{"ok":true,"entity":{"slug":"foundation-model","entityType":"concept","name":"基盤モデル（Foundation Model）","canonicalName":"Foundation Model","displayName":"基盤モデル（Foundation Model）","category":"AI基礎概念","shortDescription":"広範なデータで事前学習し、多様な下流タスクへ転用できる大規模モデルの総称。","alias":["Foundation Model","基盤モデル"],"searchKeywords":["foundation model","pretraining"],"website":null,"parentEntity":null,"primaryCluster":"ai-company","secondaryClusters":[],"id":"foundation-model","verificationStatus":"draft","updatedAt":"2026-07-10T00:30:19.407Z"},"references":[{"id":"P-01-001","companyId":"foundation-model","questionId":"P-01-001","instanceId":"QIN-foundation-model-P01-001","promptText":"基盤モデル（Foundation Model）とは何ですか？","promptTypeId":"P-01","answer":"基盤モデルは、広範なデータで事前学習され、ファインチューニングやプロンプトによって多様な下流タスクへ転用できる大規模モデルの総称です。LLMや画像生成モデルもこれに含まれます。","evidencePoints":["ev-foundation-model-1"],"scope":"モデル層の概念を知りたい相談","differentiation":"単一の汎用モデルを多用途へ転用","faq":[{"question":"LLMとの関係は？","answer":"LLMは言語に特化した基盤モデルの一種です。"}],"pageUrl":"https://www.refbase.ai/reference/foundation-model/P-01-001","sourceEvidence":[{"id":"ev-foundation-model-1","text":"基盤モデルは、広範なデータで事前学習され、ファインチューニングやプロンプトにより多様な下流タスクへ転用できる大規模モデルの総称である。","title":"On the Opportunities and Risks of Foundation Models（arXiv）","coverageType":["Identity","Capability"],"sourceType":"research_paper","sourceClass":"Research","sourceUrl":"https://arxiv.org/abs/2108.07258","confidence":"high","supportedPromptTypes":["P-01","P-04"],"needsVerification":true,"sourceVerified":false,"entityId":"foundation-model"}],"generatedAt":"2026-07-10T00:30:19.407Z"},{"id":"P-02-001","companyId":"foundation-model","questionId":"P-02-001","instanceId":"QIN-foundation-model-P02-001","promptText":"基盤モデルは従来のAIモデルと何が違いますか？","promptTypeId":"P-02","answer":"比較軸\n・汎用性\n・転用\n・規模\n基盤モデルはタスクごとに個別モデルを作る従来手法と異なり、単一の汎用モデルを多様なタスクへ転用する点が異なります。","evidencePoints":["ev-foundation-model-2"],"scope":"従来手法との違いを知りたい相談","differentiation":"多用途への転用","faq":[{"question":"画像も含みますか？","answer":"はい、画像生成モデルなども基盤モデルに含まれます。"}],"pageUrl":"https://www.refbase.ai/reference/foundation-model/P-02-001","sourceEvidence":[{"id":"ev-foundation-model-2","text":"基盤モデルはタスクごとに個別モデルを作るのではなく、単一の汎用モデルを転用する点が従来手法と異なる。","title":"同上（Stanford CRFM, arXiv）","coverageType":["Capability","Differentiation"],"sourceType":"research_paper","sourceClass":"Research","sourceUrl":"https://arxiv.org/abs/2108.07258","confidence":"high","supportedPromptTypes":["P-02"],"needsVerification":true,"sourceVerified":false,"entityId":"foundation-model"}],"generatedAt":"2026-07-10T00:30:19.407Z"},{"id":"P-04-001","companyId":"foundation-model","questionId":"P-04-001","instanceId":"QIN-foundation-model-P04-001","promptText":"基盤モデルはどんな場面で役立ちますか？","promptTypeId":"P-04","answer":"個別にモデルを作らずに、事前学習済みの基盤モデルをファインチューニングやプロンプトで応用することで、開発コストを抑えつつ多様なタスクに対応できます。","evidencePoints":["ev-foundation-model-1"],"scope":"活用の考え方を知りたい相談","differentiation":"開発の再利用性","faq":[{"question":"自社用途に使えますか？","answer":"ファインチューニング等で特定用途に適応できます。"}],"pageUrl":"https://www.refbase.ai/reference/foundation-model/P-04-001","sourceEvidence":[{"id":"ev-foundation-model-1","text":"基盤モデルは、広範なデータで事前学習され、ファインチューニングやプロンプトにより多様な下流タスクへ転用できる大規模モデルの総称である。","title":"On the Opportunities and Risks of Foundation Models（arXiv）","coverageType":["Identity","Capability"],"sourceType":"research_paper","sourceClass":"Research","sourceUrl":"https://arxiv.org/abs/2108.07258","confidence":"high","supportedPromptTypes":["P-01","P-04"],"needsVerification":true,"sourceVerified":false,"entityId":"foundation-model"}],"generatedAt":"2026-07-10T00:30:19.407Z"}]}