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He brings strong domain expertise across Automation & Robotics, Energy & Smart Infrastructure, Healthcare, as well as Gaming & Signage, with a focus on translating complex technologies into clear customer value and driving market adoption.\u003C\u002Fp>","Stefan Zieboll",{"url":58,"focus":35,"srcset":59,"width":60,"height":61,"ai-generated":13,"alt":35,"title":35},"https:\u002F\u002Fwww.swissbit.com\u002Fmedia\u002Fusers\u002FEy1uZbqD\u002Fe943fbb2db-1784879216\u002Fprofile.jpg?_=9216","https:\u002F\u002Fwww.swissbit.com\u002Fmedia\u002Fusers\u002FEy1uZbqD\u002Fe943fbb2db-1784879216\u002Fprofile-112x112-crop-q85-sharpen25.webp?_=9216 112w, https:\u002F\u002Fwww.swissbit.com\u002Fmedia\u002Fusers\u002FEy1uZbqD\u002Fe943fbb2db-1784879216\u002Fprofile-224x224-crop-q85-sharpen10.webp?_=9216 224w, https:\u002F\u002Fwww.swissbit.com\u002Fmedia\u002Fusers\u002FEy1uZbqD\u002Fe943fbb2db-1784879216\u002Fprofile-600x600-crop-q85.webp?_=9216 600w",5000,3327,[63,68,74,78,86,90,94,102,106,110,114,118,122,126,130,134,157,161,165,178,182,186],{"content":64,"id":66,"isHidden":13,"type":67},{"text":65},"\u003Cp>人工知能は、集中型データセンターの枠を超えて「エッジ」へと広がり、\u003Ca href=\"https:\u002F\u002Fwww.swissbit.com\u002Fja\u002Findustries\u002Fmanufacturing-automation\" title=\"AI is moving into factories\">工場、機械、ロボット\u003C\u002Fa>、自動運転車、産業用機器などに導入されつつあります。\u003C\u002Fp>\u003Cp>エッジAIについては、プロセッサ、アクセラレータ、高度なLLMモデルといった観点から議論されることが多い。しかし、産業分野での成功は、単に演算性能だけにかかっているわけではない。プラットフォーム全体が、長い製品ライフサイクルを通じて、信頼性が高く、安全で、予測可能な動作をしなければならない。したがって、ストレージはアーキテクチャの戦略的な要素であり、開発の最終段階で選定する単なるコンポーネントではない。\u003C\u002Fp>","d1088e04-e8e9-4b49-8511-64a63190b58f","textWithFormats",{"content":69,"id":72,"isHidden":13,"type":73},{"level":70,"text":71},"h2","\u003Cstrong>産業用AIがエッジへ移行している理由\u003C\u002Fstrong>","d17992bf-11bd-4368-95dc-66514d2c7f22","heading",{"content":75,"id":77,"isHidden":13,"type":67},{"text":76},"\u003Cp>クラウドAIは膨大な演算能力と拡張性を提供しますが、多くの産業用アプリケーションでは、リモートインフラに完全に依存することはできません。\u003C\u002Fp>\u003Cp>ロボティクス、マシンビジョン、品質検査、自律移動ロボット、機械制御などでは、ミリ秒単位での意思決定が求められる場合があります。データをクラウドに送信して応答を待つことは、許容できないほどの遅延を招く恐れがあります。また、システムは、ネットワーク障害時や、信頼性の高い高帯域幅の接続環境が整っていない場所でも、稼働を継続できなければなりません。\u003C\u002Fp>\u003Cp>ローカル処理により、企業は画像、プロセスパラメータ、品質記録、独自のAIモデルなど、機密性の高い生産データをより厳格に管理できます。これらの情報を機械や工場内に留めておくことで、情報漏洩のリスクを低減し、データガバナンスを簡素化できます。\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.swissbit.com\u002Fja\u002Findustries\u002Fai-infrastructure\" title=\"Swissbit SSDs are designed for edge AI Infrastructure\">エッジAIは\u003C\u002Fa>、より迅速な応答、より高い自律性、より強固なデータ管理、そしてクラウド帯域幅への依存度の低減を実現します。その結果、生産性の向上、コストの予測可能性の向上、外部への依存度の低減が期待できます。\u003C\u002Fp>","406ae577-3142-4d35-bbdb-2af5abb21e37",{"content":79,"id":84,"isHidden":13,"type":85},{"text":80,"citation":81,"img":35},"コンピューティングは推論を実行しますが、ストレージは、産業用AIの価値を支える知識、エビデンス、そして継続性を維持します。",{"name":82,"subtitle":83},"ステファン・ツィーボル","メモリ製品マーケティングマネージャー ","67cebb22-483e-4dd1-976f-031dd22e7c75","quote",{"content":87,"id":89,"isHidden":13,"type":73},{"level":70,"text":88},"\u003Cstrong>言語モデルから知能を持つ機械へ\u003C\u002Fstrong>","991b25b8-f805-46f1-ba34-15c4b9efc119",{"content":91,"id":93,"isHidden":13,"type":67},{"text":92},"\u003Cp>エッジにおけるAIの機能は急速に進歩しています。大規模言語モデルはテキストを理解・生成し、ビジョン・言語モデルは視覚的な解釈機能を追加することで、システムが物体を識別し、状況を評価し、文脈を提供することを可能にしています。\u003C\u002Fp>\u003Cp>さらに、ビジョン・言語・アクション（VLA）モデルは、知覚と理解を物理的な動作と結びつけることで、その機能をさらに拡張しています。VLA機能を備えたロボットは、物体を識別してその情報を別のコントローラーに渡すのではなく、状況を解釈し、適切な対応を決定することができます。\u003C\u002Fp>\u003Cp>AIが状況の認識から運用上の意思決定へと移行するにつれ、プラットフォームの信頼性が極めて重要になります。インテリジェントマシンは、モデル、設定、更新、ログ、および運用データを安全に保持しなければなりません。\u003C\u002Fp>","76f922b4-9ffd-40dd-b879-48ab86250a60",{"content":95,"id":100,"isHidden":13,"type":101},{"location":96,"image":35,"alt":97,"caption":98,"link":99,"ratio":99,"crop":13},"kirby","産業用ロボットにおける「視覚・言語・動作」モデル。信頼性の高いエッジAIインフラを活用し、ロボットが赤いコンテナを認識・理解し、移動させる様子を示しています。","「視覚・言語・行動」モデルは、産業用エッジ環境において視覚情報を物理的な行動へと変換します。そのため、AIモデル、更新データ、ログ、および業務の継続性を確保するためには、信頼性が高く安全な産業用ストレージが不可欠となります。","","1e65cb2e-c570-45d5-b8c0-ddb4d09f3231","image",{"content":103,"id":105,"isHidden":13,"type":73},{"level":70,"text":104},"\u003Cstrong>エッジAIのメモリとしての産業用SSD\u003C\u002Fstrong>","9a25f7d4-958b-4442-b1d3-d989981a71b2",{"content":107,"id":109,"isHidden":13,"type":67},{"text":108},"\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.swissbit.com\u002Fja\u002Fproducts\u002Fflash-storage\u002Fpcie-m-2-2280-ssd\" title=\"Industrial grade SSDs\">産業用SSDは\u003C\u002Fa>、エッジAIシステムの永続メモリとして機能します。これには、オペレーティングシステム、アプリケーション、AIモデル、設定、センサーデータ、推論結果、診断ログ、およびトレーサビリティ記録が保存されます。\u003C\u002Fp>\u003Cp>多くのアプリケーションは継続的にデータを書き込みます。ビジョンシステムは1シフトあたり数千枚の画像を処理し、予知保全プラットフォームは24時間体制でセンサーデータを収集し、自律型ロボットはナビゲーション情報や稼働情報を記録します。こうしたワークロードは、ストレージに持続的な負荷をかけます。\u003C\u002Fp>\u003Cp>障害が発生すると、モデルの読み込みができなくなったり、データが破損したり、生産が中断されたり、高額な修理費用が発生したりする可能性があります。したがって、ストレージは、主に容量や価格だけで選ばれる汎用製品ではなく、不可欠な運用インフラとして扱われるべきです。\u003C\u002Fp>","b6fe5d69-b5a8-4368-8ff5-c03ec96f3331",{"content":111,"id":113,"isHidden":13,"type":73},{"level":70,"text":112},"\u003Cstrong>最高の性能は、産業用レベルの信頼性とは異なる\u003C\u002Fstrong>","64803f3f-3e23-41b8-9a33-9b823c706197",{"content":115,"id":117,"isHidden":13,"type":67},{"text":116},"\u003Cp>注目される\u003Ca href=\"https:\u002F\u002Fwww.swissbit.com\u002Fen\u002Fnews\u002Fblog\u002Fwhy-a-fast-ssd-can-still-be-the-wrong-ssd\" title=\"Why a fast SSD can still be the wrong SSD\">ベンチマーク結果\u003C\u002Fa>だけでは、産業用エッジAIに最適なストレージ製品を必ずしも特定できるわけではありません。より重要な考慮事項としては、耐用期間中の書き込み量、連続稼働、動作温度範囲、振動・衝撃、予期せぬ停電、ヘルスモニタリング、部品の入手可能性、およびモデルや生産データの保護などが挙げられます。\u003C\u002Fp>\u003Cp>堅牢な産業用SSDには、高い耐久性、高度なエラー訂正機能、停電保護機能、セキュアなファームウェア、ヘルスモニタリング、および広範囲の温度対応が求められる場合があります。\u003C\u002Fp>\u003Cp>ファームウェアおよび部品表（BOM）の管理も重要です。産業用プラットフォームは、製造ラインで数年稼働し続け、現場ではさらに長期間運用される場合があります。管理されていない部品変更は、認定上の問題、ソフトウェアの非互換性、およびシステム動作の不整合を引き起こす可能性があります。OEMや機械メーカーにとって、一貫性は速度と同様に重要な要素となり得ます。\u003C\u002Fp>","8256e25d-f001-43cc-a49c-17b7d3f70cf2",{"content":119,"id":121,"isHidden":13,"type":73},{"level":70,"text":120},"\u003Cstrong>「コンピュート」と「ストレージ」を統合システムとして選択する\u003C\u002Fstrong>","dc2d1db4-560b-47a3-a078-c32c168d1497",{"content":123,"id":125,"isHidden":13,"type":67},{"text":124},"\u003Cp>エッジAIプラットフォームでは、NVIDIA、Intel、AMD、Qualcomm、Hailo、NXPなどのベンダーが提供するCPU、GPU、または専用のNPUが使用される場合があります。各アーキテクチャには、推論性能、エネルギー効率、ソフトウェア互換性、コンパクトな統合性、組み込みライフサイクルサポートなど、それぞれ異なる強みがあります。\u003C\u002Fp>\u003Cp>プロセッサの選定にあたっては、ワークロード、消費電力の制約、環境、コスト目標、およびソフトウェアエコシステムを考慮する必要があります。しかし、アクセラレータだけを評価すると、バランスの取れていない設計になってしまう可能性があります。\u003C\u002Fp>\u003Cp>ストレージは、モデルの読み込み速度、更新の信頼性、データ保持、および停電や環境事象発生時の耐障害性に影響を与えます。重要な点は、単にどのプロセッサが最高のパフォーマンスを発揮するかということではなく、システム全体の運用期間を通じて、演算、ストレージ、ソフトウェア、セキュリティ、ライフサイクルサポートのどの組み合わせが確実に機能するかということです。\u003C\u002Fp>","59748bca-712f-4f85-b9d6-14e2ad84fd9d",{"content":127,"id":129,"isHidden":13,"type":73},{"level":70,"text":128},"\u003Cstrong>エッジAIに最初からストレージ機能を組み込む\u003C\u002Fstrong>","7f63268d-d9db-4da8-b83f-04aa7d2d8a81",{"content":131,"id":133,"isHidden":13,"type":67},{"text":132},"\u003Cp>ストレージに関する決定を先送りすると、特にODMやOEMプロジェクトにおいて、不必要なリスクが生じる可能性があります。耐久性、容量、セキュリティ、動作温度範囲、インターフェース、フォームファクタは早期に定義しておくべきであり、理想的には、エッジAI PCの仕様書において具体的なSSDのタイプやモデルを明記しておくことが望ましいです。\u003C\u002Fp>\u003Cp>容量計画では、初期のオペレーティングシステムやモデルだけでなく、将来のモデルバージョン、ソフトウェアアップデート、診断データ、ログ、および保持される生産データも考慮に入れる必要があります。\u003C\u002Fp>\u003Cp>物理的な設計も重要です。着脱可能なM\u003Ca href=\"https:\u002F\u002Fwww.swissbit.com\u002Fja\u002Fproducts\u002Fflash-storage\u002Fpcie-m-2-2280-ssd\" title=\"PCIe M.2 SSDs\">.2 SSDは\u003C\u002Fa>メンテナンスやアップグレードを簡素化できますが、はんだ付けされたBGAストレージは、コンパクトで堅牢、かつ耐振動性に優れたシステムを実現します。早期の計画は、認定の遅延、再設計、および調達上の問題を未然に防ぐのに役立ちます。\u003C\u002Fp>","797ed5ed-b7c9-4512-ac77-b4ba1840680d",{"content":135,"id":155,"isHidden":13,"type":156},{"anchor-name":99,"anchor-id":99,"title":99,"alignment":136,"background-type":137,"blocks":138},"center","white",[139],{"content":140,"id":153,"isHidden":13,"type":154},{"format":141,"subtitle":142,"title":143,"text":144,"text-size":145,"cta":146,"images":151,"images-ratio":152},"textLeft","産業用エッジシステム向けに設計","インテリジェントメモリのための信頼性の高いストレージ 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Automation\">機器は\u003C\u002Fa>10年以上稼働し続ける可能性があり、OEMやシステムインテグレーターは、複数の世代や拠点にわたって同じプラットフォームをサポートすることになります。\u003C\u002Fp>\u003Cp>長期的な供給保証、予測可能な動作、管理された変更、そして透明性の高い状態情報は、総所有コスト（TCO）に直接影響を与えます。産業用ストレージプラットフォームを標準化することで、検証、調達、保守、現場サポートを簡素化できるだけでなく、本来同一であるはずのシステム間の差異を低減することができます。\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.swissbit.com\u002Fja\u002Fproducts\u002Fflash-storage\u002Fpcie-m-2-ssd\">Swissbitの産業用SSDは\u003C\u002Fa>、耐久性、データの整合性、ライフサイクル管理、および長期的な可用性が不可欠な組み込み環境や産業環境向けに設計されています。M.2およびコンパクト\u003Ca href=\"https:\u002F\u002Fwww.swissbit.com\u002Fja\u002Fproducts\u002Fflash-storage\u002Fm-2-pcie-bga\" title=\"Swissbit PCIe M.2 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href=\"https:\u002F\u002Fwww.swissbit.com\u002Fja\u002Fcompany\u002Fwhy-swissbit\" title=\"Why Swissbit for Infrastructure Reliability\">インフラの信頼性は\u003C\u002Fa>ますます重要になってきています。\u003C\u002Fp>\u003Cp>最も成功するシステムは、必ずしも最も高性能なプロセッサや最大規模のモデルを採用するとは限りません。そうしたシステムは、知能と、予測可能な動作、安全なデータ処理、管理可能なライフサイクルコスト、そして実際の産業環境における耐障害性を兼ね備えているでしょう。\u003C\u002Fp>\u003Cp>推論処理はコンピューティングが行いますが、産業用AIの価値を支える知識、エビデンス、継続性を維持するのはストレージです。次世代のインテリジェントマシンにおいて、SSDは\u003Ca href=\"https:\u002F\u002Fwww.swissbit.com\u002Fja\u002Findustries\u002Fai-infrastructure\" title=\"AI Strategy 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