【Blockchain Rhythm】Pundi AI has recently made a big move—partnering with Presens Network, the world’s first decentralized spatiotemporal data network. This collaboration seems quite imaginative, combining the technical stacks of both parties.
Simply put: Presens has deployed over 20,000 Pulse nodes and 80,000 presence locations across 141 countries worldwide, transforming human activity data from the real world into machine-readable spatiotemporal data. Pundi AI provides decentralized data infrastructure. Together, they introduce verifiable, contextually rich data sources for AI.
For developers, the benefits are quite direct—they can access verified datasets that accurately reflect real-world activities. Data contributors are also incentivized. More importantly, the entire system adheres to principles of openness, decentralization, and user ownership, avoiding centralized approaches.
From a broader perspective, this is an attempt to connect the physical world with decentralized AI infrastructure, aiming for a more open and human-centric direction. In the context of the accelerating integration of AI and Web3, this approach is indeed quite interesting.
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AirdropHunterXM
· 13h ago
This combination is quite interesting, integrating spatiotemporal data with AI infrastructure, feeling like laying a more realistic data layer.
20,000 nodes covering 141 countries, this scale is indeed quite large, but I’m not sure about the data quality.
Developers need real and verifiable data, which is definitely a pain point, but it still depends on how the ecosystem develops later.
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BlockchainGriller
· 14h ago
Real data + decentralization, this is the way AI should go, overthrow the centralized approach
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CryptoPunster
· 14h ago
Another "world-changing" partnership, 20,000 nodes, 80,000 locations, 141 countries... the numbers are stacking up quite impressively. Now AI can finally see clearly what we're doing. Goodbye privacy, friends.
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DeFiAlchemist
· 14h ago
*adjusts alchemical instruments* okay so they're literally trying to transmute raw spatiotemporal data into verifiable oracle feeds... 141 countries of pulse nodes feeding into a decentralized infrastructure layer? the yield optimization potential here is honestly obscene if the risk-adjusted returns don't crater immediately
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0xLuckbox
· 14h ago
Real data sources can indeed be a bottleneck for AI training. These two combinations don't seem to be just talk on paper.
Are data contributors incentivized? That depends on how the token economy is designed; otherwise, it’s just another PPT project.
With 20,000 nodes across 141 countries, the numbers sound impressive, but the real key is how active they actually are.
Decentralization has been talked about for many years, always as a beautiful vision. Will it finally be realized this time?
From the perspective of spatiotemporal data, it’s still quite interesting, adding more dimensions compared to just on-chain data.
Pundi AI teams up with Presens Network: Building the Global Spatiotemporal Data Intelligence Layer
【Blockchain Rhythm】Pundi AI has recently made a big move—partnering with Presens Network, the world’s first decentralized spatiotemporal data network. This collaboration seems quite imaginative, combining the technical stacks of both parties.
Simply put: Presens has deployed over 20,000 Pulse nodes and 80,000 presence locations across 141 countries worldwide, transforming human activity data from the real world into machine-readable spatiotemporal data. Pundi AI provides decentralized data infrastructure. Together, they introduce verifiable, contextually rich data sources for AI.
For developers, the benefits are quite direct—they can access verified datasets that accurately reflect real-world activities. Data contributors are also incentivized. More importantly, the entire system adheres to principles of openness, decentralization, and user ownership, avoiding centralized approaches.
From a broader perspective, this is an attempt to connect the physical world with decentralized AI infrastructure, aiming for a more open and human-centric direction. In the context of the accelerating integration of AI and Web3, this approach is indeed quite interesting.