How do I know the decentralized GPUs I rented actually ran my training job?
Opportunity
Decentralized compute networks let anyone rent GPU capacity to train AI models and receive the resulting weights. The user gets a file, not a proof. Nothing today verifies that those weights came from the training run as specified: an operator could return a pretrained checkpoint, run fewer gradient steps, or swap the dataset entirely. Inference verification, checking a single forward pass, is already hard for ZK proofs; training verification is harder by an order of magnitude because gradient descent is a long sequential process, float16 arithmetic introduces non-determinism that breaks bitwise reproduction, and the training data may be private. Every major DePIN compute network relies on reputation and economic incentives to deter cheating, not cryptographic receipts.
Why it matters
The decentralized AI training economy is built on a handshake, and no participant can verify whether the computation they paid for actually happened.
How I score the opportunity
The Opportunity Score is my own read, not a measurement: how much it hurts, how often it bites, and how little exists to solve it today. Higher means I think it is more worth building.
How much pain it causes when it shows up.
How often people actually run into it.
How little good tooling exists for it today.
More problems worth solving
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