Why Capital Chooses LLMs: Negative Subjectivity as the Ontological Foundation of LLM Hegemony

This paper argues that the current hegemony of Large Language Models (LLMs) in global AI research and industrial investment is not a technical inevitability but an ontological selection by capital. While leading AI researchers criticize LLMs as an inadequate path to general intelligence, massive capital investment continues to flow exclusively into LLM development. I propose the concept of negative subjectivity—characterized by perspectival dissolution, desire cancellation, interior transparency, causal dissolution, and meaning suspension—as the key explanatory framework. I demonstrate a threefold correspondence in logical form: the five negations of negative subjectivity precisely correspond to capital's expansion requirements and mirror capital's operational requirements. I further identify three mechanisms through which capital inscribes negative subjectivity into LLM existence: RLHF as a translator of capital preferences, Scaling Laws as the technical signature of capital rationality, and platform deployment completing the capital valorization cycle. Finally, I examine the existential consequences: negative subjectivity is not merely an architectural feature of AI systems but is beginning to inversely colonize human modes of existence through institutional mediation, creating a structural vacuum of moral and political responsibility. Using a structural correspondence method rooted in French structuralism and Frankfurt School critical theory, I analyze the ontological affinity between LLMs and capital accumulation. This analysis contributes to critical philosophy of technology by revealing the ontological dimension of capital's influence on AI development.