Democratizing LLM Training with the Edge: Challenges, Systems, and the Road Ahead
The growing computational power of modern GPU data centers has let a few industrial giants train and deploy large language models (LLMs) on massive amounts of data. Yet the sheer scale of these models and their training data makes centralized development increasingly hard to sustain, and at the same time shuts out smal...
Zi-Yue Luo, Jiaxuan Cai, C. Le Denmat et al.
· 0 citations