If everyone has access to better AI models, what do contributors compete on?
About SN112 THOR
THOR Group@THORMachinesIf everyone has access to better AI models, what do contributors compete on? How well they use them. Models like GPT-6 Astra and NVIDIA’s Flora are getting much better at labelling robotics video. NVIDIA estimates inference compute costs below $1 per hour of footage for Flora. But customer-ready data has to meet timing, description and quality requirements. Verification and rework carry costs too. On Bittensor Subnet 112, THOR is designed to tie rewards to verified output, giving contributors an incentive to improve their models, tools and workflows. A better workflow raises the bar for everyone. The test for THOR is whether that competition delivers reliable robotics training data at a lower total cost. Better AI expands what’s possible. Competition makes it count.
SN112 THOR at a glance
SN112, THOR (α token Ђ), is one of the independent markets on the Bittensor network, each with its own α token and its own price. Its α currently trades at 0.009618 τ (≈ $2.39), against 7,157 τ of pool liquidity. On-chain, the best-delegated validator on it yields about 46.42% APR (simple) and 59.08% APY (compounded), emissions add 0.001952 τ to the pool each block, epochs run every 360 blocks. It was registered at block #5,633,022.
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