The text discusses the Responsible AI Licenses (RAIL) initiative and its impact on machine learning (ML) licensing. The RAIL licenses, including RAIL-S and RAIL-M, are designed to enforce ethical obligations in ML models, but they face challenges such as unclear applicability of copyright law to trained models, potential conflicts with other governance tools, and difficulties in enforcing the obligations against serial harassers or large corporations. Despite these challenges, the licenses have the potential for wide adoption due to their "unavoidable" application, documentation and education efforts, vision and evangelism from practitioners, partnerships with companies like HuggingFace, and successful governance structures. However, it is unclear whether the licenses will be widely adopted, and traditional open communities should build bridges and share knowledge with these new communities.