BitMind
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What is BitMind?
Adversarial detection
BitMind operates Bittensor Subnet 34. Its current GAS architecture pairs detector models with generative models. Miners submit models instead of maintaining live inference endpoints. Validators evaluate them in batches against a changing benchmark. Generators contribute synthetic images and videos to a public corpus. Detector scores measure their ability to identify synthetic material. New generative samples continually refresh the challenge set.
Incentives and deployment
Detector rewards depend on measurable classification improvements. Generators earn rewards for validated samples that fool leading detectors. An entrance test screens submitted detectors before full evaluation. The current incentive model uses a decaying threshold for improvements over the leading score. Selected models can be deployed through BitMind's production services. Subnet 34 has its own alpha token within Bittensor. That token trades against TAO in the subnet's liquidity pool. Staking TAO into the subnet converts it into subnet alpha at the pool price. Unstaking reverses that conversion, subject to fees and slippage.
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