Software has traditionally benefited from zero marginal costs, enabling high gross margins and recurring revenues, making tech investments lucrative for decades. In contrast, AI operations entail high marginal costs due to scaling laws that require significant investment to improve quality. This principle suggests that while initial costs for cutting-edge AI models remain steep, advancements may lead to decreased costs over time. As a result, infrastructure efficiency and excellence will emerge as pivotal factors for success in the AI domain.

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