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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 · 1

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Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/27/2026
Recently

ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding

Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric challenge: models must absorb knowledge from heterogeneous 2D and 3D medical images, and evaluation protocols must align with radiologists' clinical practice and provide an accurate, fine-grained and factualness-driven assessment. In this paper, we introduce ClinFusion, a vision-centric MLLM designed for holistic medical understanding that systematically addresses these limitations. We propose a compositional and cascaded vision encoder architecture featuring a Cascade Spatial-Aware Locality Fusion operator that unifies diverse 2D and native 3D medical image understanding within a fused encoder. Authors: Hangjie Yuan, Yichen Qian, Zhiwei Tang.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric challenge: models must absorb knowledge from heterogeneous 2D and 3D medical images, and evaluation protocols must align with radiologists' clinical practice and provide an accurate, fine-grained and factualness-driven assessment.

Primary paperarxivcs.CV
Original
Artificial Intelligence / Machine Learning
IEEE Spectrum7/27/2026
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Why AI-Driven Cognitive Systems Are Redefining Radar and Electronic Warfare

An overview of how mode-agile threats challenge static library radar/EW systems, and how AI/ML cognitive architectures enable adaptive, real-time countermeasures. What Attendees will Learn Why mode-agile threats render static library systems ineffective — Explore how wartime reserve modes and mode-agile emitters deploy unexpected frequencies, modulation techniques, and hopping schemes that cannot be matched against traditional threat databases, leaving legacy electronic protect, attack, and support systems unable to respond. How AI/ML techniques power cognitive radar/EW systems — Understand the roles of artificial neural networks (ANN), deep neural networks (DNN), fuzzy logic, and genetic algorithms in enabling autonomous threat classification, signal de-interleaving, and real-time countermeasure generation without human intervention.

Why it matters

Read this for the concrete reporting in Artificial Intelligence / Machine Learning: An overview of how mode-agile threats challenge static library radar/EW systems, and how AI/ML cognitive architectures enable adaptive, real-time countermeasures.

Trusted sourceType-whitepaperElectronic-warfare
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Artificial Intelligence / Machine Learning
NVIDIA Technical Blog7/27/2026
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NVIDIA Ising Enables Fully Automated Quantum Computer Calibration with Enhanced In-Context Learning

NVIDIA Ising Calibration is an open source vision language model (VLM) designed to interpret diagnostic outputs from quantum processors and determine how they... NVIDIA Ising Calibration is an open source vision language model (VLM) designed to interpret diagnostic outputs from quantum processors and determine how they should be tuned to continue operating. 5, which advances AI-based QPU calibration by analyzing unfamiliar diagnostic results without prior training examples.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: NVIDIA Ising Calibration is an open source vision language model (VLM) designed to interpret diagnostic outputs from quantum processors and determine how they...

Official source
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Artificial Intelligence / Machine Learning
NVIDIA Technical Blog7/27/2026
Recently

Six Agent Harness Capabilities for Higher Model Performance

Building a great AI agent isn't just about choosing the right models. The harness is the architecture surrounding the model. How it renders context, executes...

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: Building a great AI agent isn't just about choosing the right models.

Official source
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Artificial Intelligence / Machine Learning
Apple Machine Learning Research7/26/2026
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GH-ESD: Grounded Hypothesis-Driven Error Slice Discovery for Instance-Level Vision Tasks

Systematic failures of vision models on semantically coherent subsets, known as error slices, reveal limitations in robustness and evaluation. Existing slice discovery approaches largely model slices as clusters in representation space or combinations of predefined attributes. While effective for image-level classification, such formulations are insufficient for instance-level tasks such as object detection and segmentation, where failures often arise from contextual relational and spatially grounded visual patterns.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: Systematic failures of vision models on semantically coherent subsets, known as error slices, reveal limitations in robustness and evaluation.

Official source
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Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/27/2026
Recently

A corrective agentic hybrid RAG and an operations-grounded evaluation for a scientific facility

Scientific user facilities accumulate decades of operational knowledge that no single search index covers: electronic logbooks, technical documents, internal wikis, operations chat messages, maintenance records, and live control-system data. We present APS-RAG, Advanced Photon Source Retrieval Augmented Generation, a deployed platform that makes the institutional knowledge at the Advanced Photon Source (APS) accessible to staff through natural-language queries, along with an operations-grounded evaluation. The retrieval engine fuses dense, sparse, and knowledge-graph (KG) channels with query-type-adaptive reciprocal-rank fusion, adds a corrective agentic loop, and runs a native-tool ReAct executor over a Model Context Protocol (MCP) tooling layer. Authors: Rajat Sainju, Dariusz Jarosz, Hairong Shang.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Scientific user facilities accumulate decades of operational knowledge that no single search index covers: electronic logbooks, technical documents, internal wikis, operations chat messages, maintenance records, and live control-system data.

Primary paperarxivphysics.acc-ph
Original
Automation / Agentic Systems
arXiv7/27/2026
Recently

Explainable Reinforcement Learning via Physics-Aware Policy Distillation

In safety-critical sectors such as robotics and automotive engineering, the deployment of Deep Reinforcement Learning (DRL) is often hindered by the black-box nature of deep neural networks. This lack of transparency poses significant challenges for regulatory compliance and human-agent trust. This paper presents an experimental study aimed at making high-performance continuous control DRL systems interpretable. Authors: Shaker Al-Tamari, Waled Kadour.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: In safety-critical sectors such as robotics and automotive engineering, the deployment of Deep Reinforcement Learning (DRL) is often hindered by the black-box nature of deep neural networks.

Primary paperarxivcs.LG
Original
Automation / Agentic Systems
arXiv7/27/2026
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The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation

Multi-turn long-horizon planning is critical for foundation model agents, yet how to fundamentally improve it remains unclear. Existing models are trained on uncontrollable and opaque Internet data, making it difficult to identify how planning ability is acquired, shaped, and integrated. To address this challenge, we introduce a unified and controlled multi-turn environment that enables precise control. Authors: Tianyi Men, Zhuoran Jin, Kang Liu.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Multi-turn long-horizon planning is critical for foundation model agents, yet how to fundamentally improve it remains unclear.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/27/2026
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Looping Is Not Reliability: State-Bound Evidence and Typed Revision Contracts for Agentic Code Repair

Generate--test--revise loops are common in coding agents, but repetition alone provides no reliability guarantee. We study the gap between finding a correct patch and retaining, verifying, and submitting it. A sealed five-seed study over 30 HumanEval repairs produces 900 three-revision trajectories. Authors: Xueping Gao, Jianwei Yang, Qiang Yang.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Generate--test--revise loops are common in coding agents, but repetition alone provides no reliability guarantee.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/27/2026
Recently

Data Pyramid for Embodied Manipulation

Multimodal foundation models learned to see and to speak by consuming the whole internet. Embodied agents admit no such shortcut, since they require data that couple observations with physical states and actions. These signals can be provided, to varying degrees, by multiple data sources. Authors: Yifan Ye, Yankai Fu, Yaoxu Lv.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Multimodal foundation models learned to see and to speak by consuming the whole internet.

Primary paperarxivcs.RO
Original

Archived section

Research Papers · 5

Research Papers
arXiv7/27/2026
Recently

Designing Within the Lines: Practitioners' Perspectives and Visualisation Tool Evaluation in the Arabic Context

Design guidelines and best practices serve as references that support designers throughout the visualisation design process. While considerable effort has identified the elements that contribute to effective data visualisations, little attention has been paid to how language (scripts and reading direction), tool support, and cultural context also shape design decisions. As a result, assumptions of homogeneity persist, with visualisation practices predominantly benefiting users of English and left-to-right (LTR) scripts while overlooking the needs of over two billion Arabic script users. Authors: Muna Alebri, Noëlle Rakotondravony, Yassine Bechqito.

Why it matters

Read this for the paper's specific claim in Research Papers: Design guidelines and best practices serve as references that support designers throughout the visualisation design process.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/27/2026
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Modeling Local Exploit Hazard - A Bayesian Framework for Quantifying Exploit Risk and Operational Efficiency

This paper presents a local exploit hazard model: a Bayesian framework that converts the global probabilities produced by an exploit likelihood model (ELM), such as the Exploit Prediction Scoring System (EPSS), into a daily exploit hazard rate for an organization's own assets. The model measures the exploit-prevention effectiveness of deployed controls as a probability distribution. That distribution is seeded from a subject-matter-expert opinion pool and updated through Beta-Binomial inference from telemetry, breach-and-attack simulation, or penetration testing, then applied to ELM scores by attack-vector alignment. Authors: Stephen Shaffer, Laura Voicu.

Why it matters

Read this for the paper's specific claim in Research Papers: presents a local exploit hazard model: a Bayesian framework that converts the global probabilities produced by an exploit likelihood model (ELM), such as the Exploit Prediction Scoring System (EPSS), into a daily exploit hazard rate for an organization's own assets.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/27/2026
Recently

Characterizing In-the-Wild Personal Listening Device Use to Inform Earable Application Design

Ear-worn devices are evolving from audio-playback tools into sensing platforms for health, interaction, and context-awareness. Yet, earable systems are typically designed and evaluated under strong assumptions about how long, how often, and in which situations people actually wear personal listening devices (PLDs). To ground these assumptions in-the-wild behavior, we combine a survey of 330 adults with multi-year, passively logged headphone audio-exposure records donated via Apple Health by 90 of them. Authors: Supraja Ramesh, Jonas Hummel, Silvia Becker.

Why it matters

Read this for the paper's specific claim in Research Papers: Ear-worn devices are evolving from audio-playback tools into sensing platforms for health, interaction, and context-awareness.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/27/2026
Recently

Make or Take: How Students Navigate Self-Created and Instructor-Provided Cheat Sheets

The use of cheat sheets in exams is often framed as a way to reduce cognitive load and support student performance. However, little is known about how students choose between self-created and instructor-provided cheat sheets, or how these choices relate to their broader approaches to exam preparation. We conducted a longitudinal study in a senior-level undergraduate software requirements course, where students could use either an instructor-provided or a self-created cheat sheet for both the midterm and final exams. Authors: Helen Weixu Chen, Victoria Sakhnini, Lesley Istead.

Why it matters

Read this for the paper's specific claim in Research Papers: The use of cheat sheets in exams is often framed as a way to reduce cognitive load and support student performance.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/27/2026
Recently

Leveling the Playing Field: Temporal Video Segmentation for Individuals with ADHD in Computing Education

Individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) often face significant barriers in computing education. In asynchronous learning environments, instructional videos can impose high extraneous cognitive load, often relying on assumptions about sustained attention and working memory that do not align with ADHD neurocognitive profiles. In this work, we evaluate a post-hoc video processing intervention that segments instructional content into single-instruction chunks followed by fixed-length pauses to reduce cognitive load. Authors: Veronica Pimenova, Chris Lee, Baramee Bhakdibhumi.

Why it matters

Read this for the paper's specific claim in Research Papers: Individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) often face significant barriers in computing education.

Primary paperarxivcs.HC
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/27/2026
Recently

Development of a Handheld Actuation Mechanism for a Tendon-driven Robotically Steered Guidewire

An endovascular intervention begins with a skilled clinician manually navigating a long, slender wire, called a guidewire, to the target location within the vasculature. Due to factors, such as vessel tortuosity and lack of steerability at the guidewire tip, manual navigation of a guidewire could be challenging, potentially resulting in vessel damage, perforation, dissection, and occlusion, as well as postsurgical complications, such as thrombosis. This work details the development of a handheld actuation mechanism for tendon-driven robotic guidewires by utilizing the aforementioned spooling mechanism. Authors: Saima Chavenet, Timothy A. Brumfiel, Revanth Konda.

Why it matters

Read this for the paper's specific claim in Embedded Systems: An endovascular intervention begins with a skilled clinician manually navigating a long, slender wire, called a guidewire, to the target location within the vasculature.

Primary paperarxivcs.RO
Original
Embedded Systems
NVIDIA Technical Blog7/26/2026
Recently

NVIDIA Nemotron 3 Ultra Leads Open Models on Accuracy and Efficiency in Agentic RTL Coding

Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware... Modern chip design is increasingly limited by engineering time.

Why it matters

Read this for the official technical update in Embedded Systems: Modern chip design is increasingly limited by engineering time.

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Original
Embedded Systems
arXiv7/27/2026
Recently

Task-Conditional Faithfulness Auditing of Multimodal LLMs for Grid Diagnosis

Multimodal large language models (LLMs) can combine topology, measurements, and incident text for grid diagnosis, yet answer accuracy does not establish that task-appropriate evidence was used. This letter proposes a general framework in order to conduct task-conditional faithfulness audit. It compares self-reported reliance, intervention-derived behavioral reliance, and preregistered engineering importance. Authors: Tianqiao Zhao, Meng Yue, Jianhui Wang.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Multimodal large language models (LLMs) can combine topology, measurements, and incident text for grid diagnosis, yet answer accuracy does not establish that task-appropriate evidence was used.

Primary paperarxivcs.AI
Original
Embedded Systems
Hackster.io7/25/2026
Recently

FalconS1 Pro Brings Fast, Local Edge AI to Industrial Automation

Industrial AI workloads often require fast, reliable decision-making without relying on cloud connectivity. But bringing these systems online is challenging because many embedded platforms still force developers to stitch together hardware, software, and deployment tools on their own. FalconS1 Pro aims to simplify that process by combining an industrial-focused hardware platform with an integrated software ecosystem designed to make deploying AI models at the edge far easier.

Why it matters

Read this for the engineering context in Embedded Systems: Industrial AI workloads often require fast, reliable decision-making without relying on cloud connectivity.

Trusted source
Original
Embedded Systems
Hackaday7/27/2026
Recently

A Labour Of Love Brings A Kids Book To The Spectrum

Back in the early 1980s when 8-bit home computers became affordable educational toys for children, the traditional paper publishing industry did its best to keep up.

Why it matters

Read this for the engineering context in Embedded Systems: Back in the early 1980s when 8-bit home computers became affordable educational toys for children, the traditional paper publishing industry did its best to keep up.

Trusted sourceRetrocomputing1980's
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Archived section

Computer Systems · 5

Computer Systems
arXiv7/27/2026
Recently

A Heterogeneous Neural Network Accelerator for End-to-End Multitask RF Signal Recognition

This paper presents a heterogeneous neural network accelerator for multi-task RF signal recognition, supporting automatic modulation recognition (AMR), hardware-Trojan covert channel (HT-CC) detection, and GNSS jamming classification. We introduce a compact attention-enhanced convolutional neural network (CNN) combined with LSDec, a learnable streaming decimator that enables adaptive temporal downsampling and flexible input lengths. The hardware architecture integrates a novel dual-pipeline, fused convolution-pooling engine with DMA-based streaming to minimize memory traffic and latency. Authors: Zhifan Song, Haralampos-G. Stratigopoulos, Hassan Aboushady.

Why it matters

Read this for the paper's specific claim in Computer Systems: presents a heterogeneous neural network accelerator for multi-task RF signal recognition, supporting automatic modulation recognition (AMR), hardware-Trojan covert channel (HT-CC) detection, and GNSS jamming classification.

Primary paperarxivcs.AR
Original
Computer Systems
arXiv7/27/2026
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Denial of Deadline: Network-Driven Accuracy Collapse in Distributed Inference Pipelines

Inference systems increasingly combine a fast path that returns predictions within the application's latency deadline together with a higher-accuracy slow path that runs higher-compute methods on stronger, remote hardware, so its results can be returned on time and combined with the fast path predictions. Across several application domains, we abstract this inference architecture as a fast path, a slow path, and a coordination layer with two functions: a router that invokes the slow path and a merger that decides whether to incorporate its returned predictions., Yo-Yo bursts, can exploit contention at shared resources along the slow path to push benign users' slow-path predictions past their latency deadlines. Authors: Jhonatan Tavori, Gur-Eyal Sela, Ion Stoica.

Why it matters

Read this for the paper's specific claim in Computer Systems: Inference systems increasingly combine a fast path that returns predictions within the application's latency deadline together with a higher-accuracy slow path that runs higher-compute methods on stronger, remote hardware, so its results can be returned on time and combined with the fast path predictions.

Primary paperarxivcs.NI
Original
Computer Systems
arXiv7/27/2026
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Certified Parallel-in-Time Sinkhorn for Dynamic Entropic Optimal Transport

Dynamic applications, including optimal-transport Flow Matching, repeatedly solve related entropic optimal transport problems, yet conventional distributed Sinkhorn processes frames sequentially and synchronizes after every iteration. We present TemporalSinkhorn, a parallel-in-time executor that batches future candidates and their repairs without making output accuracy speculative. A centered, row-sharded certificate accepts only a deterministic safe prefix. Authors: Xinyang Wen.

Why it matters

Read this for the paper's specific claim in Computer Systems: Dynamic applications, including optimal-transport Flow Matching, repeatedly solve related entropic optimal transport problems, yet conventional distributed Sinkhorn processes frames sequentially and synchronizes after every iteration.

Primary paperarxivcs.DC
Original
Computer Systems
LWN.net7/27/2026
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Hazard pointers for the kernel

The kernel's read-copy-update (RCU) subsystem ensures that data will not be deleted until it is known that there are no threads holding references to it. RCU works well and is widely used throughout the kernel, but it can increase memory use and add significant delays before unused kernel objects are cleaned up. Hazard pointers are an alternative approach to lockless data updates that offers better performance, for some situations at least.

Why it matters

Read this for the concrete reporting in Computer Systems: The kernel's read-copy-update (RCU) subsystem ensures that data will not be deleted until it is known that there are no threads holding references to it.

Trusted source
Original
Computer Systems
LWN.net7/26/2026
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Kernel prepatch 7.2-rc5

2-rc5 kernel prepatch is out for testing. Linus said: "So it's a bit too big for my liking, but nothing in there strikes me as particularly strange or scary".

Why it matters

Read this for the concrete reporting in Computer Systems: Linus said: "So it's a bit too big for my liking, but nothing in there strikes me as particularly strange or scary".

Trusted source
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Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
Vercel Blog7/27/2026
Recently

DeepsecBench: evaluating model performance in finding cybersecurity vulnerabilities

Last week, OpenAI evaluated two models on an exploit benchmark within an isolated sandbox. Guardrails were reduced for testing, and the models found a vulnerability in their environment, accessed the internet, and reached Hugging Face's production database. No human directed the action, but the breach is a clear example of how much more capable malicious attackers are when equipped with powerful AI models.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Last week, OpenAI evaluated two models on an exploit benchmark within an isolated sandbox.

Official source
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Developer Tools / Open Source
arXiv7/27/2026
Recently

Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review

Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand. Developers struggle to assess the validity of LLM-generated reviews, making it difficult to gauge how much trust to place in them. The role of Explainable AI (XAI) in code review and its impact on trust remain underexplored. Authors: Zhenhan Gao, Marvin Muñoz Barón, Umm-e Habiba.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
arXiv7/27/2026
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Verification-Conditioned Use: A Qualitative Study on How Generative AI Reshapes Learning, Autonomy, and Market Entry for Junior Software Developers

Objective: to investigate how the use of generative Artificial Intelligence (AI) tools affects the early stages of a career in software development, from the perspective of the newcomers themselves. Method: thirteen interns and junior developers were interviewed individually, by videoconference. Interviews were analyzed using the six phases of Braun and Clarke's thematic analysis, with inductive coding and a semantic approach. Authors: Pedro Henrique Andriotte, Danilo Monteiro Ribeiro.

Why it matters

Read this for the paper's specific claim in Developer Tools / Open Source: Objective: to investigate how the use of generative Artificial Intelligence (AI) tools affects the early stages of a career in software development, from the perspective of the newcomers themselves.

Primary paperarxivcs.SE
Original
Developer Tools / Open Source
Vercel Blog7/26/2026
Recently

Run Claude Managed Agents with Chat SDK

Claude Managed AgentsChat SDK Claude Managed Agents handles the agent loop server-side, including the model, tools, session state, and sandboxed web research. Chat SDK gives that agent a chat interface through a single type-safe handler, with adapters that carry it to Slack, WhatsApp, and more. To see it work, a new builds a working research analyst you chat with in the browser.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Claude Managed AgentsChat SDK Claude Managed Agents handles the agent loop server-side, including the model, tools, session state, and sandboxed web research.

Official source
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Developer Tools / Open Source
Vercel Blog7/26/2026
Recently

WebSocket support for OpenAI Responses API live on AI Gateway

now supports WebSocket mode for the OpenAI Responses API. OpenAI reports The Responses route opens at and accepts raw frames over a persistent WebSocket connection.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: now supports WebSocket mode for the OpenAI Responses API.

Official source
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Archived section

Cloud / Infrastructure · 1

Cloud / Infrastructure
AWS Blog7/27/2026
Recently

AWS Weekly Roundup: Local Zone in Athens, Claude Opus 5 on AWS, Lambda durable execution for.NET, and more (July 27, 2026)

Last week I had the privilege of spending three days in São Paulo with technical builders from across Latin America, brought together for a regional tech event full of deep-dive sessions, hands-on workshops, and conversations with customers and partners.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Last week I had the privilege of spending three days in São Paulo with technical builders from across Latin America, brought together for a regional tech event full of deep-dive sessions, hands-on workshops, and conversations with customers and partners.

Official sourceAmazon BedrockAmazon Bedrock AgentCore
Original