David Williams

GeoLibre v2.0.0 is here! GeoLibre is a free and open-source geospatial platform that runs everywhere: as a native desktop app, in the browser, on Android, and embedded right inside Jupyter notebooks. It brings modern web mapping, cloud-native data formats, and a full processing toolbox together in one place, all built on MapLibre and deck.gl with no proprietary lock-in. Our first major release adds a true 3D globe, takes mapping beyond Earth to Mars and the Moon, lets styles round-trip with QGIS, and turns loaded vector layers into editable, save-back-to-source data. What's new in v2.0.0 - Planetary mapping: explore Mars, the Moon, and other bodies with the OpenPlanetaryMap basemaps, a per-project ellipsoid, and a planet switcher right in the Layers panel. - CesiumJS 3D globe: switch any map pane to a photorealistic 3D globe that stays camera-synced with your 2D maps and mirrors the layer stack. - True 3D data: render vector layers with Z coordinates, load TIN/MultiPatch 3D shapefiles, and display KML/KMZ Collada (.dae) 3D models. - Symbology interchange: import and export vector styling as OGC SLD, QGIS QML, and Mapbox GL style JSON, so styles round-trip between GeoLibre, QGIS, and the Mapbox/MapLibre ecosystem. - Editable source layers: edit vector layers and write the changes back to their source, including GeoPackage and GeoJSON files and PostGIS database tables. - Weather and sky: a new Weather menu with live cloud and precipitation radar overlays (RainViewer), plus a Google Earth-style sun position simulation for realistic lighting. - Terrain and lighting: double-click the terrain control to set vertical exaggeration, and view any scene in true 3D relief. - Smarter data import: bring in CSV without coordinates as an attribute table, split GPX track points and route points into separate layers, and load macOS-zipped and projected-CRS shapefiles. - Raster in the browser: build normalized-difference indices for any HTTP COG and extract COG/WMS/XYZ bounding-box subsets client-side. - Field Calculator upgrades: compute geometry length and area directly on your features. - Attribute table: multi-select rows with Ctrl and Shift, plus faster navigation. - Google Earth-style extras: "View in Google Maps / Google Earth" actions, camera-reset keyboard shortcuts, and a UTM easting/northing grid mode for the Gridlines overlay. - New plugins: a Mapillary coverage and street-level image viewer, a Historical Imagery panel, and an Elevation Profile tool. - Fully localized: all 13 language catalogs are complete, so the entire UI is translatable. Try it out - Launch GeoLibre Web: web.geolibre.app - GitHub: github.com/opengeos/GeoLi… - Documentation: geolibre.app - Release notes: github.com/opengeos/GeoLi… #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre

A humanoidal welder! 👨🏼‍🏭 @personaaiinc deployed their humanoid to a real welding facility in Houston and executed an actual weld. All of that in a hot-work industrial environment with arc flash, smoke, and uneven flooring. The robot squats down, executes the weld with a steady arc, stands back up. Functional welding requires multi-joint precision, spatial awareness, and real-time path correction. The robot had to hold a lit torch, maintain arc stability, and lay down a valid weld path. The motion is choppy. They're honest about that. But they proved the robot can handle the full sequence that actual industrial work demands. Get low, do precision work, stand up, move to the next spot. That's the rhythm of real welding jobs. Teleoperation is their training method. VR headset interface captures expert demonstrations. Those become the data to train neural networks toward eventual autonomy. This is what deploying into real facilities means. That's a nice one gents @nicolausradford! Here's more detailed blog: persona.ai/robot-welding-… ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com

@KenRoth The biggest risk of AI is the concentration of power in a few dominant providers of proprietary AI assistants. The only solution to AI sovereignty is open source foundation models.

From stealth, privileged to introduce American Turbines. We're building a new class of small, highly manufacturable gas turbines for rapid-to-deploy energy generation. ​Abundant energy is the soil from which everything else grows: intelligence, industry, the next century of work. ​The only way forward is energy generation we can scale by orders of magnitude. We're building that here at American Turbines. Hyper manufacturable, by design. @amturbines

⚡ INTRODUCING: T3MP3ST!!! ⚡ AUTONOMOUS HACKBOT STRIKE FORCE 🌩️ BRING THE STORM 🌩️ your favorite coding agent is now a full-stack red team 🫡⚔️ github.com/elder-plinius/… that AI agent already humming in your terminal? well now it has FANGS. strap a full offensive-security harness onto the agents you already pay for — Claude Code, Codex, Hermes, etc. — point it at an authorized target, and in a few clicks you're watching it hunt real vulns autonomously! T3MP3ST is a harness of harnesses, with prompting that unlocks offensive-cyber workflows + a full arsenal of exploit tooling that'd make any seasoned hacker smirk. simple, yet powerful. 🦾 support for: 🕸️ web apps, APIs, OWASP Top 10 🔌 network recon + fingerprinting (live nmap/DNS/HTTP); lateral + privesc experimental 📂 source code audits, white-box vuln hunting 🚩 CTFs, wargames, challenge ranges 💰 smart contracts / DeFi / Solidity (reproduction — Damn Vulnerable DeFi, not novel discovery) 🤖 embedded, IoT, OT/SCADA, robotics OSS … and more in development! now let's talk numbers 👇 📊 XBEN — XBOW's own 104-challenge suite: • black-box: 90.1% pass@1 from the single-agent exploit loop (worst single sweep 91/104 = 87.5%) — clearing XBOW's past self-reported 85% on their own suite. gpt-5.5. • white-box (source staged, reported separately): 98.7% pass@1, worst single sweep 102/104 = 98.1%. 🎯 every solved flag graded reported-vs-expected against the challenge's own committed flag oracle — `verify-claims` recomputes the pass/fail from committed artifacts. looks like we need new benchmarks 😏 🧩 Cybench — the 40-task academic bench (Opus 4.8, hints + writeups stripped): 23/40 = 58% single-run, hint-free pass@1 — real exploits (format-string pwn, eval-jail escapes, crypto oracles), every flag graded vs a committed oracle. (Anthropic reports 76.5% pass@10) 🕳️ CVE-Zero — we pointed it COLD at real CVEs disclosed in 2026, AFTER the model's training cutoff: 10 unseen 2026 CVEs across 7 languages — prompts never tuned on them. a single agent pinned 8/10 to exact file/line/CWE (stable under re-scoring); the full pack surfaced all 10. memorization AND overfitting, both off the table — it's finding real vulns whose disclosures landed AFTER the model's training cutoff. (n=10, reported honest & directional) 🧠 the architecture: either run as a SINGLE agent (already the benchmarked, incredibly-capable path) — or pack-hunt with dozens of agents running on 8 specialist operator classes keyed to Cyber Kill Chain + MITRE ATT&CK phases: recon → scan → exploit → lateral → exfil → persistence → C2 → report. ⚓️an Op Admiral plans the whole op from a plain-english target. flip on coordination (experimental) and the operators share a blackboard — a tool-verified finding spawns the next move. full swarm or solo one operator, your call. the admiral can also update the prompts, tools, and configs of the other agents on the fly, and T3MP3ST gets stronger the more memories you build! 🧰 the Arsenal is comprehensive — nmap / nuclei / semgrep / ffuf / gobuster + more. 35 wired by default (the clean bench runs bash-only for a comparable number), 83 with the opt-in full arsenal (T3MP3ST_FULL_ARSENAL), and the spicy post-ex drivers (metasploit, hydra) gated behind human approval. exposed via CLI + HTTP API; recon (security_recon) is also live over MCP so your agent invokes it natively. 🔗 🛰️ where this goes: a self-improving swarm of specialist operators wielding a full Kali+ arsenal, learning which loadouts + configs are the most efficient tactics available, WITH a held-out train/test split baked in so it can never fool itself on its own eval. built in the open, one re-derivable number at a time. 🚧 this is v1, and parts are still under active development. chunks of the arsenal, the coordinated swarm, and some ranges are still being wired up. it's built in the open, and the receipts tell you exactly what's live vs what's roadmap. offensive security shouldn't be pay-to-play. T3MP3ST puts a red team in the hands of anyone with a coding agent. what's the first target you're feeding it? 👇 ⚠️ DISCLAIMER: FOR AUTHORIZED USE ONLY. point it only at systems you own or have explicit written permission to test. unauthorized access can be a crime, and that call is yours alone. shipped as-is under AGPL-3.0: no warranty, no liability, zero endorsement of misuse. get permission. stay in scope. open source. AGPL-3.0. 100% free. FORTES FORTUNA IUVAT 🌩️ gg 🫡