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So much of the complexity for multimodal/robotics data is just getting the right format that's both flexible and performant. I dig into it here in the context of 3d reconstruction. I'm hoping to build an opensource arkit like pipeline and explain the first bit for the data pipeline here!...

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Pablo Vela

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10,804 görüntüleme • 1 ay önce •via X (Twitter)

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Everyone is selling robotics data. Most of it isn't what you actually need. The right kind of data depends entirely on what you're training. And that's the question almost no one asks before the check gets cut.
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Here is a recreation of the World Cup final on a desk! It fetches game data from an API and other sources, and stores it in Supabase to project it onto a desk in an immersive experience! Amazing to see what Codex and Supabase can create for us!

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Package a project for a futuristic city in the middle of the desert, fool the public that it is for the future, gather more than $500 billion, and then scale it back to data centers and a survival city for the elites. The Line is not canceled; it's scaled down like it was always intended. They will pour trillions of dollars into the data centers and a 3-mile-long doomsday bunker protected by 500-meter walls and an entire ecosystem because the outside weather and cosmic radiation will be terrible.

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Rise is live. The developer SDK for Phoenix Perpetuals is here, in TypeScript and Rust. Build a trading bot. Power perps inside your existing product. Plug into live market data and trader state. One ergonomic surface for all of it.

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Some updates on the multiview vistadream pipeline with Rerun! Rerun came in extremely useful here, as being able to visualize depths at each stage of the pipeline allowed me to debug some nasty bugs. Since the last time, I was only working with a single image input. I've added in VGGT as my multiview pose + depth estimator. It works REALLY well for getting camera poses, but the depths are not that great. To try and fix that, I estimated depth maps from MoGeV2 for each of the views, and scale+shift aligned them so that they would match up to the confident sections of VGGT's depth predictions. You can see in the video just how much sharper the visualized 2d depth maps are! The biggest issue continues to be the multiview consistency 🫠 That's up next, along with actually training the Gaussian splat. Lots of work went into actually understanding inputs+outputs for VGGT. I had some funky bugs where the confidence values would all collapse to true I'm also really excited for this pipeline to use Difix3D+ Nvidia instead of Flux Inpainting, it seems like a better suited for a multiview pipeline.

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The influence of set-piece coaches in the Premier League seems to have grown significantly in recent years, but how much of an impact have they had, and is it just a fad? Here, our new-look interactive article analyses the data behind Premier League set-pieces.

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A new look for the new era of data movement Over the past 12+ months we've been focused on building out mump2p, our Ethereum data propagation product, onboarding top validators to test it with, and educating our peers on the merits of decentralized coding. Now with the launch of mump2p on Ethereum mainnet firmly in our sights, it feels like the right time to give Optimum's visual identity a refresh-- something to match the sleek, powerful data acceleration network we're deploying. The advent of RLNC powered data movement frees blockchains from the networking bottleneck, so they can perform at the pace demanded by our ever-expanding digital economy. The new era begins soon with data propagation on Ethereum, more chains and use cases to follow. Time to raise the ceiling for blockchains, and do it in style.

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Spent the past few weeks building a fully automated pipeline for egocentric manipulation data with Kyle Jiang. Any new manipulation task captured using our own wearable sensing platform can now be dropped into the same pipeline with minimal manual fix. Instead of raw videos and annotations, we transform human demonstrations into robot-ready training data. Next, we're bringing touch into the loop with tactile gloves.

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🆕 CrowdStrike is acquiring Onum to supercharge autonomous cybersecurity with real-time data pipelines. If Falcon SIEM is the engine of the modern SOC, Onum is both the pipeline + filter — streaming high-quality, filtered fuel quickly into the engine to drive more efficient and superior performance. Onum delivers transformational advantages across three critical dimensions: ⚡ Speed: Delivers 5X more events per second than its nearest competitor and processes security and observability data in real-time versus legacy batch and store methods. ⚡ Cost: Smart filtering reduces data storage costs by 50% through intelligent optimization. ⚡ Superior Outcomes: Real-time pipeline detection starts before data enters the Falcon platform, delivering up to 70% faster incident response with 40% less ingestion overhead. The future of cybersecurity is here – built on real-time, high-fidelity data. 👉 Learn more:

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This Huawei ad I just walked by at Munich airport hit me like a ton of bricks. Huawei watch? HUAWEI HEALTH? Delivering your intimate, real-time location, behavioral & physiological data (heart rate??) directly to the CCP is absolutely insane. I hadn't even considered how many of these watches must be on people hands right now, and how powerful a tool of espionage (the next-level invasive data gathering!) the CCP has at its disposal. Grok, what countries have the biggest usage per capita of huawei watch? Also, considering what I wrote earlier in this post, and given that Huawei is bound by Chinese law to share all data it has access to with the the Chinese government (and not disclose it is doing so), what impact is there for personal privacy and security for users of Huawei watch?

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Joined the ongoing AIOZ AI Pneumonia Chest X-Ray Classification Challenge? Smart Tip: Focus on data quality before tuning your model. → Audit the X-rays first for variations in brightness, contrast, and resolution. → Apply preprocessing techniques such as normalization, resizing, and histogram equalization. → Add controlled data augmentation, such as rotations, flips, and subtle distortions, to improve robustness without losing clinical signals. Build a stronger pipeline from the data up! Join the challenge and explore medical AI in practice.
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Joined the ongoing AIOZ AI Pneumonia Chest X-Ray Classification Challenge? Smart Tip: Focus on data quality before tuning your model. → Audit the X-rays first for variations in brightness, contrast, and resolution. → Apply preprocessing techniques such as normalization, resizing, and histogram equalization. → Add controlled data augmentation, such as rotations, flips, and subtle distortions, to improve robustness without losing clinical signals. Build a stronger pipeline from the data up! Join the challenge and explore medical AI in practice.

AIOZ Network

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💥❓ Blow up the "Power of Siberia" like the "Nord Stream"? — Fox News called to destroy the Russian gas pipeline ⚡️On Fox News, there was practically a call for sabotage against Russia: "So, Putin is laying a big old pipeline to China." 🇷🇺🇨🇳 The host emphasized that the project connects Russia and China. "It is supposed to be completed in the next decade and supply 15% of China's energy needs," — the program said. ❗️"Russia and China are getting closer. Someone might have to blow up this pipeline like the 'Nord Stream'," — the host concluded. - Ostashko
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💥❓ Blow up the "Power of Siberia" like the "Nord Stream"? — Fox News called to destroy the Russian gas pipeline ⚡️On Fox News, there was practically a call for sabotage against Russia: "So, Putin is laying a big old pipeline to China." 🇷🇺🇨🇳 The host emphasized that the project connects Russia and China. "It is supposed to be completed in the next decade and supply 15% of China's energy needs," — the program said. ❗️"Russia and China are getting closer. Someone might have to blow up this pipeline like the 'Nord Stream'," — the host concluded. - Ostashko

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