Streaming iPhone data in real-time directly to Rerun 🚀... The collection process is one of the most frustrating parts of building imitation-learning datasets. I’ve got a little army of sensors—📱 iPhone, iPad, Quest 3—but getting them temporally aligned, spatially aligned, AND seeing real-time feedback while recording is tough. I stumbled on a great library from Cake Lab (WPI) called ARFlow. It’s a thin client built on Unity’s ARFoundation that connects over gRPC to a server running Rerun for live data logging. I forked it to: - Log the SLAM translation poses, and - Upgrade rerun to v0.23 for my use case. So far, it works well, but there are still a few hitches: 1. Right now, it’s solid on iPhone and iPad; my Quest 3 client is still slow and not super reliable. 2. I’m using an older ARFlow branch focused on real-time streaming only—no spatial or temporal sync yet. Unity builds for iOS keep failing. 🛠️ 3. Nothing is saved locally to the client, so packet loss is a risk on shaky networks. There’s huge potential in tapping the ubiquitous sensors we carry around every day, and ARFlow is a big step toward making that easyshow more

🚀 Introducing EgoExo Forge - built on top of... Rerun, Gradio, and Hugging Face hub (I’ll be in San Francisco July 21–29 — if you’re into robotics, egocentric AI, large-scale data collection, or just want to chat, DM me!) In my opinion, large-scale, diverse, and high-quality data is still the largest bottleneck for generalized robotics deployment. I believe that some version of imitation learning from human examples will be the most scalable + clean way to train humanoid robots 🤖 (similar to what Tesla did for Full Self Driving). Teleop is too expensive to collect a large enough dataset in a reasonable manner, so passive collection via egocentric (and in certain cases, exocentric) views feels like the right bet. Over the past few months, I've been trying to build out the scaffolding for this and using Rerun as my underlying infrastructure. Data being collected needs to be easily inspectable + time series and rerun provides the right tooling for this. My goal is to first build out a ground truth representative dataset from already existing open source data, generate some reasonable baselines, and then go out and collect my own data that adheres to the defined schema. 🔍 Starting with open-source datasets 1. EgoDex from Apple 2. HOCap from Nvidia and the University of Texas at Dallas 3. Assembly101 from Meta All these different datasets have different sensor configurations + annotations, so my goal with egoexo-forge is to have one consistent labeling scheme + data layout. I built a data pipeline that aligns all of the different datasets in one general schema assuming the COCO133 keypoint layout that allows for exo+ego, ego only, or exo only Since the scaffolding is already there, it becomes MUCH easier to add other datasets. So the next ones that I'll be including are HD-EPIC kitchens dataset, HOT3D, and finally my own personal iPhone + insta360 go collection method. Once I have a diverse variety of datasets, I'll double down on what I believe to be the key algorithms required to make useful data for imitation learning 📊 1. Camera Pose estimation via SLAM/SFM for ego perspective (and automatic calibration for exo) 2. Human pose estimation for both egocentric + exocentric views 3. Metric 3D reconstruction + object tracking I'll be setting up reasonable open-source baselines for each of these to validate that these datasets work, and then finally try to use the generated datasets for some imitation learning via the pi0-lerobot repo I've been working on. I plan on making a blog post + providing more info on all of this in the near future so stay tunedshow more

Colmap 4.0 was very recently released, so it inspired... me to do some work to better understand it and its new capabilities with Rerun. I want to really understand how Colmap, and in particular, pycolmap, works outside of just calling it via the CLI. So my goal is to use the low-level pycolmap API to log every part of the pipeline. The explicit goal is to have an alternative to the SQLite database that I can utilize. Instead of SQLite, I want to try logging everything directly to rerun and use RRD. This means I can have deep inspectability and still save the features/matches/2D view geometry, but be able to view it directly in rerun. I think this is one of the superpowers that rerun provides; data and visualizations are deeply integrated. As I'm often working with sequential data (videos), I'm going to specifically focus on four things: 1. Monocular Video Simple: Calls high-level APIs such as pycolmap.extract_features, pycolmap.match_sequential, pycolmap.incremental_mapping. These are basically identical to the CLI options and provide a good baseline. 2. Monocular Video Streamed: Take the above high-level APIs and break them down to their iterator version, logging each component in a streamed manner. This way, I can stream the intermediate features to rerun while the extraction/matching/mapping is happening. 3. Rig with unknown calibration: <- WHAT THE VIDEO SHOWS This is probably the most interesting version and the first one I've been working on. It allows one to set a rig between known sensors, such as in VR/AR devices, leading to much better reconstructions with multiple cameras. This is the case where we don't know the calibration a priori, so we have to run a reconstruction twice: once as a normal Colmap reconstruction with no rig constraints, use this to generate the constraints, and then do it again with the newly found rig. 4. Rig with known calibration: This is the RoboCap example, where we have a pre-calibrated set of sensors, so we don't need to run the two reconstructions and also gain better matching between cameras, both spatially and temporally. Again, this leads to a much better reconstruction! Along with all this, GLOMAP has become a first-class global mapper, making it super easy to use directly within pycolmap! I'm excited to do more with this and compare it to things like pycuvslam, vipe, and other alternatives.show more

So I just played Pokemon in REAL LIFE! This... is one of the coolest things I've experienced in the headset using MR. And the fact it works this well still blows my mind. Huge thanks to DramaticShape for his work on this for Quest. Unbelievable job on this.show more

TESLA HALTED MODEL S AND MODEL X PRODUCTION TO... BUILD AN ARMY OF OPTIMUS ROBOTS The Fremont assembly line was torn down in 46 days. In its place, Tesla is building a line for humanoid production, aiming for a million units a year A humanoid robot is a body shaped like a human. Physical AI is the intelligence that controls that body Walking and making coffee is often just imitation learning from a scripted routine. But once the environment shifts, the learned trick stops working Language models had the entire internet to train on. Robotics has nothing close to that scale of data, which is why one giant brain hasn't worked for anyone yet The industry is moving toward modularity instead - separate models for vision, movement, and planning, each improved on its own The real question is no longer whether a robot can move impressively. It's whether it can pull its sensors into one picture of the world and adapt to whatever wasn't scripted for itshow more

got cloud inference working! here i have smolvla running... on a remote 4090 on prime intellect with a thin client running on my local pc sending observations to the remote server and receiving action chunks back. round trip latency is varying between 320-470ms! the 4090 instance I'm using is $0.62/hr and not even one of the cheaper ones, a raspberry pi v5 is < $100 and about $25 for a v3, which works fine as a clientshow more

My first full day with iPhone Duo. It feels... expensive. The weight, the shiny titanium edges… almost like a piece of jewelry. A little heavy, yes, but coming from an iPhone 18 Pro Max, I’m getting used to it. There’s a learning curve. I miss Face ID. Picking it up and swiping no longer gets me straight in. Having to adjust my grip to reach Touch ID feels like a step backward. The speakers sound good, but they’re also less full and bassy than on my 18 Pro Max. But that big screen makes me want to keep using it. Videos, games, reading and replying to emails, everything has more room. Real multitasking! Having ChatGPT instructions on one side while following them on the other is especially useful. Most of my everyday apps already look great, though some banking apps still not updated. The small, wide cover screen has its own charm. It’s great for quick replies, and the wider keyboard is comfortable. Unfolded, it’s mostly a two-handed device, although holding it in one hand and scrolling through X in bed is comfortable too. And I’m slowly falling in love with the matte screen. You lose some OLED contrast, and there’s a very fine grain that I’ve already stopped noticing. But reflections disappear, the crease is much harder to see, and fingerprints build up much more slowly than I expected. It feels lovely under your fingers, too. For a foldable, I’d choose this finish. The cameras surprised me. In a few side-by-side indoor evening shots, the main and ultrawide cameras looked identical to my 18 Pro Max in detail and color. Zoom to 5-10x, though, and the difference is obvious. I really want a telephoto camera in a future generation. Too early for a battery verdict, but so far it’s holding up very well. I’ve only noticed it getting hot during demanding gaming, including GTA V at max settings. Video coming soon. At first, all the little differences made it feel like a second phone. Now I’m starting to see it as my main iPhone, with an OPPO or vivo alongside it for the cameras and zoom. Still adjusting, but I’m really enjoying this thing. Finally, something completely new for iPhone. It still feels experimental, and not everything is seamless, but I love trying new gadgets and figuring them out. That’s part of the fun for me, and I’m really enjoying this one.show more

Spotlight on iOS is soooooooo slow. sometimes takes 15... seconds to show search results. It’s in an unusable state. This is on an iPhone 13 mini, the real-time spotlight experience. Am I the only one?show more

I found an old screen recording from my iPhone... 11 Pro Max with iOS 17 Decided to compare the animations to my iPhone 17 with iOS 27, and I have so many thoughts 😭 Overall, iOS 17 is INFINITELY smoother than iOS 27, purely due to its animation speed. Opening and closing apps is slow and elegant, accompanied by a beautiful wallpaper zoom. 27 is rough, fast, and lacks fluidity. For some reason, they got rid of the wallpaper zoom when opening/closing apps, making everything feel flat. All of that is paired with the atrocious performance of the iOS screen recorder that started with iOS 18 and still hasn’t been fixed. Notice how there are zero jitters on iOS 17, but both jitters and artifact on 27. This is not a hate post. I just wanted to share my thoughts. And no, this isn’t the problem of a “beta”. Stable iOS 26 has the exact same issues. Thanks 💔show more

I really learnt from the best If your content... is averaging 700 views it’s of two things 1. It’s either you did not warm up your account well to the hashtag you are posting with 2. You have a general content problem , you need to find content that has been pushed in the last 1 month max and post I have 4 iPhones , 3 iphone 8 and 1 iPhone 7 , I post content on all everyday been doign this for the past 2 years I use the iPhone 7 to post for one of my brands And I use the 3 iPhone 8 to post for one brand The most important thing is , find what works for one phone and spread it across others It took me years to learn this One big lesson, don’t tell your vpn to X , you will hate yourself , not telling people the vpn I am using so they don’t overcrowd it If you post a content in your main niche, you should be averaging 1k+ - 5k+ views Trust me it’s a lot of work I also started posting on instagram and YouTube and they work differently , don’t post the same video content on both without observing hashtags I also posted on lemon8 , one of my post average 10k+ views Daily I get around 50 users , I have gone viral several times, one of my biggest virality is 700k+ views I really want to buy more iPhone 7 and 8 , It costs me arround $50-70 for each locally here Recently I have been thinking of how do I get clippers locally to do this and train them but it looks like it’s hard because you have to train them Taking advice from the legend Alex Nguyen I have not made a lot but trust me , it works This is proof from one of the apps , we ask during onboarding where they find usshow more

Sam3 + Body is freaking amazing. I'm in the... process of building an open-source Rerun and Gradio demo that is similar to what Meta provided. Got the basic functionality up and running, now I need to hook it up to a Gradio interface. It's a really good modelshow more

iPhone Takes a Photo of You Every 5 Seconds... While you’re using your iPhone, it takes a photo of you every 5 seconds. More precisely - when you pick up or put down your iPhone, and also when it’s unlocked and sits motionless for a long time, the Face ID sensors take pictures every 5 seconds. You can see this through the infrared lens: it looks like the iPhone is taking a photo in the dark with a flash. Even if you cover the sensor, it will still keep trying to take a picture. In reality, of course, the iPhone isn’t taking photos. It scans your face to figure out whether you’re looking at it. In Face ID settings this mode is called Attention Awareness. You’re working on your iPhone, it’s charging, you get a call - and the iPhone “takes pictures” with the Face ID camera. As soon as it realizes you’re looking at it, the ringtone gets quieter. The same thing works with alarms and other notifications. This is not actually taking photos - it’s the TrueDepth infrared sensors scanning your face for the Attention Aware Features. How to turn this off on iPhone. You need to disable Attention Aware Features. Method 1 (main one): 1. Open Settings. 2. Tap Face ID & Passcode. 3. Enter your passcode. 4. Find Attention Aware Features and turn it off. Method 2 (via Accessibility): 1. Open Settings → Accessibility. 2. Tap Face ID & Attention. 3. Turn off Attention Aware Features. After that, your iPhone will stop automatically lowering the volume of calls, alarms, and notifications when you’re looking at the screen, and it won’t scan your face as actively for “attention.”show more

A few days ago, I got 7-8 leads in... one day Every client asked the pricing and just stop replying. 2 clients were about to pay but when I asked for invoice details, they stopped replying. 1 client had a very small budget so I rejected the project 1 client booked a call and cancelled it at the meeting time. 1 client project wasn’t a fit for us because the niche. I don't know why is this happening 🥹show more

Today I vibe coded an AR game entirely within... my Meta Quest 3, using Gemini 3. The holodeck is real! Just go to in the Meta browser, toggle canvas, and ask (via voice) for a WebXR app. Getting scene geometry took a few tries, but it basically just works.show more

The gold standard fluid interactions on iOS are built... using in-process client animations (like SwiftUI does it) and not render-server animations (like CoreAnimation does it). This is common knowledge inside of Apple’s UI framework and system experience teams. A close inspection of iOS’s evolution reveals the gradual upgrading of system experiences written using render-server animations (that often disable user interaction) with ones using client animations (that are interruptible and interactive). The app switcher for iPhone X, the Dynamic Island, and Liquid Glass bars are prime examples of this trend. The other thing that makes these experiences feel so fluid is their use of spring animations that preserve velocity, rather than Bézier curve easing functions. To get velocity preservation, you need to be able to interrupt a spring animation and retarget it or drive it with a gesture. That’s a lot easier to do when the animation is running in the same process as the event handling. When we were first pitching SwiftUI, two of our go-to demos were a recreation of the iOS 9 navigation and Home Screen interactions which were fully interactive and interruptible, at a time when the actual implementations of those experiences in the OS disabled user interaction and ran server-side animations. CoreAnimation is great and the framework does much more than animation. You can build a fine app using its server-side animations. But if your UI framework can’t do efficient main thread client animations, there’s a ceiling to the quality of the experience your app can provide.show more

The next World Cup star is playing right now,... and nobody is watching. The 2026 World Cup is on, and millions of kids are dreaming of one day playing for their own flag. But the path there is almost impossible: no consolidated data, too many games, not enough scouts, human bias, and wrong place, wrong time. Any one of them can bury a generational talent before a scout ever sees them. That is what we are building to fix. So we developed a full automated annotation + action spotting model where it actually matters: grassroots football. Shaky cameras, awful angles, terrible lighting. But now nothing on the market beats sn44's v2.0 model on it. Check the last GT line, it’s human annotations. Simply because miners' outputs + post-process = magic. Post-process is a deliberate design choice. We point miners at the hardest 80% of the workflow, the part that is genuinely difficult to fake, and handle the rest downstream. Fewer places to game the system means a network you can trust. Every single challenge on sn44 can be an independent startup now. Let that sink in.show more

there is so much real data just sitting in... the open right now it's almost funny. four years of starlight on every star, a NASA archive that's been free for over a decade, detectors still recording the sky tonight, and barely anyone has a net pointed at any of it. so i pointed one. this is me pulling the planet data, the data loading is the boring part. the net i built to read it, the wall it hit, and what that taught me about where AI goes next, that's the full story, and it drops tonight. the data's public, the tools are free, the box fits on a desk. what's stopping you. you can just do things anon.show more