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「国産LLM(大規模言語モデル)」の採用状況

1/3/2026

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昨今の地政学的リスクを考慮すると、他国の単一のAIベンダー(特に米国の特定のフロンティアモデル)へ過度に依存する構造は、企業経営における致命傷となりかねません。
複数のAIモデルを透過的に切り替えられるAPIゲートウェイや中間抽象化レイヤーの設計などのマルチベンダー戦略や、データの主権とアルゴリズムの完全な制御権を確保するため国内のデータセンターで稼働する「国産LLM(大規模言語モデル)」の採用、クローズドな環境で機密データを処理できるソブリンクラウド(自国主権型クラウド)の構築が求められています。
生成AIに、「国産LLM」の採用状況を調べさせました。さらに、結果をNotebookLMでインフォグラフィック、スライド資料にさせました。
なお、生成AIによる調査・分析結果は、公開された情報からだけの分析であり、必ずしも実情を示したものではないこと、誤った情報も含まれていることについてはご留意されたうえで、ご参照ください。

Adoption Status of “Domestic LLMs (Large Language Models)”
In light of growing geopolitical risks, an overreliance on a single foreign AI vendor—particularly specific U.S. frontier models—could pose a potentially fatal vulnerability to corporate management.
There is an increasing need for multi-vendor strategies, such as designing API gateways and intermediate abstraction layers that enable seamless switching between multiple AI models. At the same time, organizations are being urged to adopt “domestic LLMs (Large Language Models)” operated within domestic data centers to ensure data sovereignty and full control over algorithms. The construction of sovereign clouds—nationally controlled cloud environments capable of processing sensitive data within closed systems—is also becoming essential.
I asked generative AI to investigate the current adoption status of domestic LLMs. Furthermore, the results were transformed into infographics and slide materials using NotebookLM.
Please note that the research and analysis generated by AI are based solely on publicly available information. They do not necessarily reflect the full reality of the situation and may contain inaccuracies. Kindly keep this in mind when reviewing the materials.


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    著者

    萬秀憲

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