The Git Times

OpenClaw's v2026.4.24 release integrates Google Meet as a first-party participant plugin. The assistant can now join meetings using personal Google authentication, handling realtime sessions through Chrome or Twilio with paired-node support. New recovery tooling repairs already-open Meet tabs, while artifact and attendance exports run automatically.

Realtime voice loops for Talk, Voice Call and Google Meet now consult the full OpenClaw agent, enabling tool-backed answers during live conversations. Browser automation gains coordinate clicks, longer action budgets, per-profile headless overrides and steadier tab reuse.

The model catalog adds DeepSeek V4 Flash and V4 Pro; V4 Flash is the new onboarding default. Fixes to thinking and replay behavior produce more consistent follow-up turns after tool calls. Startup performance improves via static model catalogs, manifest-backed rows, lazy provider dependencies and external runtime repair for packaged installs.

A breaking change removes the Pi-only api.registerEmbeddedExtensionFactory(...) path. Plugin authors must now declare transforms with api.registerAgentToolResultMiddleware(...) and contracts.agentToolResultMiddleware to ensure consistent behavior across harnesses.

The update reinforces OpenClaw's local-first design, letting builders run a fast, always-on personal assistant across macOS, Linux and Windows while retaining full data ownership.

The Robotics Knowledgebase received its largest content expansion in two years following an April 2026 update that added 18 new articles on drone integration and modern fabrication methods. The CMU-linked open wiki continues to capture the “tribal knowledge” required to move robotic systems from theory to working hardware—details routinely omitted from textbooks and vendor manuals.

The site maintains a strict systems-based approach. Instead of isolated component tutorials, entries demonstrate how sensing, actuation, programming, and navigation layers interact in deployed robots. New material covers sensor fusion pipelines for UAVs, reliable motor control under variable loads, and integration patterns for ROS2 navigation stacks.

Contributors follow a precise workflow. They copy the Markdown template from /_templates/template.md, save files in kebab-case within the appropriate /wiki subdirectory, and use absolute paths for all images and cross-references. Every addition requires edits to _data/navigation.yml and the parent category’s index.md. Local preview uses a rbenv-managed Ruby environment and Bundler, allowing authors to verify layout and links before submitting pull requests.

As commercial and hobbyist interest in autonomous drones accelerates, these concrete implementation notes have become essential references for builders who need systems that survive real-world conditions rather than lab demonstrations.

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ros2_control remains the standard backbone for robot control under ROS 2. Its recent branch for the Kilted distribution keeps the framework synchronized with upstream releases, ensuring teams can deploy consistent hardware interfaces without rewriting controller logic.

Written in C++, the package separates hardware drivers from control algorithms through a standardized controller manager. It loads, activates and updates controllers at real-time frequencies while handling parameter passing, state monitoring and lifecycle events. The architecture supports everything from single-joint PID loops to multi-axis trajectory execution using uniform ROS 2 interfaces.

Maintenance across four active distributions—Humble, Jazzy, Kilted and Rolling—demonstrates sustained community and corporate investment, with contributors acknowledged at control.ros.org. Green build status and updated API documentation for each branch reduce integration friction as more production systems migrate from ROS 1.

Published Docker images (ghcr.io/ros-controls/ros2_control_release and source variants) let developers bypass compilation for rapid prototyping or CI pipelines. The project’s open contribution model continues to welcome hardware support patches and controller improvements, sustaining eight years of incremental refinement without unnecessary complexity.

As robotics scales into commercial automation, ros2_control’s focus on modularity and real-time safety matters now more than ever.

eProsima has released Fast DDS v3.6.1, a maintenance update that resolves outstanding build and documentation problems in the C++ DDS implementation.

The new version applies an SQLite3 patch to eliminate const-related compilation failures, removes deprecated Doxygen warnings, and corrects errors that prevented clean builds on Ubuntu Focal. These changes, delivered through four merged pull requests, improve reliability for developers maintaining long-running deployments without altering core RTPS behavior.

First released in 2014, Fast DDS implements the OMG DDS standard and its underlying RTPS wire protocol. It delivers configurable best-effort and reliable publish-subscribe communications over UDP and other transports, automatic participant discovery, and interchangeable transport layers. The library exposes two API layers: a high-level Publisher-Subscriber interface for rapid development and a lower-level Writer-Reader interface granting direct access to protocol internals.

The middleware remains the default choice for ROS 2 long-term support releases, powering deterministic data distribution across robot fleets, autonomous vehicles, and industrial automation systems. Its modularity has also secured adoption inside the FIWARE robotics catalogue for European Union research projects.

Commercial support is available by contacting info@eprosima.com. With this release the project continues to maintain the stability required by organizations that treat distributed real-time communications as critical infrastructure.

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Recent updates to OWASP/CheatSheetSeries address evolving threats in cloud environments and API architectures. The repository contains the Markdown source files that power the official cheat sheet website.

These working documents receive regular refinements from a global contributor base. The project website offers the polished version suitable for reference, while GitHub tracks issues and pull requests.

Leaders Jim Manico, Jakub Maćkowski and Shlomo Zalman Heigh, with core member Kevin W. Wall, manage the initiative. They invite fresh contributions via a comprehensive guide and Slack discussions in the OWASP workspace.

The build process uses Python tools. Developers run make install-python-requirements then make generate-site followed by make serve to test changes locally on port 8000. NPM scripts enable Markdown and terminology linting with automatic fixes.

The revisions matter now because modern application designs create new attack vectors daily. Cheat sheets translate standards into checklists, code snippets and configuration examples that teams can adopt quickly.

Radare2 has released version 6.1.4, codenamed CottonMouse. The update delivers 340 commits from 20 contributors, including developers from the Frida project, and concentrates on the analysis engine.

Core changes include using a dash for the callargs modifier and improved support for rnum expressions. The aCe and aCf commands have been reworked for more accurate function and control-flow handling. These tweaks address long-standing pain points for users who live in the terminal.

The framework itself needs no introduction to security practitioners. It remains a complete Unix-oriented toolset for dissecting, emulating, debugging, patching and scripting binaries. Local files, kernel memory and remote gdb or windbg sessions are all first-class targets. Wide architecture support and an embedded JavaScript interpreter keep it flexible.

Plugin extensibility via r2pm continues to differentiate the project. Current standouts are r2ai, which runs Llama models locally inside r2 sessions for AI-assisted reversing, iaito for a Qt graphical interface, and r2dec for JavaScript decompilation. Installation follows the familiar git clone then sys/install.sh path, with meson and make both supported.

Fourteen years after its initial commit, the 6.1.4 release shows radare2’s maintainers remain focused on concrete improvements rather than reinvention. For builders who prefer command-line precision over GUI abstraction, the updates matter.

The community-scripts/ProxmoxVE repository shipped its latest release on April 26, introducing meaningful refinements to its one-command installation toolkit for Proxmox VE.

The most visible change raises Frigate’s default CPU allocation from four to eight cores. Maintainers cited the growing demands of its real-time object detection, giving users better out-of-the-box performance for home surveillance workloads without manual tuning.

A new TREK script joins the catalog, while several existing tools received targeted fixes. The 2FAuth updater now correctly manages stale backup directories, Technitium DNS ensures required paths exist before service start, and a core correction improves deb822 repository detection on recent Proxmox 9.x hosts.

These updates reflect steady iteration rather than reinvention. The project’s established pattern remains: paste a command from community-scripts.org, choose Default or Advanced mode, and receive a container or VM with sensible presets or full customization. Post-install helpers stay accessible from the Proxmox shell for routine maintenance.

For administrators running Proxmox 8.4 through 9.1, the collection continues to compress days of configuration into minutes while incorporating feedback from active self-hosting communities. The changes are small, practical, and immediately useful to anyone already relying on the scripts for consistent homelab infrastructure.

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The maintainers of frp shipped version 0.68.1 to address a configuration-dependent authentication bypass. The flaw appeared in type = "http" proxies when routeByHTTPUser was used together with httpUser or httpPassword. Proxy-style requests could previously succeed despite failed authentication; the fix now returns 407 Proxy Authentication Required.

frp remains a reliable reverse proxy for exposing local servers behind NAT or firewalls. Written in Go, it forwards TCP, UDP, HTTP and HTTPS traffic, routes requests to internal services by domain name, and offers a P2P connection mode that avoids permanent intermediary servers.

The release focuses on hardening rather than new features. Existing capabilities include TLS termination, hot-reloading of frpc configuration without restart, per-proxy bandwidth limits, TCP stream multiplexing, dynamic proxy management at runtime, and a server dashboard with Prometheus metrics export. Token and OIDC authentication methods are supported alongside strict port whitelisting on the server side.

For teams operating production tunnels, the update eliminates a realistic attack vector at the intersection of multiple authentication settings. Administrators running exposed HTTP services should apply the patch promptly. The project, first released in 2015, continues steady maintenance that keeps it viable for secure infrastructure traversal a decade later.

Fuel Core v0.48.0 brings targeted production improvements to the Rust full node implementation of the Fuel v2 protocol. The update focuses on reliability, data persistence and operational tooling rather than headline features.

Key additions include FailoverTransport, which automatically retries GraphQL queries across multiple endpoints, and a quorum provider that strengthens RPC client behavior. An adapter for storing blocks on AWS S3 buckets gives node operators scalable off-chain storage options. The backup tool is now built in as an archive subcommand, simplifying long-term data management.

The release also ships a protobuf API for the block aggregator, complete coverage of proto block types, and integration tests verifying correct transaction indexing for pre-confirmations. Maintenance updates bump the Rust toolchain to 1.93.0 and refresh dependencies.

Three breaking changes accompany the new code: only the first RPC URL is now used by the relayer server, transaction indexing inside pre-confirmations has been corrected, and certain native block production paths were adjusted.

Networks currently run slightly older binaries—Ignition and Testnet on 0.47.1, Devnet on 0.47.2—suggesting an orderly upgrade path ahead. For contributors, the project still requires source ci_checks.sh before pull requests and recommends cargo xtask build for development.

These changes matter now because Fuel’s modular execution layer continues to attract infrastructure teams seeking higher throughput than traditional EVM chains while demanding enterprise-grade node software.

Faiss 1.14.1, released in March 2026, delivers concrete engineering improvements to Meta's long-standing library for similarity search and clustering of dense vectors. The update integrates SVS v0.2.0 with LeanVec out-of-distribution support, adds a Hadamard transformation as an IVF index, and exposes IndexBinaryFlat to the C API. SIMD optimizations now accelerate multi-bit RaBitQ inner products, while Python builds extend to 3.13 and 3.14.

The library remains written in C++ with complete Python/numpy wrappers and GPU implementations. It handles vector sets too large for RAM through compressed binary codes and compact quantization, trading some precision for scale. Methods such as HNSW and NSG overlay indexing structures on raw vectors; GPU indexes serve as drop-in replacements for CPU equivalents like IndexFlatL2, with automatic memory movement.

Supporting code for evaluation and parameter tuning is unchanged. The release also fixes SWIG 4.4 initialization, corrects squared-distance handling in RaBitQ, and removes outdated conda-forge documentation. These changes refine an established tool that powers retrieval pipelines processing billions of embeddings on single servers, keeping pace with expanding embedding model sizes and tighter latency requirements in production AI systems.

Node Feature Discovery v0.18.3 now ships official container images for ppc64le and s390x, enabling consistent hardware detection on IBM Power and zSystems alongside existing x86_64 and ARM64 support. The update removes the need for custom builds when running NFD in heterogeneous enterprise clusters.

The tool scans nodes for CPUID flags, cache topology, RDT capabilities, memory bandwidth and other hardware traits, then attaches standardized labels such as feature.node.kubernetes.io/cpu-cpuid.AESNI. Kubernetes schedulers and admission controllers consume these labels to place workloads on suitable hardware without manual intervention.

Installation follows the established pattern. The Helm chart can be deployed with:

helm install -n node-feature-discovery --create-namespace nfd oci://registry.k8s.io/nfd/charts/node-feature-discovery --version 0.18.3

Kustomize users pin the same v0.18.3 tag. Post-installation, node metadata immediately reflects detected features.

The release also corrects the test subcommand of the kubectl-nfd plugin, restoring reliable validation during rollout. Maintained by SIG Node, the project continues to narrow the gap between raw hardware capabilities and cloud-native scheduling policies. As organizations consolidate AI, HPC and legacy workloads onto unified Kubernetes fleets, architecture-agnostic feature detection becomes table stakes rather than a niche capability.

NFD lets operators treat diverse silicon as a programmable resource instead of a management headache.

PMSG has refreshed its AI-guided setup system, giving builders faster routes to personalized firmware on Seeed Studio XIAO hardware. Two years after its initial release, the project now directs users to pre-configured prompts in multiple AI assistants. Developers specify their exact XIAO variant—identified via USB-C board queries—and any attached I²C sensors. The AI then supplies concrete steps for BLE stacks, LED drivers, vibration motor control, and sensor fusion.

The repository centers on PlatformIO with dedicated JSON manifests in /ai/mcp/ that instruct agents to respect pinouts. An Embedded Swift workspace targets Apple developers, enabling Xcode workflows and potential future ties to Apple Intelligence features. Documentation stresses the absence of vendor lock-in: users flash exactly what they want, modify at will, and retain full ownership of both hardware and code.

This matters now as demand grows for privacy-focused, modifiable face computers. The ability to test competing AI assistants against the same hardware yields alternative implementations, accelerating iteration. Creator Paul Stefaan Mooij’s Hitchhiker’s Guide references—“Don’t forget your towel” and “42 is the answer”—remain baked into the setup flow as practical memory aids during complex configuration.

The net effect is a tighter feedback loop between idea and wearable prototype, keeping PMSG relevant in an increasingly crowded AI-hardware landscape.

Tinymovr has released firmware 2.6.1, tightening its field-oriented control implementation for brushless motors. The chief improvement cuts the position-mode control loop from roughly 2880 to 2464 cycles, enabling faster response without hardware changes.

Developers corrected a homing planner flaw that caused incorrect retraction distances on subsequent runs after boot. The update now properly references sensor-frame values instead of user-frame estimates. Homing configuration is also persisted to non-volatile memory, preventing loss after power cycles.

Additional changes address calibration frequency instability linked to flash cache behavior, expand Hall sensor documentation, and add velocity control tests for Hall feedback. Copyright notices were updated following the project's transfer to MotionLayer P.C.

The compact controller integrates FOC, an absolute encoder and CAN bus on a single board built around the PAC5527 MCU. The repository supplies the C firmware, Tinymovr Studio client library, hardware design files and Sphinx documentation. Development continues on the develop branch while main tracks stable releases. Contributors must review SAFETY.md before modifying safety-critical sections.

For teams already using Tinymovr, version 2.6.1 improves reliability and performance in precision motion tasks while maintaining drop-in compatibility.

**

O3DE has shipped version 25.10.2, an incremental update that refines stability and tool integration for its Apache 2.0-licensed 3D engine. The release follows 25.10.1 with targeted fixes and compatibility improvements, as outlined in the project's changelog.

Five years after its initial open-source debut, the engine continues to deliver production-grade capabilities without fees or commercial obligations. Developers and content creators use it to build AAA games, cinema-quality 3D worlds, and physics-heavy simulations across Windows and other platforms. Its C++ foundation supports real-time rendering, animation systems, and modular extension through Gems.

Setup remains deliberate. Teams must first install Git LFS, clone the o3de/o3de repository, then satisfy strict build requirements: Visual Studio 2019 16.9.2 or later with the Game Development with C++ workload, MSVC v142, the 2019 redistributable, and CMake 3.24.0 minimum. Optional Wwise integration adds professional audio tools.

The public roadmap tracks forthcoming features, ensuring transparency. For organizations wary of proprietary licensing models, the latest release reinforces O3DE's position as a mature, community-driven alternative that prioritizes ownership and technical flexibility over ease of entry. The engine's modular design lets teams include only the systems they need, keeping builds lean while retaining AAA-scale performance.

Valve has shipped v1.4.1 of GameNetworkingSockets, introducing a native ICE client that allows peer-to-peer networking without WebRTC dependencies. The new client is currently beta, disabled by default unless WebRTC support is compiled out, and does not yet implement TURN.

The release also tightens the protocol. A bug in malicious sender protection that could trigger asserts or drop reliable messages under extreme packet loss and latency has been corrected. Polling now uses epoll on Linux and compatible platforms. IPv6 address parsing accepts dotted-decimal IPv4-mapped formats, public headers no longer pollute the namespace with a POSIX define, and several console platform compatibility issues were resolved. No public interfaces changed.

The library itself remains a battle-tested transport layer for games. It delivers a connection-oriented API over UDP that supports both reliable and unreliable messages, robust fragmentation and reassembly, and an ack-vector reliability system drawn from DCCP and Google QUIC. AES-GCM-256 encryption with Curve25519 key exchange protects every packet. Multiple message streams, or “lanes,” can share bandwidth under priority or weight controls via ConfigureConnectionLanes.

Head-of-line blocking is minimized, NAT traversal is built in, and the ISteamNetworkingMessages interface eases migration from raw UDP code. Eight years after its initial open-source release, the project continues to ship targeted improvements that matter to developers shipping multiplayer titles on Windows, Linux, and consoles.

gdgs brings 3D Gaussian Splatting rendering to the Godot Engine through a dedicated plugin. Instead of triangle meshes, the technique represents scenes as millions of 3D Gaussians that can be reconstructed and rendered at high visual fidelity in real time.

The plugin supplies import and resource handling for supported Gaussian formats, a GaussianSplatNode for scene placement, and a CompositorEffect that blends splats with Godot's standard 3D content. It reads the scene depth buffer to produce correct occlusion between Gaussian elements and conventional geometry.

Version 2.2.0 adds editor icons, visibility propagation so nodes respect runtime and editor toggles, instancing that lets multiple nodes share the same GPU data without repeated uploads, and corrected VR rendering using proper eye-offset view-projection matrices. The system requires Godot 4.4 or newer, the Forward Plus backend, and a desktop GPU with compute shader support.

By filling the gap in Godot's native pipeline, the plugin lets developers incorporate captured real-world environments directly into interactive applications while maintaining hybrid composition with existing Godot workflows. Showcases demonstrate roughly six million points rendered alongside conventional game elements without leaving the editor ecosystem.

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