization, and security among searchers competing for the same MEV opportunity. Authors: Roozbeh Sarenche, Yunwen Liu.

Why it matters

Read this for the paper's specific claim in Research Papers: Centralization in maximal extractable value (MEV) markets is a significant concern for blockchain systems, as persistent concentration of economic power can weaken competition, reduce openness, and undermine the decentralization goals of permissionless protocols.

Primary paperarxivcs.GT
Original
Research Papers
arXiv8/5/2026
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DeepConnect: A Visual Analytics System for Bridging Interdisciplinary Research Collaborations

Interdisciplinary research collaboration is crucial for scientific innovation, but it remains difficult to initiate in practice. Existing collaborator discovery approaches are often constrained by disciplinary boundaries and static researcher profiles that do not reflect the specific context of a new collaboration goal. As a result, researchers struggle to translate open-ended collaboration goals into domain-specific tasks, evaluate candidate researchers' fit and complementarity, and establish common ground before initial contact. Authors: Yingchaojie Feng, Zekai Shao, Yiqun Sun.

Why it matters

Read this for the paper's specific claim in Research Papers: Interdisciplinary research collaboration is crucial for scientific innovation, but it remains difficult to initiate in practice.

Primary paperarxivcs.HC
Original
Research Papers
arXiv8/4/2026
Recently

Calibrating Trustworthiness: Co-Designing Metrics and Visualizations for Evaluating LLMs in Education

LLMs are reshaping educational technology, yet evaluating their responses for pedagogical alignment remains underexplored, relying heavily on the expertise of learning engineers building the technology. To bridge this gap, we explore trustworthiness as a structured lens for evaluation, leveraging existing measures of LLM trustworthiness to systematically identify potential pedagogical disruptions. Through a longitudinal co-design process with learning engineers developing an LLM-powered digital textbook, we: (1) co-constructed five trustworthiness metrics comprising 20 measures tailored to pedagogical use; (2) designed visualizations that map trustworthiness violations onto LLM responses; and (3) evaluated how these tools help learning engineers make A/B comparisons of LLM responses. Authors: Adam Coscia, Sujata Duwal, Langdon Holmes.

Why it matters

Read this for the paper's specific claim in Research Papers: LLMs are reshaping educational technology, yet evaluating their responses for pedagogical alignment remains underexplored, relying heavily on the expertise of learning engineers building the technology.

Primary paperarxivcs.HC
Original
Research Papers
arXiv8/4/2026
Recently

Semantic Bundling: Interactive Node and Edge Bundling to Simplify Knowledge Graphs using Large Language Models

We present Semantic Bundling, a visual analytics technique for making sense of text documents represented as knowledge graphs (KGs). Representing a document corpus as a KG makes relationships between entities explicit, making KGs useful both to analyze directly and in computational workflows including ML pipelines and generative AI backends., the ``hairball problem''), with the meaning of each relationship often buried in dense source text. Authors: Adam Coscia, Zeyu Hua, Eric Krokos.

Why it matters

Read this for the paper's specific claim in Research Papers: We present Semantic Bundling, a visual analytics technique for making sense of text documents represented as knowledge graphs (KGs).

Primary paperarxivcs.HC
Original
Research Papers
arXiv8/5/2026
Recently

Private Direct Preference Optimization for LLM Alignment

Direct preference optimization (DPO) is now a standard method for aligning large language models (LLMs) using human preference data. Each DPO example contains a prompt and a pair of candidate model responses. While prompts and responses are often public or model-generated, the relative preference between responses reflects subjective judgments and can reveal sensitive attributes of annotators or end users. Authors: Yangfan Jiang, Fei Wei, Ergute Bao.

Why it matters

Read this for the paper's specific claim in Research Papers: Direct preference optimization (DPO) is now a standard method for aligning large language models (LLMs) using human preference data.

Primary paperarxivcs.CR
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv8/5/2026
Recently

BridgeVLA++: A Data-Efficient, Generalizable, and Memory-Augmented Vision-Language-Action Framework for 3D Manipulation

Leveraging pre-trained vision-language models (VLMs) to construct vision-language-action (VLA) models has emerged as a promising paradigm for 3D robot manipulation. However, existing 3D VLA methods remain data-hungry, exhibit limited generalization under distribution shifts, and lack explicit memory of past observations. These limitations hinder their application to data-scarce, open-world, and memory-dependent manipulation scenarios. Authors: Peiyan Li, Yuze Zhu, Yixiang Chen.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Leveraging pre-trained vision-language models (VLMs) to construct vision-language-action (VLA) models has emerged as a promising paradigm for 3D robot manipulation.

Primary paperarxivcs.RO
Original
Embedded Systems
arXiv8/5/2026
Recently

AI-based single-shot structured-light depth reconstruction for real-time laparoscopic surgical guidance

Significance. Accurate intraoperative depth perception is important for autonomous and semi-autonomous robotic laparoscopic surgery. Conventional fringe projection profilometry can achieve millimeter-scale accuracy but often requires multi-shot acquisition, digital-micromirror-device projection, and projector-camera synchronization, complicating integration into compact laparoscopic systems. Authors: Wayne Wonseok Rodgers, Xiangyi Le, Seonghoon Jang.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Accurate intraoperative depth perception is important for autonomous and semi-autonomous robotic laparoscopic surgery.

Primary paperarxiveess.IV
Original
Embedded Systems
arXiv8/5/2026
Recently

Optimal Constrained sc-LTL Planning in MDPs via Switching Policies

We study the synthesis of optimal policies for planning problems on Markov decision processes with both objectives and safety constraints specified in co-safe linear temporal logic (sc-LTL). Our problems are inherently non-Markovian due to the complexity of the sc-LTL specification and may require policy randomization to balance the objective and constraint. We propose a novel approach that reduces the constrained sc-LTL planning problem to a constrained reachability problem on an extended model. Authors: Zetong Xuan, Yu Wang.

Why it matters

Read this for the paper's specific claim in Embedded Systems: We study the synthesis of optimal policies for planning problems on Markov decision processes with both objectives and safety constraints specified in co-safe linear temporal logic (sc-LTL).

Primary paperarxivcs.RO
Original
Embedded Systems
Hackster.io8/3/2026
Recently

Looking to Increase the Strength of Your 3D-Printed PLA Parts? Give Them a Shake, Researchers Say

Vibration, normally an unwanted force that serves to ruin the finish of your 3D prints, could be harnessed to deliver stronger PLA prints on fused filament fabrication (FFF, also known as FDM) 3D printers — at least, according to researchers from the University of Ha'il, the Higher Institute for Technical Sciences Tarhuna, the University of Sfax, and the University of Sousse. "Material Extrusion (MEX), particularly Fused Filament Fabrication (FFF), commercially known as Fused Deposition Modeling (FDM), has become one of the most widely used additive manufacturing technologies for producing polymer components," the team explains by way of background to the work. "However, the mechanical performance of printed parts remains limited by weak interlayer bonding and internal porosity.

Why it matters

Read this for the engineering context in Embedded Systems: Vibration, normally an unwanted force that serves to ruin the finish of your 3D prints, could be harnessed to deliver stronger PLA prints on fused filament fabrication (FFF, also known as FDM) 3D printers — at least, according to researchers from the University of Ha'il, the Higher Institute for Technical Sciences Tarhuna, the University of Sfax, and the University of Sousse.

Trusted source
Original
Embedded Systems
Hackster.io8/5/2026
Recently

ShiftLens Turns 3D-Printed Objects Into Smart Displays — No Electronics Required

Researchers at the Massachusetts Institute of Technology (MIT), the Technical University of Munich, and Northeastern University have combined lenticular optics with 3D printing to produce electronics-free objects that can change their appearance on demand — even letting you know if you're using them incorrectly: ShiftLens. "Interactive objects often rely on embedded electronics for dynamic surface appearance, which can increase fabrication complexity and reduce robustness in everyday settings," the team explains of the problem it set out to solve. "We present ShiftLens, a design and fabrication system for creating 3D objects with mechanically switchable surface appearances, enabling dynamic visual output without electronics.

Why it matters

Read this for the engineering context in Embedded Systems: Researchers at the Massachusetts Institute of Technology (MIT), the Technical University of Munich, and Northeastern University have combined lenticular optics with 3D printing to produce electronics-free objects that can change their appearance on demand — even letting you know if you're using them incorrectly: ShiftLens.

Trusted source
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Archived section

Computer Systems · 5

Computer Systems
arXiv8/5/2026
Recently

Kerckhoffs-Compliant Watermarking for Physical Design IP Protection: From Placement to Routing

Physical design (PD) intellectual property (IP) is a valuable artifact of modern VLSI implementation. It includes optimized cell placement, clock distribution, and routing decisions produced by carefully tuned PD flows. As access to PD tools expands, unauthorized reuse of placed-and-routed databases becomes an increasing concern. Authors: Andrew B. Kahng, Yiting Liu.

Why it matters

Read this for the paper's specific claim in Computer Systems: Physical design (PD) intellectual property (IP) is a valuable artifact of modern VLSI implementation.

Primary paperarxivcs.CR
Original
Computer Systems
arXiv8/5/2026
Recently

Hardware Design and Security in the Era of Chiplets and LLMs

5D chiplet systems and the integration of Large Language Models (LLMs) into Electronic Design Automation (EDA) flows., they radically expand the hardware attack surface. This paper provides a unified analysis of these frontiers, ranging from attacks on chiplet systems (including hardware stacks for LLM acceleration) across architectural, logical, and physical levels, to various exploits against LLM-driven EDA pipelines. Authors: Johann Knechtel, Ozgur Sinanoglu, Paul V. Gratz.

Why it matters

Read this for the paper's specific claim in Computer Systems: , they radically expand the hardware attack surface.

Primary paperarxivcs.CR
Original
Computer Systems
arXiv8/4/2026
Recently

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training

High-fidelity performance simulators are essential for designing and configuring efficient AI systems, yet today's tools lack the ability to predict power consumption. Established GPU power models rely on hardware utilization counters, which do not exist until the workload has actually run. This work evaluates whether Model FLOPs Utilization (MFU)-an analytical, software-defined metric relating achieved throughput to peak hardware capability-can serve as a portable, software-defined predictor of GPU power for LLMs. Authors: Niklas Enskat, Philipp Wiesner.

Why it matters

Read this for the paper's specific claim in Computer Systems: High-fidelity performance simulators are essential for designing and configuring efficient AI systems, yet today's tools lack the ability to predict power consumption.

Primary paperarxivcs.PF
Original
Computer Systems
arXiv8/5/2026
Recently

Deployment Feasibility Analysis of Post-Quantum Digital Signatures in Safety-Critical C-V2X Communication for Urban Mobility Scenario

The transition from the classical ECDSA to PQC creates substantially larger authentication payloads for safety-critical C-V2X sidelink communication. This study determines which NIST post-quantum signature algorithms are compatible with the current SAE J3161 deployment profile and quantifies their communication-level effects. 2 secured-message structures, SAE J3161 radio parameters, and the signature and public-key sizes of ECDSA P-256, Falcon-512, Dilithium-2, and SPHINCS+. Authors: Akid Abrar, Sagar Dasgupta, Abdullah Al Mamun.

Why it matters

Read this for the paper's specific claim in Computer Systems: The transition from the classical ECDSA to PQC creates substantially larger authentication payloads for safety-critical C-V2X sidelink communication.

Primary paperarxivcs.PF
Original
Computer Systems
LWN.net8/5/2026
Recently

Examining other network namespaces using BPF

Jordan Rife's work involves writing BPF programs for Cilium that interface with Kubernetes networking. As part of that work, he wants to enable BPF programs with appropriate permissions to iterate through the sockets of a different network namespace. He led a session about the idea at the 2026 Linux Storage, Filesystem, Memory-Management, and BPF Summit where the BPF developers in attendance were quick to suggest a number of related alternatives.

Why it matters

Read this for the concrete reporting in Computer Systems: Jordan Rife's work involves writing BPF programs for Cilium that interface with Kubernetes networking.

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Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
arXiv8/5/2026
Recently

Observing the Quantum Compiler through Automatic Experiment Tracking for Qiskit

Understanding the effectiveness of quantum compilation techniques requires visibility into the entire transpilation process, not just the final circuit metrics. This demonstration presents an MLflow-inspired autologging framework for Qiskit that automatically captures compiler provenance, including transpilation stages, pass-level execution data, backend characteristics, compiler configuration, and execution results. The framework extends the QProv provenance model with compiler-specific information and stores the collected data in an MLflow Tracking Server for analysis and visualization. Authors: Vlad Stirbu, Arianne Meijer van de Griend.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Understanding the effectiveness of quantum compilation techniques requires visibility into the entire transpilation process, not just the final circuit metrics.

Primary paperarxivquant-ph
Original
Developer Tools / Open Source
Vercel Blog8/5/2026
Recently

Pause workflows for approval with Chat SDK

You can build human-in-the-loop approvals with Chat SDK through the new subpath. chat/workflowrequestApprovalWorkflow SDK The wait can last seconds or days and survives deploys and restarts. You don't need an approvals table, an handler, or a polling loop:onAction Start the workflow from any handler, and instances serialize across the workflow boundary automatically.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: You can build human-in-the-loop approvals with Chat SDK through the new subpath.

Official source
Original
Developer Tools / Open Source
CNCF Blog8/3/2026
Recently

Kubeflow SDK evolution- One million downloads and counting

The unified kubeflow-sdk has officially crossed 1 million downloads on PyPI! This milestone reflects the rapid adoption of this streamlined interface. In this post, we celebrate this community milestone and highlight the core concepts driving the...

Why it matters

Read this for the official technical update in Developer Tools / Open Source: The unified kubeflow-sdk has officially crossed 1 million downloads on PyPI!

Official sourceBlog
Original
Developer Tools / Open Source
GitHub Engineering8/4/2026
Recently

Turn one giant AI-generated pull request to a reviewable stack

Instead of one huge, un-reviewable pull request, teach coding agents to decompose work into a clean, ordered stack with GitHub stacked pull requests. The post Turn one giant AI-generated pull request to a reviewable stack appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Instead of one huge, un-reviewable pull request, teach coding agents to decompose work into a clean, ordered stack with GitHub stacked pull requests.

Official sourceEngineeringstacked pull requests
Original
Developer Tools / Open Source
LWN.net8/4/2026
Recently

The beginning of a process-builder API

The recent discussion on "spawn templates" raised questions about whether it was time to provide an alternative to the classic Unix fork()/exec() pattern for process creation. One idea that was raised there was to shift the template pattern into an interface that could be used to efficiently assemble new processes from bare cloth, without duplicating the parent process. Preferably, that interface would be able to implement posix_spawn().

Why it matters

Read this for the concrete reporting in Developer Tools / Open Source: The recent discussion on "spawn templates" raised questions about whether it was time to provide an alternative to the classic Unix fork()/exec() pattern for process creation.

Trusted source
Original

Archived section

Cloud / Infrastructure · 5

Cloud / Infrastructure
Meta Engineering8/5/2026
Recently

From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta's Ads Ranking

Every day, Meta's recommendation platforms handle billions of user interactions, generating rich temporal signals that capture individual preferences and intent across products, ads, and content. ] Read More... The post From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta's Ads Ranking appeared first on Engineering at Meta.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Every day, Meta's recommendation platforms handle billions of user interactions, generating rich temporal signals that capture individual preferences and intent across products, ads, and content.

Official sourceData InfrastructureML Applications
Original
Cloud / Infrastructure
Cloudflare Blog8/4/2026
Recently

How we built a software factory to drive Astro's GitHub issue count to zero

By replacing manual issue verification with isolated AI subagents running in GitHub Actions, the Astro maintainers reduced open issue count by 85%. This post explores the architecture behind automated bug reproduction, patch verification, and preview releases.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: By replacing manual issue verification with isolated AI subagents running in GitHub Actions, the Astro maintainers reduced open issue count by 85%.

Official sourceAgentsAgents Week
Original
Cloud / Infrastructure
CNCF Blog8/6/2026
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LitmusChaos Q1-Q2 2026 update: community, contributions, and project progress

About LitmusChaos LitmusChaos is an open source chaos engineering platform that helps teams identify weaknesses and potential outages in their infrastructure by running controlled chaos experiments. Built on cloud native principles, LitmusChaos enables teams to validate...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: About LitmusChaos LitmusChaos is an open source chaos engineering platform that helps teams identify weaknesses and potential outages in their infrastructure by running controlled chaos experiments.

Official sourceBlog
Original
Cloud / Infrastructure
Cloudflare Blog8/3/2026
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Introducing the Billable Usage API: programmatic cost visibility for Cloudflare

Cloudflare has launched a new Billable Usage API for accounts, giving developers and FinOps teams single-endpoint programmatic visibility into cost and usage across all self-serve products. Built around the FOCUS specification, track spend seamlessly alongside the rest of your cloud stack.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Cloudflare has launched a new Billable Usage API for accounts, giving developers and FinOps teams single-endpoint programmatic visibility into cost and usage across all self-serve products.

Official sourceAgents WeekAPI
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Cloud / Infrastructure
AWS Blog8/5/2026
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Amazon DynamoDB now supports real-time vector search at any scale

DynamoDB now supports native vector search with single-digit millisecond latency at 99%+ recall. It is designed for any scale, even trillions of vectors and requires zero infrastructure management.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: DynamoDB now supports native vector search with single-digit millisecond latency at 99%+ recall.

Official sourceAmazon DynamoDBAnnouncements
Original