Companies, including market rivals, have long collaborated on the development of open source software (OSS), resulting in a tangle of co-operation and competition known as "open source co-opetition". While prior work investigates open source co-opetition in OSS projects that are hosted by vendor-neutral foundations, we have a limited understanding thereof in OSS projects that are hosted and governed by one company. Given their prevalence, it is timely to investigate open source co-opetition in such contexts. Towards this end, we conduct a mixed-methods analysis of three company-hosted OSS projects in the artificial intelligence (AI) industry: Meta's PyTorch (prior to its donation to the Linux Foundation), Google's TensorFlow, and Hugging Face's Transformers. We contribute three key findings. First, while the projects exhibit similar code authorship patterns between host and external companies (80%/20% of commits), collaborations are structured differently (e.g., decentralised vs. hub-and-spoke networks). Second, host and external companies engage in strategic, non-strategic, and contractual collaborations, with varying incentives and collaboration practices. Some of the observed collaborations are specific to the AI industry (e.g., hardware-software optimizations or AI model integrations), while others are typical of the broader software industry (e.g., bug fixing or task outsourcing). Third, single-vendor governance creates a power imbalance that influences open source co-opetition practices and possibilities, from the host company's singular decision-making power (e.g., the risk of license change) to their community involvement strategy (e.g., from over-control to over-delegation). We conclude with recommendations for future research.

翻译：长期以来，包括市场竞争对手在内的企业一直在开源软件（OSS）开发中进行协作，形成了合作与竞争交织的复杂状态，即"开源竞合"。尽管已有研究探讨了由供应商中立基金会托管的OSS项目中的开源竞合现象，但对于由单一企业托管和治理的OSS项目中的竞合关系，我们的理解仍较为有限。鉴于此类项目的普遍性，及时开展相关研究具有重要价值。为此，我们对人工智能（AI）领域三个企业托管的OSS项目进行了混合方法分析：Meta的PyTorch（捐赠给Linux基金会前）、Google的TensorFlow以及Hugging Face的Transformers。本研究得出三个关键发现：首先，虽然这些项目在代码提交量上呈现出托管企业与外部企业相似的比例关系（80%/20%），但协作网络结构存在显著差异（如去中心化网络与中心辐射型网络）。其次，托管企业与外部企业之间形成了战略性、非战略性及契约性三类协作模式，各具不同的激励动因与实践方式。部分协作模式具有AI行业特性（如硬件-软件协同优化或AI模型集成），而其他模式则普遍存在于更广泛的软件行业（如漏洞修复或任务外包）。第三，单供应商治理模式造成的权力失衡深刻影响着开源竞合实践的可能性边界——从托管企业的单方决策权（如许可证变更风险）到其社区参与策略（如从过度控制到过度授权）均产生系统性影响。最后，本文为未来研究提出了方向性建议。