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          信貸助推AI熱潮,亦引發(fā)泡沫擔(dān)憂

          業(yè)內(nèi)關(guān)鍵人物也承認(rèn),人工智能投資者很可能將面臨陣痛。

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          6月2日,OpenAI首席執(zhí)行官薩姆·奧爾特曼出席在舊金山舉行的2025年Snowflake峰會(huì)。圖片來源:Justin Sullivan—Getty Images

          就在業(yè)內(nèi)高管和分析師紛紛質(zhì)疑人工智能是否正在催生又一個(gè)泡沫之際,信貸投資者正將數(shù)十億美元資金投入這個(gè)新技術(shù)領(lǐng)域。

          據(jù)知情人士本周透露,摩根大通(JPMorgan Chase & Co.)和三菱日聯(lián)金融集團(tuán)(Mitsubishi UFJ Financial Group)正牽頭承銷一筆超過220億美元的貸款,用于支持Vantage Data Centers建設(shè)一個(gè)龐大的數(shù)據(jù)中心園區(qū)。據(jù)彭博社本月報(bào)道,F(xiàn)acebook母公司Meta Platforms Inc.將從太平洋投資管理公司(Pacific Investment Management Co.)和Blue Owl Capital Inc.獲得290億美元資金,用于在路易斯安那州鄉(xiāng)村地區(qū)建設(shè)一個(gè)大型數(shù)據(jù)中心。

          未來還將涌現(xiàn)更多此類交易。僅OpenAI一家公司就預(yù)計(jì),其未來開發(fā)和運(yùn)營(yíng)人工智能服務(wù)所需的基礎(chǔ)設(shè)施投入將達(dá)數(shù)萬億美元。

          與此同時(shí),業(yè)內(nèi)關(guān)鍵人物也承認(rèn),人工智能投資者很可能將面臨陣痛。OpenAI首席執(zhí)行官薩姆·奧爾特曼本周表示,他看到當(dāng)前人工智能投資熱潮與上世紀(jì)90年代末的互聯(lián)網(wǎng)泡沫存在相似之處。在談及初創(chuàng)企業(yè)估值時(shí),他直言:“總會(huì)有人在這里遭受損失?!贝送?,麻省理工學(xué)院(Massachusetts Institute of Technology)的一項(xiàng)研究計(jì)劃發(fā)布報(bào)告指出,在企業(yè)界,95%的生成式人工智能項(xiàng)目未能帶來任何利潤(rùn)。

          這些情況足以讓信貸市場(chǎng)的觀察者們感到不安。

          花旗集團(tuán)(Citigroup)美國(guó)投資級(jí)信貸策略主管丹尼爾·索里德表示:“信貸投資者自然會(huì)回想起2000年代初的情景,當(dāng)時(shí)電信公司可謂過度建設(shè)、過度舉債,最終我們看到這些資產(chǎn)出現(xiàn)了重大減值。因此,從中期來看,人工智能熱潮無疑會(huì)引發(fā)關(guān)于可持續(xù)性的疑慮?!?/p>

          在早期,用于訓(xùn)練和驅(qū)動(dòng)最先進(jìn)人工智能模型的基礎(chǔ)設(shè)施建設(shè)資金,主要由人工智能公司自身承擔(dān),其中包括Alphabet Inc.旗下谷歌(Google)和Meta Platforms Inc.等科技巨頭。不過,近期的資金來源正越來越多地轉(zhuǎn)向債券投資者和私人信貸機(jī)構(gòu)。

          據(jù)彭博情報(bào)(Bloomberg Intelligence)近期分析,這類融資風(fēng)險(xiǎn)敞口的形式和規(guī)模多樣,風(fēng)險(xiǎn)等級(jí)也各不相同。許多大型科技公司——即所謂的AI超大規(guī)模服務(wù)商——一直通過發(fā)行優(yōu)質(zhì)企業(yè)債來為新建基礎(chǔ)設(shè)施融資。由于這些債務(wù)有現(xiàn)有現(xiàn)金流作為擔(dān)保,因此被認(rèn)為相對(duì)安全。

          如今,大部分債務(wù)融資正來自私人信貸市場(chǎng)。

          瑞銀集團(tuán)(UBS)信貸策略主管馬修·米什表示:“過去三個(gè)季度,人工智能領(lǐng)域的私人信貸融資規(guī)模每季度約為500億美元,這是保守估計(jì)。即便不計(jì)入Meta和Vantage的巨額交易,私人信貸市場(chǎng)的資金供給也已是公共市場(chǎng)的兩到三倍。”

          與此同時(shí),許多新的計(jì)算中心正通過商業(yè)地產(chǎn)抵押貸款支持證券(CMBS)融資,這類證券并非與企業(yè)主體掛鉤,而是與園區(qū)產(chǎn)生的付款綁定。據(jù)摩根大通本月估算,人工智能基礎(chǔ)設(shè)施支持的CMBS已較2024年全年總額增長(zhǎng)30%,達(dá)到156億美元。

          索里德與花旗的一位同事在8月8日發(fā)布了一份報(bào)告,重點(diǎn)分析了公用事業(yè)公司面臨的特殊風(fēng)險(xiǎn)。這些公司為建設(shè)滿足高能耗數(shù)據(jù)中心所需的電力基礎(chǔ)設(shè)施而大幅舉債。索里德及其同事與其他分析師一樣,都對(duì)當(dāng)前如此巨額的投入感到擔(dān)憂,因?yàn)槿斯ぶ悄茼?xiàng)目尚未證明其具備長(zhǎng)期創(chuàng)造營(yíng)收的能力。

          標(biāo)普全球評(píng)級(jí)(S&P Global Ratings)私人市場(chǎng)分析全球主管露絲·楊表示:“數(shù)據(jù)中心項(xiàng)目的融資周期往往長(zhǎng)達(dá)20至30年,而我們甚至無法確定五年后這項(xiàng)技術(shù)會(huì)是什么樣子。我們會(huì)保守評(píng)估未來現(xiàn)金流,因?yàn)槿狈v史參考?!?/p>

          瑞銀集團(tuán)指出,壓力已經(jīng)開始顯現(xiàn),表現(xiàn)之一是面向科技領(lǐng)域的私人信貸機(jī)構(gòu)的實(shí)物支付(PIK)貸款正在增加。根據(jù)瑞銀的數(shù)據(jù),第二季度,商業(yè)發(fā)展公司(BDCs)的PIK收入占比升至6%,創(chuàng)下自2020年以來的最高水平。

          但這股資金洪流短期內(nèi)似乎難以停歇。

          穆迪全球項(xiàng)目與基礎(chǔ)設(shè)施融資團(tuán)隊(duì)高級(jí)副總裁約翰·梅迪納表示:“直接貸款機(jī)構(gòu)不斷在籌集資本,而這些資金必須找到去處。他們把這些資本需求巨大的AI超大規(guī)模服務(wù)商視作下一個(gè)長(zhǎng)期基礎(chǔ)設(shè)施投資標(biāo)的?!保ㄘ?cái)富中文網(wǎng))

          譯者:劉進(jìn)龍

          審校:汪皓

          就在業(yè)內(nèi)高管和分析師紛紛質(zhì)疑人工智能是否正在催生又一個(gè)泡沫之際,信貸投資者正將數(shù)十億美元資金投入這個(gè)新技術(shù)領(lǐng)域。

          據(jù)知情人士本周透露,摩根大通(JPMorgan Chase & Co.)和三菱日聯(lián)金融集團(tuán)(Mitsubishi UFJ Financial Group)正牽頭承銷一筆超過220億美元的貸款,用于支持Vantage Data Centers建設(shè)一個(gè)龐大的數(shù)據(jù)中心園區(qū)。據(jù)彭博社本月報(bào)道,F(xiàn)acebook母公司Meta Platforms Inc.將從太平洋投資管理公司(Pacific Investment Management Co.)和Blue Owl Capital Inc.獲得290億美元資金,用于在路易斯安那州鄉(xiāng)村地區(qū)建設(shè)一個(gè)大型數(shù)據(jù)中心。

          未來還將涌現(xiàn)更多此類交易。僅OpenAI一家公司就預(yù)計(jì),其未來開發(fā)和運(yùn)營(yíng)人工智能服務(wù)所需的基礎(chǔ)設(shè)施投入將達(dá)數(shù)萬億美元。

          與此同時(shí),業(yè)內(nèi)關(guān)鍵人物也承認(rèn),人工智能投資者很可能將面臨陣痛。OpenAI首席執(zhí)行官薩姆·奧爾特曼本周表示,他看到當(dāng)前人工智能投資熱潮與上世紀(jì)90年代末的互聯(lián)網(wǎng)泡沫存在相似之處。在談及初創(chuàng)企業(yè)估值時(shí),他直言:“總會(huì)有人在這里遭受損失。”此外,麻省理工學(xué)院(Massachusetts Institute of Technology)的一項(xiàng)研究計(jì)劃發(fā)布報(bào)告指出,在企業(yè)界,95%的生成式人工智能項(xiàng)目未能帶來任何利潤(rùn)。

          這些情況足以讓信貸市場(chǎng)的觀察者們感到不安。

          花旗集團(tuán)(Citigroup)美國(guó)投資級(jí)信貸策略主管丹尼爾·索里德表示:“信貸投資者自然會(huì)回想起2000年代初的情景,當(dāng)時(shí)電信公司可謂過度建設(shè)、過度舉債,最終我們看到這些資產(chǎn)出現(xiàn)了重大減值。因此,從中期來看,人工智能熱潮無疑會(huì)引發(fā)關(guān)于可持續(xù)性的疑慮。”

          在早期,用于訓(xùn)練和驅(qū)動(dòng)最先進(jìn)人工智能模型的基礎(chǔ)設(shè)施建設(shè)資金,主要由人工智能公司自身承擔(dān),其中包括Alphabet Inc.旗下谷歌(Google)和Meta Platforms Inc.等科技巨頭。不過,近期的資金來源正越來越多地轉(zhuǎn)向債券投資者和私人信貸機(jī)構(gòu)。

          據(jù)彭博情報(bào)(Bloomberg Intelligence)近期分析,這類融資風(fēng)險(xiǎn)敞口的形式和規(guī)模多樣,風(fēng)險(xiǎn)等級(jí)也各不相同。許多大型科技公司——即所謂的AI超大規(guī)模服務(wù)商——一直通過發(fā)行優(yōu)質(zhì)企業(yè)債來為新建基礎(chǔ)設(shè)施融資。由于這些債務(wù)有現(xiàn)有現(xiàn)金流作為擔(dān)保,因此被認(rèn)為相對(duì)安全。

          如今,大部分債務(wù)融資正來自私人信貸市場(chǎng)。

          瑞銀集團(tuán)(UBS)信貸策略主管馬修·米什表示:“過去三個(gè)季度,人工智能領(lǐng)域的私人信貸融資規(guī)模每季度約為500億美元,這是保守估計(jì)。即便不計(jì)入Meta和Vantage的巨額交易,私人信貸市場(chǎng)的資金供給也已是公共市場(chǎng)的兩到三倍。”

          與此同時(shí),許多新的計(jì)算中心正通過商業(yè)地產(chǎn)抵押貸款支持證券(CMBS)融資,這類證券并非與企業(yè)主體掛鉤,而是與園區(qū)產(chǎn)生的付款綁定。據(jù)摩根大通本月估算,人工智能基礎(chǔ)設(shè)施支持的CMBS已較2024年全年總額增長(zhǎng)30%,達(dá)到156億美元。

          索里德與花旗的一位同事在8月8日發(fā)布了一份報(bào)告,重點(diǎn)分析了公用事業(yè)公司面臨的特殊風(fēng)險(xiǎn)。這些公司為建設(shè)滿足高能耗數(shù)據(jù)中心所需的電力基礎(chǔ)設(shè)施而大幅舉債。索里德及其同事與其他分析師一樣,都對(duì)當(dāng)前如此巨額的投入感到擔(dān)憂,因?yàn)槿斯ぶ悄茼?xiàng)目尚未證明其具備長(zhǎng)期創(chuàng)造營(yíng)收的能力。

          標(biāo)普全球評(píng)級(jí)(S&P Global Ratings)私人市場(chǎng)分析全球主管露絲·楊表示:“數(shù)據(jù)中心項(xiàng)目的融資周期往往長(zhǎng)達(dá)20至30年,而我們甚至無法確定五年后這項(xiàng)技術(shù)會(huì)是什么樣子。我們會(huì)保守評(píng)估未來現(xiàn)金流,因?yàn)槿狈v史參考。”

          瑞銀集團(tuán)指出,壓力已經(jīng)開始顯現(xiàn),表現(xiàn)之一是面向科技領(lǐng)域的私人信貸機(jī)構(gòu)的實(shí)物支付(PIK)貸款正在增加。根據(jù)瑞銀的數(shù)據(jù),第二季度,商業(yè)發(fā)展公司(BDCs)的PIK收入占比升至6%,創(chuàng)下自2020年以來的最高水平。

          但這股資金洪流短期內(nèi)似乎難以停歇。

          穆迪全球項(xiàng)目與基礎(chǔ)設(shè)施融資團(tuán)隊(duì)高級(jí)副總裁約翰·梅迪納表示:“直接貸款機(jī)構(gòu)不斷在籌集資本,而這些資金必須找到去處。他們把這些資本需求巨大的AI超大規(guī)模服務(wù)商視作下一個(gè)長(zhǎng)期基礎(chǔ)設(shè)施投資標(biāo)的?!保ㄘ?cái)富中文網(wǎng))

          譯者:劉進(jìn)龍

          審校:汪皓

          Credit investors are pouring billions of dollars into artificial intelligence investments, just as industry executives and analysts are raising questions about whether the new technology is inflating another bubble.

          JPMorgan Chase & Co. and Mitsubishi UFJ Financial Group are leading the sale of a more than $22 billion loan to support Vantage Data Centers’ plan to build a massive data-center campus, people with knowledge of the matter said this week. Meta Platforms Inc., the parent of Facebook, is getting $29 billion from Pacific Investment Management Co. and Blue Owl Capital Inc. for a massive data center in rural Louisiana, Bloomberg reported this month.

          And plenty more of these deals are coming. OpenAI alone estimates it will need trillions of dollars over time to spend on the infrastructure required to develop and run artificial intelligence services.

          At the same time, key players in the industry acknowledge there is probably pain ahead for AI investors. OpenAI Chief Executive Officer Sam Altman said this week that he sees parallels between the current investment frenzy in artificial intelligence and the dot-com bubble in the late 1990s. When discussing startup valuations he said, “someone’s gonna get burned there.” And a Massachusetts Institute of Technology initiative released a report indicating that 95% of generative AI projects in the corporate world have failed to yield any profit.

          Altogether, it’s enough to make credit watchers nervous.

          “It’s natural for credit investors to think back to the early 2000s when telecom companies arguably overbuilt and over borrowed and we saw some significant writedowns on those assets,” said Daniel Sorid, head of U.S. investment grade credit strategy at Citigroup. “So, the AI boom certainly raises questions in the medium term around sustainability.”

          The early build-out of the infrastructure needed to train and power the most advanced AI models was largely funded by the AI companies themselves, including tech giants like Alphabet Inc.’s Google and Meta Platforms Inc. Recently, though, the money has been increasingly coming from bond investors and private credit lenders.

          The exposure here comes in many shapes and sizes, with varying degrees of risk. Many large tech companies — the so-called AI hyperscalers — have been paying for new infrastructure with gold-plated corporate debt, which is likely safe due to the existing cash flows that secure the debt, according to recent analysis from Bloomberg Intelligence.

          Much of the debt funding now is coming from private credit markets.

          “Private credit funding of artificial intelligence is running at around $50 billion a quarter, at the low end, for the past three quarters. Even without factoring in the mega deals from Meta and Vantage, they are already providing two to three times what the public markets are providing,” said Matthew Mish, head of credit strategy at UBS.

          And many new computing hubs are being funded through commercial mortgage-backed securities, tied not to a corporate entity, but to the payments generated by the complexes. The amount of CMBS backed by AI infrastructure is already up 30%, to $15.6 billion, from the full year total in 2024, JPMorgan Chase & Co. estimated this month.

          Sorid and a colleague at Citi put out a report on Aug. 8 focusing on the particular risks for the utility firms that have boosted borrowing to build the electrical infrastructure needed to feed the power-hungry data centers. They and other analysts share a commonly held concern about spending so much money right now, before AI projects have shown their ability to generate revenue over the long term.

          “Data center deals are 20 to 30 year tenor fundings for a technology that we don’t even know what they will look like in five years,” said Ruth Yang, global head of private market analytics at S&P Global Ratings. “We are conservative in our assessment of forward cash flows because we don’t know what they will look like, there’s no historical basis.”

          The stress has begun to appear in the rise of payment-in-kind loans to tech-oriented private credit lenders, UBS Group noted. In the second quarter, PIK income in BDCs reached the highest level since 2020, climbing to 6%, according to UBS.

          But the fire hose of money is unlikely to stop anytime soon.

          “Direct lenders are constantly raising capital, and it has to go somewhere,” said John Medina, senior vice president in Moody’s Global Project and Infrastructure Finance Team. “They see these hyperscalers, with this massive capital need, as the next long-term infrastructure asset.”

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