In their discourse on open-source AI, Red Hat emphasizes the growing influence of community contributions on enhancing AI models. They argue that community-driven improvements are primarily made through model weight modifications, promoting a narrative that these enhancements can foster innovation in AI. However, critics argue that this approach exploits volunteer work without providing adequate credit, and the lack of access to original training data undermines the open-source ideal. Critics see this stance as merely repackaging existing ideas rather than fostering genuine innovation, calling into question the authenticity of Red Hat's commitment to true open-source principles.