Every week, I organize 400 to 700 links into roughly 60 categories as part of my ongoing effort to learn about AI. This is my personal notebook, which I enjoy sharing with friends… a hobby and a labor of love, rather than a commercial publication or product.
If you arrived here through a search or shared link, this page collects the links I found for Augmented Reality (AR/VR) for the week ending August 14, 2026.
As part of my learning process, I like to automate the category covers. It gives me a chance to learn Python and APIs.
This week’s cover prompt was written using Claude Opus 4.7, and the image was generated using Nano Banana 2.1.
Category Cover Image Prompt: A single photorealistic VR headset resting face-up on a mirror-still pale dawn lake, its visor softly reflecting an indigo sky with one thin thread of warm gold light on the horizon, surrounded by vast misty negative space and quiet symmetry with its reflection, bold clean title text 'AR/VR' set large in the open sky above, minimalist fine-art magazine-cover composition, soft diffused natural light, crisp detail on the headset while the surroundings fall away.
This Week in Augmented Reality (AR/VR) News
Summary by Claude Sonnet 5.5 based on this week’s links:
- Video and photos pinned into 3D space: Bilawal Sidhu showed a phone video of a mother deer and fawn turned into a geo-anchored 3D hologram, and described mapping the location of every photo taken at TED. He also traced how reconstructing places from internet photos has progressed from Photosynth in 2008 to whole cities.
- World models for robots: Dyna Robotics introduced Dyna-2, a world-action model pre-trained on over a million hours of egocentric human video. The company says it saw scaling laws across four orders of magnitude of human data. Separately, Stanford and NVIDIA's PointWorld-1B predicts how a whole scene moves from RGB-D input and robot actions.
- Memory and open releases for video worlds: NVIDIA published WorldTrace, which adds addressable memory to video world models, and it also made The Turing Post's must-read list. LTX released LTX-2.5, billed as an open world model for video.
This summary was generated by Claude Sonnet 5.5 to help you explore the links below. Rest assured, I select, organize, and check the links by hand in Google Sheets, and write the introduction and personal commentary in The Main Newsletters myself each week as a labor of love.
This week's links related to Augmented Reality (AR/VR)
What if every video you ever shot could turn into a permanent 3D hologram in the exact place it happened? I did it with photos first. Now I can do it with any video. Here’s a mama deer and her baby deer, filmed with my iphone a few days ago — now floating as geo anchored”
https://x.com/bilawalsidhu/status/2087285954218279307
Databricks Grows >80% YoY, Surpasses $7B Revenue Run-Rate, Scales Lakebase, Genie, and Unity AI Gateway – Databricks
https://www.databricks.com/company/newsroom/press-releases/databricks-grows-80-yoy-surpasses-7b-revenue-run-rate-scales
What if a robot could simulate the physical world from a single image. [📍Bookmark Paper & GitHub for later] PointWorld-1B from Stanford and NVIDIA is a large 3D world model that predicts how an entire scene will move, given RGB-D input and robot actions. The key idea is”
https://x.com/IlirAliu_/status/2086151375084265842
WorldTrace: Addressable Memory for Video World Models
https://research.nvidia.com/labs/sil/projects/WorldTrace/
Today we are introducing Dyna-2, a world-action model pre-trained on one million hours of human video. At this scale, for the first time, we discovered several new scaling laws: • world-action models exhibit scaling law on human data across four orders of magnitude, from 1000″
https://x.com/DynaRobotics/status/2086856327150858298
world models are brutal”
https://x.com/dreamingtulpa/status/2086546779852378356
Progress update: figuring out the 3D location of every photo taken at TED with attribution. It’s starting to feel magical — makes me wonder what experiences are possible if we could do this for every live event ever.”
https://x.com/bilawalsidhu/status/2086116653071216892
Reconstructing the world in 3D from random internet photos is a deep rabbit hole. In 2008, Photosynth proved that 3D reconstruction of smaller monuments was possible. The next year, “Building Rome in a Day” proved it could be done for entire cities. Since then, there’s been a”
https://x.com/bilawalsidhu/status/2087677694112628771
What a LiDAR sensor sees when cyclists are racing through Iowa.”
https://x.com/bilawalsidhu/status/2085788609290834241
Must-read papers of the week ▪️ EnvACE ▪️ The Optimizer Is the Agent: Reasoning-Driven Search across Prompts, Programs, and ML Workflows ▪️ SFT Conflicts, RL Coexists ▪️ Addressable Memory for Video World Models ▪️ The Personalization Mirage: How LLMs Fabricate User Profiles,”
https://x.com/TheTuringPost/status/2087141521493787031
Introducing LTX-2.5: The Open World Model for Video, Real-Time, & Physical AI | LTX
https://ltx.io/newsroom/introducing-ltx-2-5
Dyna-2: A 1-Million-Hour Scaling Law for World-Action Models … DYNA
https://www.dyna.co/dyna-2
How well do egocentric human videos scale? Apparently, really well. Dyna Robotics has introduced Dyna-2, a world-action model (WAM) pre-trained on more than 1 million hours of real egocentric human video. It learns by jointly predicting the next video frames and the actions, and”
https://x.com/TheHumanoidHub/status/2086875827296436394
GUSH3R: Everyone Everywhere All at Once as Gaussians” TL;DR: reconstructs dynamic humans and static scenes from monocular video as unified 3D Gaussians in one forward pass, using Human3R geometric priors and dedicated human/scene Gaussian decoders.”
https://x.com/Almorgand/status/2086857724399145193
Leave a Reply