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基盤モデル時代の終焉:オープンウェイトモデル、ソブリンAI、そしてインフラとしての推論
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ポイント
- 大規模言語モデルの事前学習が競争優位性につながらない構造的な真実が明らかになった研究。
- オープンソースモデルが最先端の性能に到達し、推論コストがほぼゼロになったことが重要である。
- AI業界は経済、技術、商業、政治の4つの軸で同時に再構築され、オープンウェイトモデルが主権管理の手段となる。
Abstract
The foundation model era -- roughly 2020 to 2025 -- is over. The forces that defined it have inverted. Open source models have reached frontier performance while inference costs approach zero, exposing what was always structurally true: pre-training large language models at scale is not a durable competitive moat. The US government's formal designation of Anthropic as a supply chain risk in February 2026 accelerated a transition already underway -- but did not cause it. The paper argues that the AI industry is restructuring simultaneously along four axes: economic, as the circular financing structure that inflated foundation model valuations collapses; technical, as the pre-training scaling paradigm gives way to post-training optimization and agentic composition; commercial, as application-layer integrators displace the foundation model companies whose commodity they now consume; and political, as the government asserts its historic role as gatekeeper of strategic technology. These are not separate disruptions. They are one structural shift, arriving together. The paper further argues that open-weight models are the counterintuitive instrument of sovereign control: a government that holds the weights commands the capability on its own terms, without dependence on vendor policy, financial continuity, or personnel clearance.
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