Title: Re-decentralization in Machine Learning 
Abstract: 
Redecentralization has emerged as a growing trend in response to concerns about model’s control, privacy, and sustainability. However, hyperscale cloud platforms continue to outperform decentralized alternatives on dimensions that most users prioritize, including usability, availability, and operational resilience. Conversely, centralized systems may underperform with respect to privacy and environmental sustainability—dimensions that, to date, appear to have limited influence on user adoption. This tension raises a central question: can decentralized systems close the gap on user-centric performance metrics, or can centralized systems be redesigned to better address privacy and sustainability concerns?