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    Vangrid's smartphone network for 3D spatial data collection

    One post describes on-chain provenance for Vangrid's 3D captures; another cites 1.25M-plus captures and 450K-plus users.

    3 Sources, 1d ago, first seen 1d ago

    TLDR

    One post describes Vangrid as a smartphone network for real-world 3D captures, with provenance anchored on-chain. Another cites 1.25M-plus captures, 450K-plus users, 4,700-plus attestations and $600K-plus USDC settled. A third argues that the tougher challenge may be keeping spatial data current as physical environments change.

    Combined views

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    3 Sources, first seen 1d ago

    — likes— comments— saves— reposts

    Combined views

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    3 Sources, first seen 1d ago

    — likes— comments— saves— reposts
    Image: @remonnyy on X

    Sentiment

    Positive85%15%Negative

    Summary

    Many accounts welcomed Vangrid's push for real-world spatial data captures in physical AI because it tackles robotics data bottlenecks and decay, while some replies questioned the practicality and costs in changing environments.

    Based on 90 sentiment-bearing replies from 90 accounts across 2 conversations.

    Featured Source

    Sentiment

    Positive85%15%Negative

    Summary

    Many accounts welcomed Vangrid's push for real-world spatial data captures in physical AI because it tackles robotics data bottlenecks and decay, while some replies questioned the practicality and costs in changing environments.

    Based on 90 sentiment-bearing replies from 90 accounts across 2 conversations.

    3 Sources

    C O $ M O 🪐🃏@remonnyyrobots need something different. They need to understand the physical world. ➠ Streets. ➠ Buildings. ➠ Warehouses. ➠ Homes. ➠ The environments where machines will actually operate. And that creates a major data challenge. ⇩ The information robots need cannot simply be scraped from websites. It has to come from the real world itself. That’s what makes @vangrid_io interesting. Vangrid turns smartphones into a distributed network for capturing real world 3D data. ➜ Capture a location. ➜ Turn it into spatial data. ➜ Anchor its provenance onchain. ➜ Make that data available for the next generation of Physical AI. The shift is from: “AI learns from digital information” to: “AI learns how the physical world looks, moves, and changes.” Robots and world models need more than powerful models. They need fresh, ground.level data from the environments they are designed to understand. ◈ Vangrid is building infrastructure for that missing layer of Physical AI. The next AI breakthrough may not come from more text.1d
    HRX@SpaulhrxGM fam ☀️ physical AI needs more than powerful models. it needs real world data to understand how the world actually works. @vangrid_io is building infrastructure to make that possible and their latest numbers are worth paying attention to. ◈ 1.25M+ real world captures ◈ 450K+ users ◈ 4,700+ attestations ◈ $600K+ USDC settled these aren’t just numbers. they represent a growing network collecting and verifying real-world spatial data. as robotics, autonomous systems and world models continue to evolve, access to reliable ground truth data becomes increasingly important. Vangrid is positioning itself right at that intersection of Physical AI, human participation and decentralized infrastructure. with $9M raised and a growing ecosystem, it’s definitely a project worth watching. the next AI breakthrough might not come from more text data but from understanding the physical world. what do you think?23h
    Gohan 🧬@0x99GohanThink about this Vangrid post a bit more. Everyone keeps saying robotics has a data problem. I think that’s only half right. The harder problem might be data decay. A robot can learn from millions of hours of training data, but the second it walks into a warehouse that changed this morning, some of that intelligence becomes useless lol. → So my read on @vangrid_io is shifting a bit, that the real product may be a reality refresh network. Keep updating the parts of the world machines actually care about. Models will get better. Compute will get cheaper. But reality changes every damn minute. Whoever can keep machines closest to the current version of reality might own a pretty important layer of physical AI. That’s the angle I'm caring rn2h
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    3 Sources

    C O $ M O 🪐🃏@remonnyyrobots need something different. They need to understand the physical world. ➠ Streets. ➠ Buildings. ➠ Warehouses. ➠ Homes. ➠ The environments where machines will actually operate. And that creates a major data challenge. ⇩ The information robots need cannot simply be scraped from websites. It has to come from the real world itself. That’s what makes @vangrid_io interesting. Vangrid turns smartphones into a distributed network for capturing real world 3D data. ➜ Capture a location. ➜ Turn it into spatial data. ➜ Anchor its provenance onchain. ➜ Make that data available for the next generation of Physical AI. The shift is from: “AI learns from digital information” to: “AI learns how the physical world looks, moves, and changes.” Robots and world models need more than powerful models. They need fresh, ground.level data from the environments they are designed to understand. ◈ Vangrid is building infrastructure for that missing layer of Physical AI. The next AI breakthrough may not come from more text.1d
    HRX@SpaulhrxGM fam ☀️ physical AI needs more than powerful models. it needs real world data to understand how the world actually works. @vangrid_io is building infrastructure to make that possible and their latest numbers are worth paying attention to. ◈ 1.25M+ real world captures ◈ 450K+ users ◈ 4,700+ attestations ◈ $600K+ USDC settled these aren’t just numbers. they represent a growing network collecting and verifying real-world spatial data. as robotics, autonomous systems and world models continue to evolve, access to reliable ground truth data becomes increasingly important. Vangrid is positioning itself right at that intersection of Physical AI, human participation and decentralized infrastructure. with $9M raised and a growing ecosystem, it’s definitely a project worth watching. the next AI breakthrough might not come from more text data but from understanding the physical world. what do you think?23h
    Gohan 🧬@0x99GohanThink about this Vangrid post a bit more. Everyone keeps saying robotics has a data problem. I think that’s only half right. The harder problem might be data decay. A robot can learn from millions of hours of training data, but the second it walks into a warehouse that changed this morning, some of that intelligence becomes useless lol. → So my read on @vangrid_io is shifting a bit, that the real product may be a reality refresh network. Keep updating the parts of the world machines actually care about. Models will get better. Compute will get cheaper. But reality changes every damn minute. Whoever can keep machines closest to the current version of reality might own a pretty important layer of physical AI. That’s the angle I'm caring rn2h
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