ʞooH ɯlǝsu∀ @anselm

There's now a free website that lets you watch any city on Earth sprawl outward twice a year for a decade, and then shows you exactly where it grew into danger. Picture a family moving to the edge of a fast-growing city. The land is cheap because it floods, or because the ground beneath it is slowly sinking, or because it bakes in summer heat the city centre never sees. Nobody planned for them to be there. The city simply spread outward faster than anyone was watching, and by the time the danger is obvious the houses are already full of people who can't easily leave. That gap between how fast a city grows and how slowly we measure it is the problem a new free tool sets out to close. The German Aerospace Center, MindEarth, the European Space Agency and the World Bank built it together and launched it at World Bank headquarters in Washington. ESA's Fabio Cian described it as space agencies, industry and development partners designing the answer side by side. The result is the World Settlement Footprint Tracker, and what it does is simple to say and pretty difficult to pull off. It watches cities grow from orbit. Every six months, continuously from 2016 to 2026, it maps where human settlement exists and where it has just spread, at a resolution of ten metres. That's roughly one pixel per small building plot. So instead of one static snapshot of a city today and maybe a blurry one from years back, you get a decade of the city breathing outward, frame by frame, twice a year. Then it lays that growth over danger. Five hazards, to be exact: flooding, sinking ground, earthquakes, extreme heat and cyclones. And the overlaps are stark. In Hanoi, a huge share of the past decade's expansion pushed straight into suburban flood zones, and not the shallow kind, the areas where water tends to sit deepest. In Xi'an, fresh development sprawls across ground that's projected to subside, meaning the buildings going up now sit on land that is forecast to drop out from under them. The same lens covers Bangkok, New Cairo, Goma, Pucallpa, Chengdu, Warsaw, Cologne and more, and anyone can open it, zoom in and download the numbers for free. Why this matters comes down to timing. Roughly two in three people will live in cities by 2050, which means the buildings that will house that surge are being sited right now, this decade, often in places where growth and hazard are colliding before anyone has drawn the comparison on a map. Steering a new neighbourhood away from a floodplain is cheap. Moving one after it's built, or rebuilding it after a disaster, is ruinously expensive, and that bill usually lands on the people who could least afford to be there. More info here: esa.int/Applications/O…

🦧 Day 30 – Call me the architect now. Houses fully optimized. Reality level absolutely cranked. Parametric everything: cultures, floor plans, multi-story, extensions, garages, terraces; the system is breathing and ready to grow. I bent my clanker till it snapped. Said it couldn’t be done. 3-0 me, bitch. Still messy in places but we don’t stop. Zero assets. Pure Three.js + AI insanity. No excuses. No mercy. Yesterday was peak momentum. Today we made it real. Still not satisfied… but it’s hitting different. Next? Full cities or pure chaos? Be brutal. #ApeCode #Procedural #ThreeJS #WebGPU #gamedev #indiedev

Gaussian Splats are great, but they had one drawback, until now: Collision detection was impossible, so it wasn't viable for gaming. But now, there is a method that turns the splats into voxels for the collision detection, and it works great:

クリエイター(doorfortyfour氏)が公開したUnity向け「TileWorldCreator」のルールベースマップ作成デモ🗺️ タイル配置ルールを組み合わせることで、地形・森林・道などを自動生成し、自然なレベルデザインを高速に構築。オープンワールドやストラテジーゲームの開発効率を大幅に高める技術として注目

Red patches = mines. Plane icons = illegal airstrips. All inside Venezuelan rainforest. All found by a journalist in exile using satellite AI. 🛰️🌿 Map: Armando.info | niemanlab.org/2026/04/geospa… #Geoawesome #GeoAI #EarthObservation #Amazon

原来学空翻这么简单吗？

Breaking: Google permanently locks people out of their accounts with no warning and no way to reach a human. Gmail, Photos, Drive, every login. Gone, with no appeal. Here is the backup that protects you, in under an hour:

今日は夏至。

A simple strip of wildflowers can dramatically reduce the need for chemical pesticides. So why aren’t they standard on every farm? Farmers are increasingly planting colorful wildflower strips within and around their fields because these habitats attract beneficial insects that naturally control crop pests. Ladybugs are the most familiar example. Both adult ladybugs and their larvae are voracious predators of aphids, small sap-sucking insects that damage crops. A single ladybug can eat dozens of aphids a day, while its larvae can consume hundreds before reaching adulthood. Yet ladybugs are just the beginning. Wildflower strips also draw in hoverflies, lacewings, parasitic wasps, and predatory beetles, all highly effective natural enemies of common pests such as aphids, whiteflies, thrips, and caterpillars. This approach is known as conservation biological control. Rather than releasing predators into fields, farmers create permanent habitats that support and boost populations of beneficial insects already present in the landscape. The flowers supply essential nectar and pollen that many of these insects need as adults. Research shows that access to such resources significantly increases their lifespan, reproductive success, and pest-hunting efficiency. Some parasitic wasps offer an especially impressive form of control: they lay eggs inside aphids or caterpillars, and their developing larvae consume the pest from the inside out. Multiple studies confirm that fields with wildflower strips support far higher numbers of beneficial insects and achieve stronger natural pest suppression compared to conventional fields. Beyond pest control, these strips provide additional benefits: they support pollinators, enhance biodiversity, reduce soil erosion, and create valuable wildlife habitat within agricultural areas. Scientists are now fine-tuning which flower species work best for different crops and climates, aiming to design the most effective and practical wildflower strips possible.

New paper: every law in America is technically public. But not really, until now! With @DenisPeskoff at UC Berkeley, we built a corpus of ~every publicly accessibly city and county law, and released a huge chunk of it! 2.2 million laws, you're (probably) covered in it! 🧵

Interesting paper. They took 10,272 writing prompts and gave each one to a human author and to five AI models: Claude, GPT, Gemini, DeepSeek, and Kimi. From these, they generated 61,608 stories, at around 5,000 words each to see if there was divergence at a narrative level. From the analysis, they found that they could identify a human-written story from an AI-generated one nearly 93% of the time. Left: Each story is a dot. The story’s 304 dimensional narrative feature vector has been projected down to two dimensions using Linear Discriminant Analysis (LDA). Brown dots are human. Right: Each story gets scored on how rare its narrative feature profile is, then mapped to a percentile: approximate 1.0 means highly unusual relative to the reference set. The models reliably produce narratively “average” stories, while humans more often into unusual territory arxiv.org/pdf/2604.03136

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Below is the statement from the NSF about halting the dismantling of the ocean monitoring infrastructure. The Senate passed a measure yesterday (Wednesday) to block the Trump administration from dismantling the OOI system, with lawmakers in both parties warning that the action would be illegal and would threaten the safety of coastal communities.

Ready to turn planetary-scale data into instant conservational insights? 🌍 Nicholas Clinton, Alicia Sullivan, and Sheba Rasson are here to introduce custom Geospatial AI Agents built with the Agent Development Kit and Google Earth Engine! 💻✨ 🧠 Reason through ambiguity. 🛠️ Orchestrate Google Earth Engine datasets. 📝 Generate clear narratives. 📂 Try open-source examples. Read the full guide to build your first agent. goo.gle/4vcje7Y

@LLMJunky Humor but funny

I'm a cardiologist. Something just happened today that I genuinely did not see coming — and it could change the future of preventive medicine more than anything I've written about on this platform. Midjourney — the AI company that became famous for generating images from text prompts — just announced a medical hardware division and unveiled a working prototype of a full-body scanner unlike anything that's ever existed. It's called the Midjourney Scanner. And it works like this. You step into a shallow pool of water. You stand on a platform that slowly descends — about two inches per second — through a ring containing roughly half a million tiny ultrasonic transducers, each the size of a grain of sand. Every one of them acts as both a speaker and a microphone, sending ultrasonic waves through your body from every angle and recording what comes back. 60 seconds later, you step out. The scan is done. No radiation. No magnets. No claustrophobia. No IV contrast. Just sound, water, and an almost incomprehensible amount of computing power — roughly 2 petaflops processing 17 gigabytes per second of raw acoustic data — reconstructing a 3D map of your entire internal anatomy down to half a millimeter resolution. Organs. Tissues. Blood vessels. Bones. Muscle. Fat distribution. All segmented by AI in real time. As a cardiologist who has spent months writing about how the standard screening playbook misses the majority of future heart attacks — this is the technology I've been waiting for without knowing it existed. Here's why this matters for the future of your heart. Right now, getting a detailed look inside your cardiovascular system requires either a CT scan (radiation), an MRI (magnets, claustrophobia, 45-60 minutes, $1,000+), or a coronary CT angiogram (radiation, IV contrast, limited availability). These are powerful tools. I order them regularly and they save lives. But they're reactive. You get them when something is already suspected. They're expensive. They're uncomfortable. And for most people, they happen once — maybe twice — in a lifetime. Imagine instead: a 60-second scan with no radiation that you could repeat monthly or quarterly. Tracking cardiac structure over time. Watching body composition shift. Detecting changes in organ size, fluid distribution, or vascular architecture before symptoms ever develop. Building a longitudinal dataset of YOUR body that AI can analyze for patterns no single snapshot would reveal. That's what Midjourney is building toward. The company plans 50,000 scanners worldwide over six years, with capacity for a billion scans per month. The first location — the "Midjourney Spa" in San Francisco — opens at the end of 2027 with 10 scanners alongside saunas, cold plunges, and a gym. The scan costs a few dollars. The experience is designed to feel like wellness, not medicine. The technology is built on Butterfly Network's ultrasound-on-chip platform — 40 modules per scanner — combined with Midjourney's own AI segmentation and reconstruction stack. David Holz, the founder, claims the system aims for image quality comparable to MRI in many aspects but at nearly 100x the speed with zero radiation. Now the caveats — because I'm a physician and the caveats matter enormously. This is a Gen 1 prototype. About a dozen people have been scanned so far. Current scan time is actually closer to 20 minutes, not 60 seconds — the system is bottlenecked by bandwidth and reconstruction algorithms. The 60-second target is aspirational for future hardware generations. It is not FDA-cleared for diagnostic use. Midjourney is starting with body composition maps — a category below diagnostic imaging in the regulatory hierarchy. The path from "beautiful 3D body scans" to "clinically validated diagnostic tool that your cardiologist can act on" runs through years of clinical trials, comparative studies against MRI and CT gold standards, and FDA review. No independent clinical validation has been published. The imaging claims come from Midjourney's own demonstrations. Comparative data against established modalities does not yet exist. And the privacy implications of full-body internal scans at planetary scale — a billion scans per month — is a conversation that hasn't even started yet. So I want to be precise. This is not ready for clinical medicine today. It may not be ready for years. Many ambitious medical hardware projects have failed in the gap between prototype and product. But. The fact that a working prototype exists — producing real segmented 3D anatomy from sound waves and compute alone — means the physics works. The engineering works. The question is no longer "is this possible" but "how fast can it be validated and scaled." And if it is validated — if the resolution holds up against MRI, if the AI segmentation proves reliable, if the regulatory path clears — then what we're looking at is the most significant new imaging modality in 50 years. For my entire career, preventive cardiology has been limited by the fact that seeing inside the body is expensive, slow, uncomfortable, and infrequent. We catch disease late because we image rarely. We image rarely because imaging is hard. A 60-second, no-radiation, spa-based full-body scan that costs a few dollars would demolish every one of those barriers. I've written about AI detecting inflamed arteries. About gene editing curing cholesterol. About GLP-1 drugs rewriting metabolic medicine. About cellular reprogramming reversing aging. This is the missing piece: the ability to see inside every human body, routinely, safely, and affordably — so all of those interventions can be deployed before the disease arrives instead of after. The company that taught AI to generate images from imagination just built a machine that generates images from the human body. The future of medicine showed up today from the last place anyone expected.

Midjourney @midjourney

2 weeks ago

Announcing a new division of Midjourney called "Midjourney Medical"

3K 6K 40K 18.3M 11K

Can AI do Time Series Forecasting? This is what I found out.

🚨速報🚨 『Codex』の進化が凄まじい🔥 「PUBG」や「荒野行動」の様な ゲーム制作を完全自動で制作が可能に‼️ 詳しく解説⬇︎

The new Metahuman markerless motion capture plugin in Unreal Engine 5.8 is insane!! I just took a quick video with my galaxy s22 ultra and I got amazing motion capture results. I can't believe it's available in the engine for free #unrealengine #gamedev #animation

This recent paper is super interesting... Using ultrasound imaging to generate images of the entire in vivo human cross-section in the abdomen and thighs Basically trying to do CT/MRI-like imaging but using ultrasound! Ultrasound imaging is highly underrated :)

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