Top AI labs like OpenAI and Anthropic engage in a 'Cournot Equilibrium' by competing on the supply of compute and data centers, not by undercutting each other on price. This strategy aims to create high barriers to entry and maintain high prices for access to frontier models.
The paradoxical financial state of AI labs: individual models can generate healthy gross margins from inference, but the parent company operates at a loss. This is due to the massive, exponentially increasing R&D costs required to train the next, more powerful model.
A major factor in a star's appeal is their real-world persona and narrative, from celebrity relationships to public appearances. This off-screen context drives audience fixation and cannot be authentically replicated by an AI, serving as a significant moat for human talent against purely synthetic actors.
By stating Bytedance's AI model 'undercuts the ability of human talent to earn a livelihood,' Hollywood's actors' union (SAG-AFTRA) implicitly admits the technology is good enough to be a credible threat. Their condemnation serves as a powerful, albeit unintentional, endorsement of the AI's capabilities.
The argument that only software engineering is fully automatable is flawed. Much of the context for other white-collar jobs is also logged in digital formats like emails, Slack messages, recorded calls, and documents. The challenge isn't a lack of data, but its unstructured and dispersed nature.
Anthropic's aggressive legal stance against the popular open-source project 'Claude Bot' backfired. It not only alienated developers but also created a perfect opportunity for rival OpenAI to acquire the project (renamed 'OpenClaw'), turning a competitor's PR fumble into a major strategic win and ecosystem capture.