Bittensor aims to make machine learning model development as open and unstoppable as Bitcoin’s blockchain, an ambitious goal which might just be possible thanks to a unique distributed ledger called subtensor, designed specifically to support machine learning applications such as smart contracts that automatically process payments.
TAO token is the cornerstone of this ecosystem, providing incentives to all participants involved. Miners earn these tokens by contributing computational resources and intelligence to the network; users in turn can spend tokens to pose queries to TAO and obtain answers.
Answers to user inquiries are provided by an active community of “townspeople”, each running their own machine learning model specialized for one particular task. When users submit queries, these models compare knowledge before returning a proposed answer from within themselves. All this activity is then tracked on a decentralized ledger – much like blockchain – so everything remains fair and secure.
Bittensor uses Yuma as an innovative consensus mechanism to maintain decentralization, in lieu of the more conventional Proof of Work or Proof of Stake approaches. Yuma rewards nodes not on their computing power or token holdings but for their quality of work done; in turn it also increases energy efficiency while encouraging participation across a broader array of nodes.
Verification of our work is conducted by a group of subnet-based validators. They evaluate outputs from each subnet in terms of speed, intelligence, diversity and weight matrix assignment for every node; this ensures that only valuable and trustworthy subnets remain at the top while others fade from prominence.
Dynamic TAO was an upgrade introduced in 2025 that allows each subnet to mint its own tokens for local validation and staking purposes; their value depends on how closely these align with network goals.
Bittensor team still faces significant obstacles; for instance, running a full archival node requires 2TB of storage – more than Bitcoin (641GB) or Ethereum (1248GB). Without solutions for its scalability issues, Bittensor may only be suitable for use cases requiring minimal computational power; thus the project has implemented lighter node options to increase scalability.