"Selling coffee beans to Starbucks" - How will the AI ​​boom make AI giants fall behind

Basic models are increasingly seen as interchangeable commodities, with AI startups focusing on fine-tuning and interface design rather than pre-training. The diminishing returns of hyperscale models have caused people to turn their attention to post-training and reinforcement learning. This trend weakens the dominance of major AI labs such as OpenAI and Anthropic as open source alternatives and application layer competition weakens their pricing power. While underlying model companies still maintain their advantages in branding and infrastructure, the lack of a lasting technology moat means that in the future they may become low-margin back-end suppliers rather than industry leaders.