arXiv
Open Access
2025
Towards Decentralized and Sustainable Foundation Model Training with the Edge
Leyang Xue
Meghana Madhyastha
Randal Burns
Myungjin Lee
Mahesh K. Marina
Abstrak
Foundation models are at the forefront of AI research, appealing for their ability to learn from vast datasets and cater to diverse tasks. Yet, their significant computational demands raise issues of environmental impact and the risk of centralized control in their development. We put forward a vision towards decentralized and sustainable foundation model training that leverages the collective compute of sparingly used connected edge AI devices. We present the rationale behind our vision, particularly in support of its sustainability benefit. We further outline a set of challenges that need to be addressed to turn this vision into reality.
Topik & Kata Kunci
Penulis (5)
L
Leyang Xue
M
Meghana Madhyastha
R
Randal Burns
M
Myungjin Lee
M
Mahesh K. Marina
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓