Rafael Spring (@Rafael_L_Spring) header
Rafael Spring (@Rafael_L_Spring) profile picture

Founder @dotproduct3d Prev. Founder @ Enkin AR (acq‘d by Google) SLAM / Sensor Fusion / 3D Capture GPU poor

Joined June 2013
Photo by Rafael Spring (@Rafael_L_Spring)Photo by Rafael Spring (@Rafael_L_Spring)Photo by Rafael Spring (@Rafael_L_Spring)Photo by Rafael Spring (@Rafael_L_Spring)Photo by Rafael Spring (@Rafael_L_Spring)Photo by Rafael Spring (@Rafael_L_Spring)Photo by Rafael Spring (@Rafael_L_Spring)Photo by Rafael Spring (@Rafael_L_Spring)Photo by Rafael Spring (@Rafael_L_Spring)
The 3D Gaussian Splatting paper has (rightfully!) stirred up a lot of attention and some friends asked me for a technical take on it, so here we go: TLDR: Fast, simple, outstanding level of detail, with some caveats (see below). 1/x
3D Gaussian Splatting for Real-Time Radiance Field Rendering paper page: huggingface.co/papers/2308.0… Radiance Field methods have recently revolutionized novel-view synthesis of scenes captured with multiple photos or videos. However, achieving high visual quality still requires neural networks that are costly to train and render, while recent faster methods inevitably trade off speed for quality. For unbounded and complete scenes (rather than isolated objects) and 1080p resolution rendering, no current method can achieve real-time display rates. We introduce three key elements that allow us to achieve state-of-the-art visual quality while maintaining competitive training times and importantly allow high-quality real-time (>= 30 fps) novel-view synthesis at 1080p resolution. First, starting from sparse points produced during camera calibration, we represent the scene with 3D Gaussians that preserve desirable properties of continuous volumetric radiance fields for scene optimization while avoiding unnecessary computation in empty space; Second, we perform interleaved optimization/density control of the 3D Gaussians, notably optimizing anisotropic covariance to achieve an accurate representation of the scene; Third, we develop a fast visibility-aware rendering algorithm that supports anisotropic splatting and both accelerates training and allows realtime rendering. We demonstrate state-of-the-art visual quality and real-time rendering on several established datasets.
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Rafael Spring retweeted
【全世界がこの瞬間に感動した?】 #dot3d と #drogger 最新状況 dot3dがdroggerのGパッケージに対応 希望者またはPRO版の方は30日限定のテストライセンス番号を交付して貰えるので、まずは公式サイトから申し込みしてください ※PRIME版は1年間$999てすが、月額$139の契約もあるので、まずは必要な時に月額サブスク契約するのもやり方もありですね @DotProduct3D
#dot3d 更新キター❗️ まだBETA版ですが #drogger を機種選択できません😭 PRIME版に契約しないいけないの? PRO版で動かないと動作テストも出来ないよ😵 最初から難題が起きて躓いてしまった…🤦 どうすれば試用できるのでしょうか? @DotProduct3D
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I have a weird feeling "vibe coding" will go the same way as "prompt engineering". Will anyone even be interacting with code in 2028? I'm not so sure actually.
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My fellow Gaussian Splat enjoyers, I created a monster. I'm about to set it free this week. Be prepared.
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Replying to @unusual_whales
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Rafael Spring retweeted
Y Combinator just published the list of startups it wants to fund next winter. One of them is AI for City Hall. In some American cities, YC writes, getting a building permit takes longer than building the house. By its own math, if every permit in the country were approved in a tenth of the time, cities would collect $16 billion more a year in property tax. There are 19,000 cities in America, and almost all of them still check drawings against the code by hand. I like the idea. My first company, while I was still at Columbia in the 1980s, redeveloped buildings in Tribeca and SoHo, so I have stood on the other side of that counter. But look at what the waiting actually costs. In 2021 the National Association of Home Builders surveyed more than 2,000 builders and found that regulation accounts for $93,870 of the price of an average new home, 23.8% of it. Only about $2,400 of that is the pure cost of delay. The rest is fees, building codes that keep changing, design standards beyond the ordinary, and land the government takes or forces you to leave empty. So AI can make City Hall faster. It cannot make it cheaper. A model that approves a bad rulebook in one day still leaves the same $94,000 inside the average new house, just sooner. The startup I would fund does both: it reads every permit, and it also measures what each rule costs the family that will buy the house. Then it publishes the numbers and lets voters decide which rules are worth paying for. Faster bureaucracy is progress. Less bureaucracy is reform.
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Can it really be that easy? Can it really be that fast? Actually yes. The real numbers: Prep: 0 min Scanning: 13 min Optimization: 3.5 min Software: Dot3D Prime Hardware: iPhone Pro Max + General Laser GLRM RTK Constraints: 1 AprilTag for loop closure, MaCORS RTK corrections
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Rafael Spring retweeted
Replying to @jbulltard1
"Yeah bro, I had Muse fill out my extension for unemployment. Shit's fire."
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my github is pure white* *I don't even have an account
“You look at their GitHub and they’re not dark green.” @saradu co-founded Alloy Automation and now runs Ando solo, with $20M from Accel, Index and Emergence. She doesn’t think most of your competitors are real. Every market, in her view, has only a few serious players. The rest talk about the mission and then drift toward quick money. “A lot of solo founders should take solace in that.”
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ついに始まった…… #Drogger #Dot3D
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Replying to @Rafael_L_Spring
@Rafael_L_Spring COLMAP with no install. Drop images or a video into this unofficial browser port and watch keypoints, matches, camera poses and a sparse point cloud appear. Nothing leaves your computer. We made a 30s intro video for it. offlinetools.io/colmap-landi…
OK, launch day!! Over the past few weeks I built a fully browser-resident implementation of COLMAP, using WASM and WebGPU (-- link in reply --). No uploads, no installs, no setup. Just drop images or video and run the pipeline. Then export and drop results into a 3DGS tool of your choice. The first naive implementation was about 10x slower than native but with many optimizations it's now faster than the original! Go give it a try!
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You know what? I'm here for it. Make them cost 50k, 100k, the higher the better. It will make the market value efficient code and punish sloppy code again. Y'all know we're overdue for this.
Don’t shoot the messenger: Why would Nvidia sell any RTX 5090 at <$5K when they can sell the same die as RTX 6000 Pro for $16K? It has massive demand. Today every RTX 5090 they sell is a charity project. Capitalism basics = sell for highest bidder.
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My razor confirmed again. If a person or organization aggressively wants you to believe they are X, they're almost certainly the exact opposite of X. Look at this horror show of a UI called "ComfyUI". Plus their docs are several gens behind and nothing applies anymore. Avoid.
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How much edge compute is needed you ask? If you hard code your physics, control systems are surprisingly cheap. Inputs are a bunch of IMUs + altitude. At a rate of 400 / sec, that's ~ 64 KB / sec of input processing. Output is next to nothing. Could run on a Raspberry Pi easy.
Hate to dox myself a bit but have worked on just about every fighter jet the US has. I have seen some impressive technology over my career but this is a whole other level. I have so many questions and need to know how this works. How much edge compute is needed to make this happen? My first thought is dual processor + 1TB ram. That way it can handle the fuckquintillion process per second. There was zero correction it nailed it 100%.
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Someone should build a headless "AI creative suite" backend that does it all and let everyone else build their UI on top of an API. Runway, Krea, Higgsfield, OpenArt, Vido, Kaiber, Dreamina, Topview, Invideo, JXP, Artlist etc. are all building the exact same backends and it makes no sense.
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Actually, I think this is finally the killer use case for trusted execution environments (TEE). Software companies will push Apple, Google, Microsoft for this, HARD. And I think they will deliver. Nobody wants software vendors gone from their platforms overnight.
Reverse Engineer Anything 😂 Software is done.
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Yep. Also why I think Open Source is kinda dead. The two pillars that kept every Open Source project afloat, attribution and contributor community, are both being eroded by AI at the same time. Ironic that OSS was so wildly successful we're all going back to closed source now.
there is an argument (which I've made privately until now) that one of the principal innovations of the large language model labs is a *legal* innovation, not a technical one by building a system that hoovers up mind-bogglingly large volumes of human information and feeds it into a recombinatorial association machine, the companies have bulldozed the existing IP regime and made the contents of ~all human IP (including the most mundane) searchable, reconfigurable, and usable while also obscuring any trace of origin and eliminating a need to provide credit or attribution. much of the perceived benefit is therefore access and exposure to IP people would not otherwise have had access to, presented behind a system that abstracts the IP from its context and history and presents it as net-new information. I imagine we would have seen ~similar productivity outcomes had Google actually been allowed to make productive use of the Google Books database over a decade ago.
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MacOS has become so ridiculously bad, I now have a constant base load of about 1 full CPU core for it just sitting there, doing absolutely nothing of value. Nothing is happening in my browsers either, I barely have any tabs open.
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Rafael Spring retweeted
What people are missing about the French debt crisis is that it is greatly worsened by the currency union. Yes, the US is $40T in debt, and it will pay like all countries in those circumstances do, print the currency & inflate its way out. Destroy the debt via inflation. 1/
While it lacks the "sex appeal" of nons rioting & burning down beautiful new schools, the biggest news in France has been the financial headlines. France is bankrupt, with annual interest on the national debt being 3X greater than the real growth in GDP. No way out. 1/
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