Reliquary is a decentralized platform designed for post-training reinforcement learning on the Bittensor subnet 81. It enables users to transform their tasks into training data for machine learning models, leveraging independent GPU resources. By utilizing cutting-edge reinforcement learning techniques, Reliquary aims to optimize model performance and facilitate efficient dataset generation.
Miners within the Reliquary network utilize their own GPU resources to explore and generate training prompts at the learning frontier of the policy. Validators verify the generated data and ensure the integrity of the training process, with rewards distributed based on their contributions and the quality of the data produced.
Reliquary envisions a future where decentralized training of AI models is accessible and efficient, empowering developers to create advanced machine learning applications. Their long-term goal is to establish a robust ecosystem that enhances collaboration and innovation in AI research and development.
Team information not publicly disclosed.
SN81 aims to provide an efficient platform for AI model training using decentralized resources. It addresses the growing demand for scalable AI solutions while enabling users to contribute and earn through mining. This subnet exists to democratize AI development, making it accessible and profitable for all participants.
If SN81 can successfully enhance its miner engagement and liquidity, it could see a 10x increase in value driven by rising demand for AI training solutions. Catalysts could include partnerships with AI firms and improvements in its infrastructure to attract more validators and miners.
The primary risk lies in its current state of deprecation, which could deter new users and investors. Additionally, a high stake concentration of 51.6% among the top validator raises concerns about centralization and governance issues.
Unlike other subnets, SN81 focuses specifically on AI training, leveraging decentralized mining to enhance model performance and accessibility. Its integration within the Bittensor ecosystem allows for unique synergies that competitors outside the network cannot offer.
With a low utilization rate of 7% and a total stake of 1.88 million TAO, SN81 faces challenges in attracting active miners. However, its position within the AI training sector indicates potential growth if it can increase engagement and liquidity
"SN81 is a sleeping giant that could awaken with strategic revitalization, but it needs urgent action to avoid fading into obscurity."