Ian George

It’s 10 years today, since I joined X and that’s been a decent amount of time for me to have given to this platform. I thank everyone for their likes and shares of my contributions over that decade. Something more important is on my horizon so I’m on a quest to find it. Cheers!

NVIDIA has DLSS 5. Gauzilla Pro has the world's first #GaussianSplatting sharpness filter.

People are undoubtedly a little alarmed at having unwittingly helped build a 3D map of the world for Niantic by contributing 30 billion crowdsourced images. I interviewed Niantic's CTO Brian McClendon about exactly this in a TED interview last year -- he's also the guy who co-created Google Earth. But let's put it in perspective. Pokestop data isn't what you think it is. It's not a surveillance panopticon of your neighborhood. These are static captures of parks, statues, murals, landmarks -- the places people congregate. Brian described it as "building the map from the bottom up, from the locations where people spend time." Think of these 20 million waypoints as basically the inverse of what Google mapped with Street View. Google mapped the drivable streets. Niantic mapped where people actually hang out. Cool data, genuinely useful for visual positioning -- but very different from what the headlines imply. And lest we forget that Niantic is just one of many companies quietly building their own map of the world right now -- and they're all capturing different facets of reality: >🚶 person-level: Axon body cams on hundreds of thousands of officers. Meta Ray-Ban glasses capturing first-person POV at scale -- overseas operators reviewing images every time someone says "Hey Meta." > 🚗 vehicle-level: Tesla dashcams on every car in the fleet, massive onboard compute extracting and distilling data to the cloud. Waymo with cm-accurate 3D maps of every city they operate in. Fleet telematics cameras on delivery vehicles globally. > 🏠 street & home-level: Flock Safety deploying CCTV across neighborhoods and cities. Amazon with Ring cameras on every doorstep and mailroom (recently got dragged over that Super Bowl commercial about fusing all these cams together to find your dog) plus dashcams on every Prime delivery van. Roomba mapping your floor plan every time it vacuums -- Amazon wanted that data badly enough to try acquiring iRobot for $1.7B before regulators shut it down. > 🥽 headset-level: Apple Vision Pro and Meta Quest build a 3D model of whatever room you're in every time you put them on. Between Ring, Roomba, and your headset, your entire home is being spatially understood by at least three different companies. >📍platform-level: Google with Street View cars, aerial planes, satellite imagery, and live location from every Android phone in your pocket. Apple doing the same with mapping cars AND every LiDAR iPhone is quietly a 3D scanner. And yeah, despite the "Apple is too privacy-conscious" narrative, they're collecting location data too. >🏃 trajectory-level: Strava mapped every running and cycling trail on Earth -- and accidentally exposed secret military bases in Afghanistan and Syria because soldiers logged their jogs. When you aggregate enough individual trajectories, patterns emerge that were never supposed to be visible. > 🛰️ space-level: Planet Labs imaging the entire Earth's landmass every single day from orbit. Vantor capturing it in higher detail. Iceye doing it in 3D using SAR. If something changes anywhere on the planet -- a building goes up, a forest burns down, a military convoy moves -- before-and-after imagery within 24 hours. Fused together -- we have everything from body cam to dashcam to doorbell to phone to satellite -- every layer of physical reality is being mapped by somebody right now. Different sensors, different angles, different purposes. Same pattern. The interesting part is how they incentivize it. Google spends billions. Mapillary tried altruism. Hivemapper grinds with crypto. Pokémon GO cracked something none of them could: a game mechanic that subsidizes the scanning behavior. You're not building a map. You're catching pokemon. The map is just a side effect. 3D scanning is still a niche hobby for reality capture nerds like me. The moment somebody gamifies dense 3D capture at scale -- not posed photos but actual geometry -- that's when this blows wide open. Niantic sold the games for $3.5B but kept the spatial platform, with a data-sharing agreement in place. One team makes the game great, the other builds the spatial infrastructure underneath. Incentives finally aligned. Gaming is becoming a way for humans to contribute real-world trajectories that help physical AI learn about the real world. Google does it with live traffic. Tesla does it with autopilot. The mechanic is different but the pattern is identical -- and most people are already part of at least one -- if not a majority -- of these datasets whether they realize it or not.

A new mobile app for capturing #3DGS is out called #Splatking. It’s free (but a donation can be made) to download on the App Store. More details on it here: radiancefields.com/radiancefields…

From a local apple orchard in spring last year. #3DGS @arrival_space_ arrival.space/46208023_2888

This is not a video. It’s a walkable photorealistic Gaussian Splat running live in your browser. Vibe-coded camera + post effects. 50 spatial audio sources. Multiplayer avatars. Step inside the space: arrival.space/64122763_3127 Scan & vid by THE @Schindelar3D #3DGS #WebXR #vibecodingin3D @OpenAI #codex GPT5.4

@FakeSmileNFT I’ll DM you with more details later, but I thought it was very stylistic and pop art👏🏻👏🏻👏🏻

@Scannerian1 Hope i did the scans justice! If I can ever get a bit better they might be an interesting scan for another project in the summer. Will let you know more details soon and see if it's interesting to you etc. Thanks again Ian!!!

Artist @FakeSmileNFT asked me (a few days ago) for a few of my forest scans to include in this energetically deconstructed collision of particles, pixels and #3DGS “inspired by Brâncuși's Bird in Space”. On a tight deadline, well done (and thank you for inclusion in it🙏🏼 ).

Excited to share that our paper LASER has been accepted to #CVPR2026! We bridge the gap between high-quality offline reconstruction and real-time streaming. We can now turn SOTA models like VGGT and π³ into streaming systems—training-free.⚡️ Kilometer-scale reconstruction at 14 FPS. (1/n)

LiDAR is over

@nigeldanson @jimscottphoto I used to use that camera with a fast prime Voigtlander lens. Amazing lowlight abilities. Nice capture btw👏

A photograph I took 21 years ago on one on my 2nd digital camera a Nikon D200. This camera would be seen as obsolete now but the quality is still amazing. It really doesn't matter what camera you have. The most important thing in photography is subject, light, composition and timing.

Share your bird silhouette

Post a picture YOU took. Just a pic. No description.

A masterclass from a master on splats👏youtu.be/QW8ec3qquHA

Look at how crispy this 3d gaussian splat came out! The reflections in the painting have me floored. Captured with a Sony a7iii camera and 18mm lens. I posed the imagery using epic's reality capture and trained it with lichtfeld studio. Lichtfeld is my new favorite way to train splats -- it integrates all the latest research and it’s completely free. Also what I love about 3d capture -- you can process old datasets with new algorithms and breathe new life into them.

You probably can’t begin to imagine my elation when I added a 16Kb memory module to mine.

@ViewFromShikhar Magnolias in bloom at sunset.

Let's see some colours of nature from your gallery!

@billymooreAPBD We should just start calling them Hard Labour. We’ve witnessed nothing but since ‘that’ got into No10.

This is terrible leaving pensioners on the streets of Britain who obviously haven’t got a drug or alcohol problem homeless!! Shame on our government!!!

Building Gaussian Splatting Pipelines for Spatial Intelligence x.com/i/broadcasts/1…

Vibe-coding. In 3D. In real-time. On the web. 👉 arrival.space