XYO’s Markus Levin: Why a data-native L1 could become AI’s “proof of origin” backbone
In the latest SlateCast episode, XYO co-founder Markus Levin joined CryptoSlate’s hosts to unpack why decentralized physical infrastructure networks (DePIN) are moving beyond niche experiments—and why XYO built a purpose-built Layer-1 to handle the kind of data AI and real-world applications increasingly demand.
Levin’s ambition for the network is blunt: “First, I think XYO is gonna have eight billion nodes,” he said, calling it a stretch goal—but one he believes matches where the category is headed.
DePIN’s “every corner of the world” thesis
Levin framed DePIN as a structural shift in how markets coordinate physical infrastructure, pointing to rapid growth expectations for the sector. He cited a World Economic Forum projection that DePIN could expand from roughly today’s tens of billions to trillions by 2028.
For XYO, scale is not hypothetical. One of the hosts noted that the network has grown “with over 10 million nodes,” setting the stage for a conversation focused less on “what if” and more on what breaks when real-world data volume becomes the product.
Proof of origin for AI: the data problem, not just compute
Asked about deepfakes and the collapse of trust in media, Levin argued that AI’s bottleneck isn’t only computation—it’s provenance. “Whereas DePIN, what you can do is you can, uh, prove where data comes from,” he said, outlining a model where data can be verified end-to-end, tracked into training pipelines, and queried when systems need ground truth.
In his view, provenance creates a feedback loop: if a model is accused of hallucinating, it can check whether the underlying input is verifiably sourced—or request new, specific data from a decentralized network rather than scraping unreliable sources.
Why a data-native Layer-1 matters
XYO spent years trying not to build a chain, Levin said—operating as middleware between real-world signals and smart contracts. But “nobody built it,” and the network’s data volume forced the issue.
He explained the design goal simply: “Blockchain can’t bloat… and it’s just built for data really.”
XYO’s approach centers on mechanisms such as Proof of Perfect and “lookback” style constraints intended to keep node requirements lightweight, even as datasets grow.
COIN onboarding: turning non-crypto users into nodes
A key growth lever has been the COIN app, which Levin described as a way to transform mobile phones into XYO network nodes.
Rather than pushing users into immediate token volatility, the app uses dollar-tied points and broader redemption options—then bridges users into crypto rails over time.
Dual token model: aligning incentives with XL1
Levin said the dual token system is designed to separate ecosystem rewards/security from chain activity costs. “We’re extremely excited about this dual token system,” he said, describing $XYO as the external staking/governance/security asset and $XL1 as the internal gas/transactions token used on XYO Layer One.
Real-world partners: charging infrastructure and mapping-grade POI data
Levin pointed to new partnerships as early “killer app” momentum inside the broader DePIN ecosystem, citing a deal with Piggycell—a large South Korean charging network that needs proof-of-location and plans to tokenize data on XYO Layer One.
He also described a separate proof-of-location use case involving point-of-interest datasets (hours, photos, venue info), claiming a major geolocation partner found issues in its own dataset “in 60% of the cases,” while XYO-sourced data was “99.9% correct,” enabling downstream mapping for large enterprises.
Taken together, Levin’s message was consistent: if AI and RWAs need trustworthy inputs, the next competitive frontier may be less about faster models—and more about verifiable data pipelines anchored in the real world.
The post XYO’s Markus Levin: Why a data-native L1 could become AI’s “proof of origin” backbone appeared first on CryptoSlate.
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