Conference: Pushing Towards Open-Source AI

本次研讨会将让研究人员和实践者齐聚一堂，了解为生产性人工智能构建强大的开源生态系统所面临的关键挑战。作为生成性人工智能基础的技术系统不同于其他开源系统，并提出了一系列独特的问题。该研讨会服务于一个仅在开源或学术机器学习社区中无法实现的利基市场，并将把研究人员和开源开发人员联系起来，专门针对核心共同挑战。研讨会的成果将成为促进安全和公平的开源人工智能的路线图，可以用来提高美国的经济增长和工人生产率。开源软件开发对世界各地不同行业的巨大增长做出了贡献。这个研讨会提案的目标是研究如何为生成性人工智能培育一个强大的开源生态系统，这个生态系统可以与一般的开源软件生态系统相媲美。生成性人工智能背后的技术系统提出了新的和复杂的问题，使之不能轻而易举地适应当前的开源最佳实践。生成式人工智能的成功也不主要是由于代码；它们是几个因素的产物，包括：仔细协调的数据管理、战略协调的训练运行、利用大量人类反馈进行调优，以及对现实用例的严格评估。研讨会将侧重于以下四个主题，以定义和解决开源生成性人工智能的核心挑战：面向更广泛用户的模型适应；针对人类反馈的开放生态系统；对伦理、安全和准确系统的评估；以及支持分散的人工智能开发。研讨会将努力确定人工智能开发的开源模型中的挑战和机遇，这些挑战和机遇将作为未来几年的路线图。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This workshop will bring together researchers and practitioners to understand the key challenges in building a robust, open-source ecosystem for generative AI. The technological systems that underlie generative AI differ from other open-source systems and present a unique set of issues. This workshop serves a niche that is not being fulfilled in either the open-source or academic machine learning community alone, and will connect researchers and open-source developers to specifically target core shared challenges. The outcomes of the workshop will serve as a roadmap to foster open-source AI that is safe and equitable and can be deployed to increase American economic growth and worker productivity. Open-source software development contributes to enormous growth in diverse industries across the world. The goal of this workshop proposal is to study how to foster a robust open-source ecosystem for generative AI that is comparable to the general open-source software ecosystem. The technological systems underlying generative AI present novel and complex issues that make it non-trivial to adapt current open-source best practices. Successes of generative AI are also not primarily due to code; they are the product of several factors, including: carefully coordinated data curation, strategically coordinated training runs, tuning with large-amounts of human feedback, and rigorous evaluation on realistic use-cases. The workshop will focus on the following four themes to define and address the core challenges of open-source generative AI: model adaptation for a broader range of users; open ecosystems for human feedback; evaluation of ethical, safe, and accurate systems; and supporting decentralized AI development. The workshop will strive to identify the challenges and opportunities in open-source models for AI development that will serve as a roadmap for the coming years.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.