founder: @fiercealliancee • affiliate: @arkham • computer/software engineer
Joined October 2020
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every transaction has a cost. where that fee goes matters too.
on the @PRDCTR_IO network, $PRD pays the gas fees, and those fees go to node operators.
that creates a direct link between activity on the network and the people helping run it.
- node operators validate transactions and help maintain network security.
- they can earn rewards for running their nodes, with fee shares tied to uptime.
it’s a practical part of the ecosystem worth paying attention to. the network has users, but it also has operators supporting what happens behind the scenes.
🤝 Paid partnership
rick retweeted
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rick retweeted
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the network was already live before the funding news broke.
@vangrid_io completed its $9m seed round with backing from hashkey capital, animoca brands, borderless capital, crypto.com capital, gate labs and mapleblock capital.
the round was announced in august 2026, after the project had moved beyond stealth.
the next step is expanding spatial data coverage and fulfilling more location specific requests.
🤝 Paid partnership
rick retweeted
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what happens when prediction markets move beyond crypto?
think sports, elections, technology, finance and major world events. all of them create questions people want answers to, but each brings its own context and audience.
@PRDCTR_IO opens the door to markets around these different categories, giving prediction market infrastructure a wider field to serve.
the opportunity goes beyond guessing where a token’s price will be tomorrow. it’s about putting expectations around events across the world to the test.
🤝 Paid partnership
imagine being able to request spatial data for a specific location and have contributors capture what’s needed.
that’s the idea behind on demand data collection.
@vangrid_io connects location specific requests with a distributed network of contributors, creating a way to gather spatial data based on actual demand.
it’s a different way to think about data collection. the request comes first, and contributors can help fill the gap.
which places do you think physical ai will need better spatial data for first?
🤝 Paid partnership
there’s more to a prediction market than picking an outcome and waiting to see if you’re right.
with @PRDCTR_IO, the network behind those markets deserves a closer look, and nodes are part of that conversation.
if you’re exploring the project, look into how nodes fit into the ecosystem and what participation actually involves.
understanding the network gives you a fuller picture of what keeps the ecosystem going.
🤝 Paid partnership
where did the data come from? that’s worth knowing before putting it to work in ai.
spatial data needs more than a useful format. developers also need a way to verify its origin and trace its record.
@vangrid_io uses edge-level fingerprints for captures and anchors batch hash roots on Base through Ethereum Attestation Service, creating an onchain record that can be independently checked.
it gives developers more visibility into where spatial data came from and how its provenance is recorded.
because when ai relies on data from the physical world, its origins shouldn’t be a mystery.
🤝 Paid partnership
a token’s real value proposition starts with what it lets people do.
for prediction market infrastructure, utility can connect the people using the network with the systems that keep it running.
$PRD sits within the @PRDCTR_IO ecosystem, with its role tied to the network’s operation and participation.
the ticker gets attention. the utility is what gives it a purpose beyond the chart.
🤝 Paid partnership
rick retweeted
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rick retweeted
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a map can be accurate when it’s made and outdated by the time the world around it changes.
construction alters access points. temporary barriers block familiar routes. new structures change how a space can be navigated.
@vangrid_io enables spatial data to be collected for specific locations on demand, giving physical ai systems a way to access information about the environments they need to understand.
for autonomous systems, knowing what a place looked like yesterday may not be enough.
🤝 Paid partnership
the crowd can get the prediction wrong when everyone starts with bad information.
two people can study the same event and reach opposite conclusions. add missing context, a misleading headline or an unreliable source, and the picture gets even messier.
trusted media plays an important role here. @PRDCTR_IO connects real world events and trusted media with prediction markets, giving people events to forecast and outcomes to track.
before trusting a prediction, look at the quality of the information behind it.
🤝 Paid partnership
a satellite can show you an entire city. it can’t tell you everything you’d encounter walking through it.
the entrance tucked behind a building. the narrow passage between two structures. the obstacles along a pavement.
@vangrid_io uses smartphones as a distributed capture network to collect spatial data from specific places on demand.
that matters because physical ai needs ground level detail to understand real environments, and collecting it at scale remains a challenge.
the world has been mapped from above. there’s still plenty to capture at ground level.
🤝 Paid partnership
one person can be certain. a thousand people can still get it wrong.
but when people with different information, experience and perspectives weigh in on the same outcome, you get a wider range of views to work with.
that’s the idea behind collective forecasting. the goal isn’t to find the loudest opinion, but to see how different expectations come together around a question.
with @PRDCTR_IO bringing trusted media and real world events into prediction markets, those opinions can be weighed against what actually happens.
the crowd won’t always be right. the interesting part is seeing how its predictions hold up against reality.
🤝 Paid partnership
rick retweeted
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an ai can describe a street perfectly and still have no idea how to move through it.
a robot needs more than language skills. it needs spatial information about the world around it, from the layout of its surroundings to the obstacles in its path.
that’s the gap @vangrid_io is working on, building a decentralized spatial data layer to give physical ai and autonomous systems access to real world ground truth.
because understanding the world on paper is one thing. navigating it is another.
🤝 Paid partnership
