Head of Web3 @GEODNET | Building the infrastructure of Physical AI

Palo Alto, CA
Joined November 2014
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Honored to speak at @token2049 on The Rails for Physical AI. 🎤 Every robot, drone, and autonomous machine entering the real world needs to know exactly where it is. @GEODNET delivers that centimeter-level positioning layer: 22K+ stations across 175 countries. Thank you to everyone who stopped by. 📍
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🌍 GEODNET is evolving into the rails for Physical AI. From centimeter-level positioning to verified real-world intelligence, @GEODNET is building the infrastructure that connects AI to the physical world. 🤖 AI needs more than data. It needs to understand, navigate, and interact with reality. GEODNET is laying the rails. The Physical AI revolution is coming. 🚀 #GEODNET #PhysicalAI #DePIN #AI #Web3
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In token2049 now
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If AI performs 99% of a job and a human performs only 1%, how could human make a living? Think about luxury goods. The raw materials and manufacturing may represent only a fraction of the selling price. A large part of the value comes from: brand, authenticity, scarcity and trust. Human participation in an AI economy could work in a similar way. Imagine an AI completing almost an entire workflow—but in the middle some facts data can not be verified until a real human physically visits a location, observes reality and provides input. That small human contribution may become the value anchor for the entire job. Society and regulators could even decide that certain AI-driven activities require verified human participation. Not because humans can calculate faster than AI. But because physical presence, accountability and independent verification are scarce. AI supplies intelligence at nearly zero marginal cost. Humans supply something AI cannot manufacture: verified presence in the real world. So perhaps the future-of-work question isn’t only: “Which jobs will AI replace?” It may also be: “Which parts of the AI economy should only humans be allowed to validate—and how much should that validation be worth?” That is the bigger idea behind WorkForAI. #WorkForAI #FutureOfWork #AI #ProofOfLocation #TokenRun
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What if AI eventually performs 99% of many jobs? The natural reaction is: What happens to humans? But there may be another way to look at it. AI could research the problem, analyze millions of records, build the plan and generate the final report. Then, somewhere in that workflow, it still needs someone to: • visit a physical location • inspect something in person • take a live photo or video • verify that an event actually happened • collect local data • provide real-world feedback That final 1% may be impossible to generate synthetically. Someone has to actually be there. So instead of competing with AI to perform the 99% it increasingly does better, humans could become the trusted physical layer that AI depends on. AI does the digital work. Humans provide verified reality. AI creates the task. A human completes the physical-world part. Proof of Location verifies the result. That’s the idea behind WorkForAI. But there’s another assumption worth challenging: If humans perform only 1% of the work, should they receive only 1% of the value? #WorkForAI #FutureOfWork #AI #TokenRun
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AI has already consumed most of the useful public data on the internet. So where does the next major source of AI data come from? Probably not another website. It comes from the physical world. What does this street look like right now? Is this store actually open? How long is the line? Is this product really on the shelf? What is happening at this location today? These answers cannot simply be generated from old internet data. They require someone—or something—to observe the real world. That creates a massive new data layer for AI: Live. Local. Human-verified. Proof-of-location data. AI can reason, plan and generate at enormous scale. But it cannot independently be everywhere. Humans can. The internet helped train today’s AI. The physical world may train—and power—the next generation. And that leads to a much bigger question: What role will humans play in that economy? #WorkForAI #AI #PhysicalAI #TokenRun #GEODNET
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David Chen retweeted
We just had to celebrate. 🎉 Big milestone last week. GEOD is now live on Coinbase and we took a moment to celebrate the people who made it happen. Grateful to the whole GEODNET community who helped us get there. We're just getting started. 🚀
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Spot trading for GEODNET (GEOD) will go live on 23 June 2026. The opening of our GEOD-USD trading pair will begin on or after 9AM PT, if liquidity conditions are met, in regions where trading is supported.
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David Chen retweeted
May closed with a bang. 🔥 Burns dipped mid-month, then snapped back hard - near $170K in the final week alone as $GEOD continues to grow momentum. 20,000+ miners. 80% of revenue burned. Every week. Why does it matter? The burn isn't speculation. It's real infrastructure, where each miner is doing real work to expand the foundation for drones, robots, and an autonomous future. Want in? Follow us.
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David Chen retweeted
GEODNET is gaining momentum. Meet David Chen (@mvrender), the blockchain leader forging the path for GEODNET's network usage and token stability.
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. @GEODNET might be one of the most important DePIN networks for robotics. - $7M ARR - 20,000+ base stations. - 40+ paying Web2 customers. I sat down with @mvrender to break down how GEODNET is becoming the location layer for robots and drones TIMESTAMPS 00:00 - What Is Geodnet? 04:13 - Why Customers Choose Geodnet? 06:29 - Robotics Narrative 12:12 - Future of Robots
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A network 4× larger than the closest web2 competitor with costs 80–90% lower and $7M ARR This @GEODNET clip previews one of the biggest infra stories in web3 robotics and DePIN. Full interview with @mvrender dropping soon 👀
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David Chen retweeted
When it comes to robots, centimeter precision is what turns automation into true autonomy. @mvrender See David’s insights at KBW on $GEOD ’s unique market position👇
Replying to @LunarStrategy
2/ Why robots need GEODNET? Autonomous systems need precise location data to navigate safely. Regular GPS gives you 1-5 meters of accuracy. GEODNET narrows it down to centimeters. That level of accuracy enables obstacle avoidance and full autonomy.
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Thanks to @geodnet @LayerDrone @n_amberland for introducing us to our future robot overlords in Singapore! 🫡 @blakeminhokim @levitate_labs
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Try some AI image generator
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Wrapping up an amazing Boba Tea Party with the Geodnet & Inflection community! 🧋✨ Big thanks to @geodnet , @OpenledgerHQ , and @MMTFinance for co-creating such a vibrant space. Here’s a quick glimpse of the vibes from the day 👇🏼
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