The hyperscale, cost-efficient, compute protocol for the world's deep learning models

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Hyperscale

> Use as much compute power as you need, really

Decentralised

> PoS blockchain with forkless runtime updates; connected to off-chain workers/storage

Cost efficient

> Access the world’s latent compute resources at cost price

Rewarding

> Commit your own hardware to the network for generous returns

Trustless

> Probabilistic verification of training with deterministic on-chain challenge mechanisms

Censorship resistant

> No kill switch

Distributed

> Built for large neural networks which train across multiple devices

Green

> Useful work that provides an environmentally friendly yield on processor operations

Backed by

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