Background for "Understanding the diffusion of large language models"

Abstract

The diffusion of large language models (LLMs) has a complex relationship with the risks posed by transformative AI (TAI). Diffusion can increase the risk of TAI by accelerating the pace of capability development and increasing the number of actors capable of building TAI systems. This, in turn, could lead to a multipolar scenario where numerous actors are capable of misusing TAI, or to a single actor deploying TAI prematurely. However, diffusion can also offer some benefits, such as increased scrutiny of leading AI developers, faster progress on AI alignment research, and improved defense against misuse of AI. The article analyzes the diffusion of GPT-3-like models through a database of case studies, examining the mechanisms of diffusion, including open publication, replication, and incremental research. It explores the influence of factors like compute sponsorship and open-source software, concluding that diffusion can be net-beneficial if the right things are diffused carefully. – AI-generated abstract