Diving into Decentralized Training on Bittensor

As part of our mission to improve emission allocation on Bittensor, we’re open-sourcing our internal research on the subnet ecosystem. Our approach is sector-based, starting with decentralized training.

While many deAI teams are working within this space, most are still in early development or conducting permissioned, non-incentivized experiments. Bittensor stands apart, hosting 10 active training networks that range from pre-training to fine-tuning, each with distinct incentive structures. Yet, these efforts remain underappreciated within the broader deAI community.

Through this research, we aim to spotlight Bittensor’s decentralized training initiatives, foster greater awareness in the deAI space, and help ecosystem participants identify the most promising approaches to support and fund.

Access the PDF of our research here.