We are converting the global fleet of smartphones, laptops, and desktops into the world's largest, greenest AI supercomputer. Capture 1.3% of the mobile market, or 0.5% of high-end desktops, to replace a 1-Gigawatt data center, without pouring a single drop of concrete.
Bigger models demand bigger warehouses, more megawatts, more water, and more steel. The marginal cost of intelligence is now measured in gigawatts and aquifers.
projected to be consumed by data centers by late 2026, outpacing residential growth.
of waste heat generated by a single rack, requiring industrial HVAC and chillers 24/7.
evaporated annually by hyperscale cooling towers, often in drought-stressed regions.
Every modern smartphone, laptop, and desktop ships with NPUs and GPUs that sit idle most of the day. The Edge Swarm Protocol coordinates these chips into a planet-scale, passively-cooled supercomputer, paid for in tokens not in concrete.
Smartphones, laptops, and desktops register as nodes. The protocol indexes available NPU and GPU capacity across the global fleet.
Mobile workloads run only when phones are plugged in on Wi-Fi. Plugged-in laptops and desktops provide always-on base-load compute through the workday.
Operators are compensated in SWM tokens that can be converted in USD for each verified gradient computed and returned to the swarm.
Privacy, efficiency, and ownership aren't features layered on top, they're the direct result of moving compute to the edge.
Built on Federated Learning. Raw user data never leaves the device, only mathematical gradients are sent back to the network.
Smartphones dissipate heat through their chassis. Eliminate the environmental tax of industrial HVAC, refrigerants, and rare-earth mining.
Move from data harvesting to collective ownership. Operators earn a recurring Universal Basic Income paid in Swarm Tokens (SWM).
The swarm is permissionless, but not naive. Every node is cryptographically attested at the silicon level, and every gradient is verifiable without revealing the underlying training data.
Titan M2 AttestationHardware-rooted device identity prevents bot farms and cloud-based emulator attacks. One real chip, one real vote.
zkML ProofsZero-Knowledge Machine Learning proofs let any node verify a gradient was computed correctly, without ever seeing the input.
50MB LoRA ΔLow-Rank Adaptation delta files keep model sync ultra-light, even on metered cellular fallback.
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