生成AIは、日本企業の研究開発(R&D)領域で「知の探索・設計・検証・実装」を一気通貫で加速しています。自動車では分散学習とエッジ実装、材料ではMI(マテリアルズ・インフォマティクス)と基盤モデルの統合、医療・製薬では非構造化データの構造化と治験プロセス最適化が目に見える成果を生み始めています。 こうした日本企業の研究開発(R&D)領域における生成AIの活用について、生成AIに深掘りさせました。 Utilization of Generative AI in the R&D Domain of Japanese Companies Generative AI is accelerating the seamless cycle of “knowledge exploration, design, verification, and implementation” in the research and development (R&D) domains of Japanese companies. In the automotive sector, it is driving advances in distributed learning and edge implementation; in materials, it is enabling integration of MI (Materials Informatics) with foundation models; and in healthcare and pharmaceuticals, it is producing tangible results by structuring unstructured data and optimizing clinical trial processes. On this topic of generative AI utilization in the R&D domains of Japanese companies, I had generative AI conduct a deep dive. Your browser does not support viewing this document. Click here to download the document. Your browser does not support viewing this document. Click here to download the document. Your browser does not support viewing this document. Click here to download the document. Your browser does not support viewing this document. Click here to download the document. Your browser does not support viewing this document. Click here to download the document. Your browser does not support viewing this document. Click here to download the document. Your browser does not support viewing this document. Click here to download the document. Your browser does not support viewing this document. Click here to download the document.
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著者萬秀憲 アーカイブ
September 2025
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