标题： 面向边缘的去中心化和可持续基础模型训练 显示英文标题

标题： Towards Decentralized and Sustainable Foundation Model Training with the Edge

摘要： 基础模型处于人工智能研究的前沿，因其能够从大量数据集中学习并适应各种任务而受到青睐。 然而，它们显著的计算需求引发了环境影响以及在开发过程中集中控制的风险问题。 我们提出了一种去中心化和可持续的基础模型训练愿景，该愿景利用了偶尔使用的连接边缘人工智能设备的集体计算能力。 我们提出了这一愿景的依据，特别是为了支持其可持续性优势。 我们进一步概述了一组需要解决的挑战，以将这一愿景变为现实。 显示英文摘要

摘要： 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.