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          英偉達對OpenAI千億美元投資引發“循環交易”質疑

          Jeremy Kahn
          2025-10-12

          當前的人工智能熱潮,有多少只是英偉達資金的循環利用?

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          英偉達(Nvidia)首席執行官黃仁勛(Jensen Huang)。他對客戶的投資為英偉達人工智能芯片市場培育了土壤。然而,這種“循環”性質開始引發部分分析師擔憂。圖片來源:Quan Yajun—VCG via Getty Images

          英偉達本周早些時候宣布,將向OpenAI投資1000億美元,以支持其大規模數據中心建設,此舉加劇了投資者對人工智能領域潛藏危險金融泡沫的擔憂。該領域上市公司和私營公司估值所依據的營收與盈利計算存在邏輯矛盾。

          盡管英偉達此次投資規模空前,但這家人工智能芯片制造商已進行一系列“循環交易”——向自身客戶注資或提供貸款。各行業都在一定程度上存在供應商融資,但此類循環交易可能使投資者對人工智能的真實需求產生虛高預期。

          在以往科技泡沫中,營收“迂回投資”和科技公司為自身客戶融資的做法,在泡沫最終破裂時都加劇了損害。盡管此類融資目前對英偉達營收的貢獻比例看似有限,但該公司作為全球最具價值上市公司的主導地位意味著其股票已被“精準定價”,任何微小失誤都可能對其估值產生遠超常規的沖擊,進而波及金融市場乃至更廣泛的經濟領域。

          整個人工智能熱潮在多大程度上是由英偉達的資金支撐的,這一問題的答案難以明晰,這也正是其令人不安之處。該公司已達成多項投資和融資交易,其中許多交易單筆金額過小,不足以被視為“重大交易”,無需在財務文件中披露,但這些交易累積起來可能產生深遠影響。

          此外,存在諸多相互關聯的循環環節——英偉達投資了一家公司,如OpenAI,而OpenAI又從某云服務商采購服務,該云服務商恰是英偉達的投資對象,然后該云服務提供商又從英偉達購買或租賃圖形處理器(GPU)——要理清資金流向絕非易事。

          錯綜復雜的投資網絡

          在英偉達構建的迂回投資網絡里,最為引人注目的兩個范例當屬OpenAI與Coreweave。除最新注資外,英偉達早在2024年10月就參與了這家快速成長的人工智能公司高達66億美元的融資輪。英偉達還投資了Coreweave,后者為OpenAI提供數據中心算力支持,同時也是英偉達的客戶。截至6月底,英偉達持有Coreweave約7%的股份,目前價值約為30億美元。

          企業從英偉達投資中獲得的收益遠不止資金本身。英偉達在OpenAI和Coreweave等公司持有股權,使這些企業能夠以遠低于市場利率的條件獲得數據中心項目債務融資,而若沒有英偉達的支持,它們無法獲得如此優惠利率的融資機會。Seaport Global Securities分析師杰伊·戈德堡(Jay Goldberg)將此類交易比作有人請父母共同簽署抵押貸款合同,這能讓貸款方確信資金能順利收回。

          為數據中心融資的初創公司通常只能接受高達15%的借款利率,而像微軟這樣的大型成熟公司可能只需支付6%到9%的利率。在英偉達的支持下,OpenAI和Coreweave的融資利率已接近微軟或谷歌享有的水平。

          英偉達還簽署了一項63億美元的協議,旨在購買Coreweave無法售予他方的云計算資源。此前該芯片制造商已同意在四年內斥資13億美元采購Coreweave的云服務。與此同時,Coreweave迄今為止已采購至少25萬塊英偉達圖形處理器——據稱其中多數為單價約3萬美元的H100 Hopper型號——這意味著Coreweave購買英偉達芯片的支出約達75億美元。從本質上講,英偉達對Coreweave的所有投資均以營收形式實現回流。

          英偉達還與其他所謂“新云”公司達成了類似的云計算交易。據《The Information》報道,今年夏天英偉達同意在四年內斥資13億美元,從Lambda租用約1萬塊自家生產的人工智能芯片——Lambda與Coreweave一樣,都運營著數據中心。此外,雙方還簽署了另一份價值2億美元的協議,將在未指明的時間段內租用約8000塊芯片。

          對于那些篤定人工智能存在泡沫的人而言,Lambda的交易顯然是泡沫存在的有力佐證。Lambda租用英偉達芯片,然后將使用時間轉租給英偉達?它以圖形處理器本身價值作為抵押獲取借款,進而購置這些芯片。

          除對OpenAI和Coreweave進行大額投資外,這家人工智能芯片制造商還在多家上市企業中持有數百萬美元股份,這些公司要么采購其圖形處理器,要么從事相關芯片技術研發。其中包括芯片設計公司Arm、高性能計算企業Applied Digital、云服務公司Nebius Group以及生物技術公司Recursion Pharmaceuticals。(英偉達近期還斥資50億美元收購了英特爾4%的股份。與Arm類似,英特爾生產的芯片在某些場景下可替代英偉達的圖形處理器,但多數情況下與之形成互補。)

          本月早些時候,英偉達還承諾向英國人工智能初創企業投入20億英鎊(約合27億美元),其中至少5億英鎊將投向英國數據中心運營商Nscale。該企業預計將動用部分資金采購英偉達的圖形處理器,用于其正在建設的數據中心。英偉達還表示將通過直接投資以及借助當地風投機構,對多家英國初創企業進行投資,其中部分資金可能以計算資源采購形式回流至OpenAI——無論是直接采購還是通過云服務商間接采購,這些服務商最終都需購買英偉達的圖形處理器。

          據Dealroom與《金融時報》數據顯示,2024年英偉達通過直接投資或旗下企業風險投資部門NVentures,向全球人工智能初創企業投入約10億美元。這一數額較2022年顯著增長——當年OpenAI推出ChatGPT掀起生成式人工智能熱潮。

          這筆資金最終會有多少以銷售形式回流至英偉達?同樣難以精確測算。華爾街研究機構NewStreet Research估算,英偉達每向OpenAI投入100億美元,便能收獲價值350億美元的圖形處理器采購或租賃收入,相當于其上一財年年度收入的27%。

          互聯網泡沫時代的回聲

          如此回報率無疑使客戶融資極具吸引力,但這確實引發了分析師對人工智能估值泡沫的擔憂。此類循環交易是以往科技泡沫的典型特征,往往最終對投資者造成反噬。

          此次英偉達與OpenAI達成的租賃協議(作為其最新投資的一部分)可能暗藏隱患。通過向OpenAI租賃而非要求其直接購買芯片,使得OpenAI無需為芯片的高折舊率承擔會計費用,這最終將改善其利潤表現。但這意味著英偉達必須獨自承擔折舊成本。此外,若人工智能工作負載需求與英偉達首席執行官黃仁勛的樂觀預期不符,該公司還將面臨圖形處理器庫存積壓風險——屆時這些芯片將無人問津。

          在部分市場觀察者看來,英偉達的最新交易與過往科技繁榮時期的過度行為如出一轍。21世紀初互聯網泡沫時期,北電網絡(Nortel)、朗訊(Lucent)和思科(Cisco)等電信設備制造商曾向初創企業和電信公司提供貸款以購買其設備。就在2001年泡沫破裂前夕,思科和北電網絡向客戶提供的融資額已超過其年收入的10%,而五大電信設備制造商的融資總額超過其總收益的123%。

          最終,鋪設的光纖電纜和安裝的交換設備數量遠超市場實際需求。當泡沫破裂導致眾多客戶破產時,電信設備制造商的資產負債表上便背負了壞賬。當泡沫破裂時,這種情況導致資產價值縮水幅度遠超正常情況下可能出現的水平,在隨后的十年間,網絡設備企業的市值蒸發了逾90%。

          更糟糕的是像光纖巨頭環球電訊(Global Crossing)這樣直接進行“營收迂回投資”的公司。為達成營收預期,這些公司常在季度末通過向其他公司支付服務費,再由對方回購等值設備的方式完成交易。當泡沫破裂時,環球電訊破產了,其高管最終因營收迂回投資問題支付巨額和解金。

          正是對這類交易的記憶,讓分析師們至少對英偉達的部分循環投資心存疑慮。Seaport Global分析師戈德堡表示,這些交易帶有循環融資印記,堪稱“泡沫式行為”的典型范例。

          “此舉顯然會加劇人們對‘循環’問題的擔憂。”伯恩斯坦研究公司(Bernstein Research)分析師斯泰西·拉斯貢(Stacy Rasgon)在英偉達宣布對OpenAI進行巨額投資后,在一份投資者報告中寫道。誠然,從心懷擔憂到陷入危機尚有漫長的距離,但隨著人工智能公司估值持續攀升,這段距離正在逐漸縮短。(財富中文網)

          譯者:中慧言-王芳

          英偉達本周早些時候宣布,將向OpenAI投資1000億美元,以支持其大規模數據中心建設,此舉加劇了投資者對人工智能領域潛藏危險金融泡沫的擔憂。該領域上市公司和私營公司估值所依據的營收與盈利計算存在邏輯矛盾。

          盡管英偉達此次投資規模空前,但這家人工智能芯片制造商已進行一系列“循環交易”——向自身客戶注資或提供貸款。各行業都在一定程度上存在供應商融資,但此類循環交易可能使投資者對人工智能的真實需求產生虛高預期。

          在以往科技泡沫中,營收“迂回投資”和科技公司為自身客戶融資的做法,在泡沫最終破裂時都加劇了損害。盡管此類融資目前對英偉達營收的貢獻比例看似有限,但該公司作為全球最具價值上市公司的主導地位意味著其股票已被“精準定價”,任何微小失誤都可能對其估值產生遠超常規的沖擊,進而波及金融市場乃至更廣泛的經濟領域。

          整個人工智能熱潮在多大程度上是由英偉達的資金支撐的,這一問題的答案難以明晰,這也正是其令人不安之處。該公司已達成多項投資和融資交易,其中許多交易單筆金額過小,不足以被視為“重大交易”,無需在財務文件中披露,但這些交易累積起來可能產生深遠影響。

          此外,存在諸多相互關聯的循環環節——英偉達投資了一家公司,如OpenAI,而OpenAI又從某云服務商采購服務,該云服務商恰是英偉達的投資對象,然后該云服務提供商又從英偉達購買或租賃圖形處理器(GPU)——要理清資金流向絕非易事。

          錯綜復雜的投資網絡

          在英偉達構建的迂回投資網絡里,最為引人注目的兩個范例當屬OpenAI與Coreweave。除最新注資外,英偉達早在2024年10月就參與了這家快速成長的人工智能公司高達66億美元的融資輪。英偉達還投資了Coreweave,后者為OpenAI提供數據中心算力支持,同時也是英偉達的客戶。截至6月底,英偉達持有Coreweave約7%的股份,目前價值約為30億美元。

          企業從英偉達投資中獲得的收益遠不止資金本身。英偉達在OpenAI和Coreweave等公司持有股權,使這些企業能夠以遠低于市場利率的條件獲得數據中心項目債務融資,而若沒有英偉達的支持,它們無法獲得如此優惠利率的融資機會。Seaport Global Securities分析師杰伊·戈德堡(Jay Goldberg)將此類交易比作有人請父母共同簽署抵押貸款合同,這能讓貸款方確信資金能順利收回。

          為數據中心融資的初創公司通常只能接受高達15%的借款利率,而像微軟這樣的大型成熟公司可能只需支付6%到9%的利率。在英偉達的支持下,OpenAI和Coreweave的融資利率已接近微軟或谷歌享有的水平。

          英偉達還簽署了一項63億美元的協議,旨在購買Coreweave無法售予他方的云計算資源。此前該芯片制造商已同意在四年內斥資13億美元采購Coreweave的云服務。與此同時,Coreweave迄今為止已采購至少25萬塊英偉達圖形處理器——據稱其中多數為單價約3萬美元的H100 Hopper型號——這意味著Coreweave購買英偉達芯片的支出約達75億美元。從本質上講,英偉達對Coreweave的所有投資均以營收形式實現回流。

          英偉達還與其他所謂“新云”公司達成了類似的云計算交易。據《The Information》報道,今年夏天英偉達同意在四年內斥資13億美元,從Lambda租用約1萬塊自家生產的人工智能芯片——Lambda與Coreweave一樣,都運營著數據中心。此外,雙方還簽署了另一份價值2億美元的協議,將在未指明的時間段內租用約8000塊芯片。

          對于那些篤定人工智能存在泡沫的人而言,Lambda的交易顯然是泡沫存在的有力佐證。Lambda租用英偉達芯片,然后將使用時間轉租給英偉達?它以圖形處理器本身價值作為抵押獲取借款,進而購置這些芯片。

          除對OpenAI和Coreweave進行大額投資外,這家人工智能芯片制造商還在多家上市企業中持有數百萬美元股份,這些公司要么采購其圖形處理器,要么從事相關芯片技術研發。其中包括芯片設計公司Arm、高性能計算企業Applied Digital、云服務公司Nebius Group以及生物技術公司Recursion Pharmaceuticals。(英偉達近期還斥資50億美元收購了英特爾4%的股份。與Arm類似,英特爾生產的芯片在某些場景下可替代英偉達的圖形處理器,但多數情況下與之形成互補。)

          本月早些時候,英偉達還承諾向英國人工智能初創企業投入20億英鎊(約合27億美元),其中至少5億英鎊將投向英國數據中心運營商Nscale。該企業預計將動用部分資金采購英偉達的圖形處理器,用于其正在建設的數據中心。英偉達還表示將通過直接投資以及借助當地風投機構,對多家英國初創企業進行投資,其中部分資金可能以計算資源采購形式回流至OpenAI——無論是直接采購還是通過云服務商間接采購,這些服務商最終都需購買英偉達的圖形處理器。

          據Dealroom與《金融時報》數據顯示,2024年英偉達通過直接投資或旗下企業風險投資部門NVentures,向全球人工智能初創企業投入約10億美元。這一數額較2022年顯著增長——當年OpenAI推出ChatGPT掀起生成式人工智能熱潮。

          這筆資金最終會有多少以銷售形式回流至英偉達?同樣難以精確測算。華爾街研究機構NewStreet Research估算,英偉達每向OpenAI投入100億美元,便能收獲價值350億美元的圖形處理器采購或租賃收入,相當于其上一財年年度收入的27%。

          互聯網泡沫時代的回聲

          如此回報率無疑使客戶融資極具吸引力,但這確實引發了分析師對人工智能估值泡沫的擔憂。此類循環交易是以往科技泡沫的典型特征,往往最終對投資者造成反噬。

          此次英偉達與OpenAI達成的租賃協議(作為其最新投資的一部分)可能暗藏隱患。通過向OpenAI租賃而非要求其直接購買芯片,使得OpenAI無需為芯片的高折舊率承擔會計費用,這最終將改善其利潤表現。但這意味著英偉達必須獨自承擔折舊成本。此外,若人工智能工作負載需求與英偉達首席執行官黃仁勛的樂觀預期不符,該公司還將面臨圖形處理器庫存積壓風險——屆時這些芯片將無人問津。

          在部分市場觀察者看來,英偉達的最新交易與過往科技繁榮時期的過度行為如出一轍。21世紀初互聯網泡沫時期,北電網絡(Nortel)、朗訊(Lucent)和思科(Cisco)等電信設備制造商曾向初創企業和電信公司提供貸款以購買其設備。就在2001年泡沫破裂前夕,思科和北電網絡向客戶提供的融資額已超過其年收入的10%,而五大電信設備制造商的融資總額超過其總收益的123%。

          最終,鋪設的光纖電纜和安裝的交換設備數量遠超市場實際需求。當泡沫破裂導致眾多客戶破產時,電信設備制造商的資產負債表上便背負了壞賬。當泡沫破裂時,這種情況導致資產價值縮水幅度遠超正常情況下可能出現的水平,在隨后的十年間,網絡設備企業的市值蒸發了逾90%。

          更糟糕的是像光纖巨頭環球電訊(Global Crossing)這樣直接進行“營收迂回投資”的公司。為達成營收預期,這些公司常在季度末通過向其他公司支付服務費,再由對方回購等值設備的方式完成交易。當泡沫破裂時,環球電訊破產了,其高管最終因營收迂回投資問題支付巨額和解金。

          正是對這類交易的記憶,讓分析師們至少對英偉達的部分循環投資心存疑慮。Seaport Global分析師戈德堡表示,這些交易帶有循環融資印記,堪稱“泡沫式行為”的典型范例。

          “此舉顯然會加劇人們對‘循環’問題的擔憂。”伯恩斯坦研究公司(Bernstein Research)分析師斯泰西·拉斯貢(Stacy Rasgon)在英偉達宣布對OpenAI進行巨額投資后,在一份投資者報告中寫道。誠然,從心懷擔憂到陷入危機尚有漫長的距離,但隨著人工智能公司估值持續攀升,這段距離正在逐漸縮短。(財富中文網)

          譯者:中慧言-王芳

          Nvidia’s announcement earlier this week that it is investing $100 billion into OpenAI to help fund its massive data center build out has added to a growing sense of unease among investors that there is a dangerous financial bubble around AI, and that the revenues and earnings math underpinning the valuations of both public and private companies in the sector just doesn’t add up.

          While Nvidia’s latest announcement is by far the largest example, the AI chipmaker has engaged in a series of “circular” deals in which it invests in, or lends money to, its own customers. Vendor financing exists to some degree in many industries, but in this case, circular transactions may give investors an inflated perception of the true demand for AI.

          In past technology bubbles, revenue “roundtripping” and tech companies financing their own customers have exacerbated the damage when those bubbles eventually popped. While the share of Nvidia’s revenues that are currently being driven by such financing appears to be relatively small, the company’s dominance as the world’s most valuable publicly-traded company means that its stock is “priced for perfection” and that even minor missteps could have outsized impact on its valuation—and on financial markets and perhaps even the wider economy.

          The extent to which the entire AI boom is backstopped by Nvidia’s cash isn’t easy to answer precisely, which is also one of the unsettling things about it. The company has struck a number of investment and financing deals, many of which are too small individually for the company to consider “material” and report in its financial filings, even though collectively they may be significant.

          In addition, there are so many interlocking rings of circularity—where Nvidia has invested in a company, such as OpenAI, that in turn purchases services from a cloud service provider that Nvidia has also invested in, which then also buys or leases GPUs from Nvidia—that disentangling what money is flowing where is far from easy.

          Tangled webs of investment

          Two of the most prominent examples of Nvidia’s web of circuitous investments are OpenAI and Coreweave. In addition to the latest investment in OpenAI, Nvidia had previously participated in a $6.6 billion investment round in the fast-growing AI company in October 2024. Nvidia also has invested in CoreWeave, which supplies data center capacity to OpenAI and is also an Nvidia customer. As of the end of June, Nvidia owned about 7% of Coreweave, a stake worth about $3 billion currently.

          The benefits that companies get from a Nvidia investment extend beyond the cash itself. Nvidia’s equity stakes in companies such as OpenAI and Coreweave enable these companies to access debt financing for data center projects at potentially significantly lower interest rates than they would be able to access without such backing. Jay Goldberg, an analyst with Seaport Global Securities, compares such deals to someone asking their parents to be a co-signer on their mortgage. It gives lenders some assurance that they may actually get their money back.

          Startups financing data centers have often had to borrow money at rates as high as 15%, compared to 6% to 9% that a large, established corporation such as Microsoft might have to pay. With Nvidia’s backing, OpenAI and Coreweave have been able to borrow at rates closer to what Microsoft or Google might pay.

          Nvidia has also signed a $6.3 billion deal to purchase any cloud capacity that CoreWeave can’t sell to others. The chipmaker had previously agreed to spend $1.3 billion over four years on cloud computing with CoreWeave. Coreweave, meanwhile, has purchased at least 250,000 Nvidia GPUs so far—the majority of which it says are H100 Hopper models, which cost about $30,000 each—which means Coreweave has spent about $7.5 billion buying these chips from Nvidia. So in essence, all of the money Nvidia has invested in Coreweave has come back to it in the form of revenue.

          Nvidia has struck similar cloud computing deals with other so-called “neo-cloud” companies. According to a story in The Information, Nvidia agreed this summer to spend $1.3 billion over four years renting some 10,000 of its own AI chips from Lambda, which like Coreweave runs data centers, as well as a separate $200 million deal to rent some 8,000 more over an unspecified time period.

          For those who believe there’s an AI bubble, the Lambda deal is clear evidence of froth. Those Nvidia chips Lambda is renting time on back to Nvidia? It bought them with borrowed money collateralized by the value of the GPUs themselves.

          Besides its large investments in OpenAI and Coreweave, AI chipmaker also holds multi-million dollar stakes in several other publicly-traded companies that either purchase its GPUs or work on related chip technology. These include chip design firm Arm, high-performance computing company Applied Digital, cloud services company Nebius Group, and biotech company Recursion Pharmaceuticals. (Nvidia also recently purchased a 4% stake in Intel for $5 billion. Like Arm, Intel makes chips that in some cases are alternatives to Nvidia’s GPUs, but which for the most part are complementary to them.)

          Earlier this month, Nvidia also pledged to invest £2 billion ($2.7 billion) in U.K. AI startups, including at least £500 million in Nscale, a U.K.-based data center operator that will, presumably, be using some of that money to purchase Nvidia GPUs to provision the data centers it is building. Nvidia also said it would invest in a number of British startups, both directly and through local venture capital firms, and some of that money too, will likely come back to OpenAI in the form of computing purchases, either directly, or through cloud service providers, who in turn will need to buy Nvidia GPUs.

          In 2024, Nvidia invested about $1 billion in AI startups globally either directly or through its corporate venture capital arm NVentures, according to data from Dealroom and The Financial Times. This amount was up significantly from what Nvidia invested in 2022, the year the generative AI boom kicked off with OpenAI’s debut of ChatGPT.

          How much of this money winds up coming right back to Nvidia in the form of sales is again, difficult to determine. Wall Street research firm NewStreet Research has estimated that for every $10 billion Nvidia invests in OpenAI, it will see $35 billion worth of GPU purchases or GPU lease payments, an amount equal to about 27% of its annual revenues last fiscal year.

          Echoes of the dotcom era

          That kind of return would certainly make this sort of customer financing worthwhile. But it does raise concerns among analysts about a bubble in AI valuations. These kinds of circular deals have been a hallmark of previous technology bubbles and have often come back to haunt investors.

          In this case, the lease arrangements that Nvidia is entering into with OpenAI as part of its latest investment could prove problematic. By leasing GPUs to OpenAI, rather than requiring them to buy the chips outright, Nvidia is sparing OpenAI from having to take an accounting charge for the high depreciation rates on the chips, which will ultimately help OpenAI’s bottom line. But it means that instead Nvidia will have to bear this depreciation costs. What’s more, Nvidia will also take on the risk of being stuck with an inventory of GPUs no one wants if demand for AI workloads don’t match Nvidia CEO Jensen Huang’s rosy predictions.

          To some market watchers, Nvidia’s latest deals feel all-too-similar to the excesses of past technology booms. During the dot com bubble at the turn of the 21st Century, telecom equipment makers such as Nortel, Lucent, and Cisco lent money to startups and telecom companies to purchase their equipment. Just before the bubble burst in 2001, the amount of financing Cisco and Nortel had extended to their customers exceeded 10% of annual revenues, and the amount of financing the top five telecom equipment makers had provided to customers exceeded 123% of their combined earnings.

          Ultimately, the amount of fiber-optic cabling and switching equipment installed far exceeded demand, and when the bubble burst and many of those customers went bust, the telecom equipment makers were left holding the bad debt on their balance sheets. This contributed to a greater loss of value when the bubble burst than would have otherwise been the case, with networking equipment businesses losing more than 90% of their value over the ensuing decade.

          Worse yet were companies such as fiber-optic giant Global Crossing that engaged in direct “revenue roundtripping.” These companies cut deals—often at the end of a quarter in order to hit topline forecasts—in which they paid money to another company for services, and then that company agreed to purchase equipment of exactly equal value. When the bubble burst, Global Crossing went bankrupt, and its executives ultimately paid large legal settlements related to revenue roundtripping.

          It is memories of these kinds of transactions that have caused analysts to at least raise an eyebrow at some of Nvidia’s circular investments. Goldberg, the Seaport Global analyst, said the deals had a whiff of circular financing and were emblematic of “bubble-like behavior.”

          “The action will clearly fuel ‘circular’ concerns,” Stacy Rasgon, an analyst with Bernstein Research, wrote in an investor note following Nvidia’s announcement of its blockbuster investment in OpenAI. It’s a long way from a concern to a crisis, of course, but as AI company valuations get higher, that distance is starting to close.

          財富中文網所刊載內容之知識產權為財富媒體知識產權有限公司及/或相關權利人專屬所有或持有。未經許可,禁止進行轉載、摘編、復制及建立鏡像等任何使用。
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