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The paper presents SNAP3D, a physics‑guided pipeline that converts a single image into a set of 3D parts that can be assembled without interpenetration. By using simulation‑driven connector placement and a new physics‑based evaluation, the method yields assemblies that are both geometrically accurate and stable enough for 3D printing.
Arduino’s blog spotlights a community‑built robotic arm that’s been mechanically redesigned for cheaper parts, easier 3‑D printing, and better performance. The arm uses a Nano ESP32 to read potentiometer‑based puppet‑style input and drive servos via a driver board, with belt‑driven wrist and rack‑and‑pinion gripper upgrades.
Microsoft released Windows 11 24H2/25H2 Release Preview builds 26100.9539/26200.9539. The update ships via gradual or normal rollout and adds UI tweaks (File Explorer preview pane, Home state, thumbnail reliability), Emoji 17.0 support, a new Tips widget, extensive personalization background fixes, Bluetooth UI/audio stability improvements, accessibility “Open apps maximized”, refreshed Magnifier…
AI‑generated code breaks the traditional chain of ownership: developers merge PRs they didn’t write, reviewers approve logic they didn’t originate, and QA validates tests chosen by a model. A CloudBees survey shows 81% of firms see more production failures from AI code, and accountability often drifts upward to CTO/VP. The post argues role‑based accountability isn’t enough; you need end‑to‑end tr…
A CloudBees blog post argues that existing CI, security, and QA tools don’t give release managers a complete view of AI‑generated code risk. It claims tool consolidation rarely helps and proposes a “control plane” (CloudBees Unify) that aggregates signals from multiple tools and adds AI‑driven test prioritization. The piece is largely promotional, with no concrete implementation details, metrics,…
The paper defines recursive self‑improvement (RSI) for AI, introduces the Headroom‑Closed Index to expose current LLM limits, and proposes a staged roadmap toward full RSI. It surveys application scenarios and outlines practical challenges.
COBRA‑Skills uses a contextual‑bandit loop to selectively evaluate and evolve LLM agent skills, achieving better performance with roughly half the evaluation cost of prior methods. The framework works with limited examples and remains robust across different agent setups and even when the target model creates its own skills.
The paper shows that the Fisher‑Rao geometry of next‑token probabilities is largely shared across transformer, state‑space and recurrent LLMs, and that this shared geometry can be used to design low‑disturbance interventions that steer model behavior. Experiments demonstrate that geometry predicts semantic transfer, fact acquisition, and enables reusable control better than Euclidean methods.
Benchmark Radar is a continuously updated database and search engine that aggregates AI benchmark papers, datasets, and scores from 37 sources into a searchable catalog. It offers a web dashboard, CLI, and analysis of benchmark saturation to help LLM developers find and compare evaluations.
Manivannan built a smart boxing band using the Arduino Nesso N1, a pulse sensor, and an Edge Impulse‑trained model to recognize punches and display heart‑rate‑based feedback. The standalone device logs biometric and motion data for post‑training analysis.
Thunderbird’s Automation Team rewrote 250+ settings strings to plain language, ran user tests with new copy on Notifications, Appearance, and Composition, and achieved >80% comprehension and high confidence, though interaction mismatches remain.
Deezer built QAradar, a workflow‑driven Slack‑bot that lets developers discover and run the exact automated tests covering their feature. By pre‑generating a clean test catalog and keeping the LLM in a fixed four‑step workflow, they avoided the complexity and cost of a full‑blown agent while dramatically reducing knowledge silos and friction for QA and developers.
This issue of *This Week in Rust* (Sept 9 2026) aggregates community news, recent Rust releases, notable blog posts, a “crate of the week” (tokio‑rcu), and a long list of merged PRs across the compiler, std, Cargo, rustdoc, rustfmt, Clippy and rust‑analyzer. The most concrete technical highlight is the tokio‑rcu crate, an async‑aware userspace RCU implementation built on Tokio.
The paper proposes a Program‑Solve interface where LLMs emit Python code that a sandboxed executor runs, making arithmetic deterministic for clinical calculators. Experiments show the approach boosts a 32B model’s accuracy on a verified benchmark, but coverage and upstream extraction remain limiting factors.
Temporal’s Serverless Workers let you replace always‑on Kubernetes Workers with on‑demand Lambda invocations. The guide shows how to add a Lambda handler, configure worker versioning, tune shutdown timeouts for long‑running activities, package dependencies for Lambda, and deploy the function, keeping workflow and activity code unchanged.
LLaDA‑UI is a 16.7 B‑parameter Mixture‑of‑Experts vision‑language model that uses block‑wise diffusion to generate GUI actions in parallel. It achieves state‑of‑the‑art performance on multiple GUI grounding and navigation benchmarks, beating larger Qwen models while keeping decoding latency low.
Codename One adds a permission‑free `ContactPicker` API that uses the Android 17 system contact picker and iOS `CNContactPickerViewController` to let apps request only the specific fields (name, phone, etc.) they need. The picker returns a snapshot `Contact` object without granting broad address‑book access, and the API gracefully falls back on older platforms or unsupported cases.
The post shows how to wire Temporal's Worker Controller with GitHub Actions to automatically build, version, and roll out worker images via Kubernetes. A demo repo illustrates the full CI pipeline and safe version upgrades.
Weekly Firefox automation update covering new @media emulation UI, theme picker tweaks, Picture‑in‑Picture caption support, several WebExtension bug fixes (frameId attribution, startup race), DevTools enhancements (JSONL viewer, screenshot speed‑up, ::checkmark pseudo‑element), and assorted tooling clean‑ups.
Microsoft announced the Windows Age API, a set of platform calls (GetUserAgeRangeAsync, GetAgeVerificationStatusAsync, CheckAgeStatusAsync) that expose age signals from a Microsoft account while preserving privacy. The APIs let Windows apps deliver consistent, age‑appropriate experiences and reuse verified age status, with parental controls now highlighted during device setup.
Microsoft Edge added automated validation checks to its extension review pipeline and now refreshes the Featured badge every 15 days. The changes aim to cut review turnaround while keeping quality standards.
Codename One added a daily automated scan of Apple and Google deprecation notices, linking each notice to concrete builder artifacts before work is created. The system caught the Android 16 back‑gesture change and enabled a permission‑free ContactPicker, turning policy shifts into repeatable, evidence‑backed patches.
Feyospace‑v1 presents a data‑centric training pipeline for cyber‑security agents, combining five systems (Choulea, SkyReal, Hongzwang, PSBreakup, Kreator) to generate and verify 164 k long‑context trajectories across diverse exploit environments. The resulting checkpoints improve baseline performance by ~24% on CyberGym and achieve a 63% verified success rate, ranking top among similarly‑sized op…
Anthropic added an invisible, statistical watermark to Claude’s output to satisfy EU AI‑Act transparency rules. The mark only signals that a model was involved; it doesn’t affect Google rankings, but creators should disclose AI use and avoid bulk unreviewed content.
Codename One adds a one‑time‑code autofill component that leverages iOS, Android, and browser autofill APIs, eliminating the need for SMS‑reading permissions. The new `PhoneVerification` component handles phone entry, code entry, resend timing, and server callbacks, while the UI uses a single hidden editor to back six visual boxes, improving typing, paste, and accessibility. The post explains the…
The paper studies long‑horizon memorization where a language model must learn 100 tasks via continual fine‑tuning without retaining data or task IDs. By composing data, function, and weight anchors with merged LoRA, they boost final retention from 1.2% to 34.9%, a 28× improvement.
Codename One switched its default Mac build from iOS‑Catalyst to a native AppKit port. The new path creates true NSApplication/NSWindow objects with per‑window CAMetalLayer rendering, native menus, text input, multi‑monitor support and accessibility, eliminating the costly image‑copy pipeline of Catalyst and enabling proper desktop window behavior.
Deep Persona is a three‑layer architecture that models LLM personas with hierarchical expression, beliefs, and motivations, and enforces behavior through scripted determinism and bounded agency. The authors also introduce a reference‑free evaluation using psychological instruments, finding that structured personas improve alignment with human dialogue but LLMs still lag in emotion and joint atten…
SkillSpec introduces a Hoare‑style framework that turns heterogeneous agent skill artifacts into a unified graph and reasons about correctness via intent‑masked specifications. In a study of 515 real‑world skills it flagged 763 confirmed defects with 61.2% precision, especially exposing intent‑implementation mismatches.
This paper introduces HEAL, a method to identify and mitigate hallucinations in Multimodal Large Language Models (MLLMs). It finds that hallucinations stem from information distribution drift in "synergy heads" within the attention mechanism and proposes dynamic calibration to steer output towards factual evidence.
