AuroraSubnet
AuroraSubnet is a modular subnet prototype for the Bittensor ecosystem that introduces a bonding curve-based incentive mechanism and validator quality metrics (uptime, response time). We provide node
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描述
AuroraSubnet — Professional Project Description
AuroraSubnet is a modular DeFi + AI subnet prototype designed for the Bittensor ecosystem, focusing on transparent incentive mechanisms, validator quality evaluation, and full reproducibility. The project introduces a bonding curve–based reward model combined with measurable validator performance metrics, including uptime and response time, to ensure fair and data-driven reward distribution.
AuroraSubnet provides a complete simulation environment that allows developers and researchers to create subnets, simulate validator behavior, stake tokens, and observe reward allocation in real time. A smart reward allocator dynamically distributes incentives based on validator quality, enabling experimentation with incentive design and network dynamics.
The system includes an interactive dashboard that visualizes subnet creation, staking flows, validator simulations, and transparent reward distribution, making complex subnet mechanics easy to understand and audit. AuroraSubnet is built with reproducibility as a core principle—anyone can run the full stack locally using a single command (docker-compose up) and reproduce the same results consistently.
By combining DeFi incentive models, AI-driven evaluation metrics, and developer-friendly tooling, AuroraSubnet aims to serve as a practical reference implementation for building fair, transparent, and reproducible subnets in decentralized AI networks.
黑客松進展
During the hackathon, we designed and implemented a functional prototype of AuroraSubnet, focusing on incentive transparency, validator evaluation, and reproducibility within the Bittensor ecosystem. We defined the subnet architecture and implemented a bonding curve–based incentive mechanism to model dynamic staking and reward behavior. To ensure fair validator evaluation, we introduced validator quality metrics, including uptime and response time, and integrated them into a smart reward allocator that distributes rewards based on measurable performance. We built a node and validator simulation framework that allows testing different validator behaviors and network conditions without deploying to a live network. In parallel, we developed an interactive dashboard that visualizes subnet creation, staking flows, validator simulations, and transparent reward distribution in real time. A key focus of the hackathon was reproducibility and developer experience. We containerized the entire system using Docker and provided a one-command setup (docker-compose up) to ensure anyone can run, test, and reproduce the subnet behavior locally. Automated demo flows were added to showcase the full lifecycle of subnet creation, staking, validation, and reward allocation. By the end of the hackathon, AuroraSubnet reached a complete end-to-end demo stage, demonstrating a transparent, fair, and reproducible approach to subnet design for decentralized AI networks.
技術堆疊
籌資狀態
AuroraSubnet is currently bootstrapped and developed entirely by the founding team during the hackathon. We have not raised external funding yet and are focused on validating the technical design, incentive mechanisms, and subnet performance through a working prototype and reproducible demos. Following the hackathon, we plan to explore strategic grants, ecosystem funding, and early partnerships within the Bittensor ecosystem to support further development, validator onboarding, and long-term subnet sustainability.