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資深市場觀察人士警告:人工智能實(shí)際上“毫無用處”

WILL DANIEL
2024-07-11

詹姆斯·弗格森表示:“人工智能制造了一個(gè)‘裝模作樣,直到成功’的泡沫,最終可能導(dǎo)致災(zāi)難。”

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2024年6月28日,星期五,一名交易員在紐約證券交易所大廳工作。圖片來源:MICHAEL NAGLE/BLOOMBERG VIA GETTY IMAGES

如今,圍繞人工智能的炒作已避無可避。高管們利用一切機(jī)會(huì)向感興趣的投資者以及興趣稍低的消費(fèi)者強(qiáng)調(diào)其人工智能能力,因此,關(guān)于個(gè)人機(jī)器人助手和神奇的癌癥治療等新發(fā)展的承諾無處不在。

然而,并非所有人都受到人工智能大肆宣傳的震撼??偛课挥谟暮暧^經(jīng)濟(jì)研究公司MacroStrategy Partnership的創(chuàng)始合伙人詹姆斯·弗格森(James Ferguson)擔(dān)心,投資者對人工智能的狂熱會(huì)造成市場泡沫集中,這讓人想起互聯(lián)網(wǎng)泡沫時(shí)代。

弗格森在最新一期Merryn Talks Money播客中對彭博社記者梅里恩·薩默塞特·韋伯(Merryn Somerset Webb)說:“從歷史上看,這些泡沫都會(huì)帶來糟糕結(jié)局。因此,任何上了年紀(jì)并遇到過這種情況的人,都會(huì)傾向于相信結(jié)局會(huì)很糟糕。”

這位資深分析師認(rèn)為,幻覺——大型語言模型(LLM)傾向于編造事實(shí)、來源等——可能比最初預(yù)期的更棘手,導(dǎo)致人工智能的可行應(yīng)用大大減少。

他表示:“我認(rèn)為,人工智能仍然未經(jīng)完全證實(shí)。在硅谷,‘偽裝一切,直到成功’可能行得通,但對于我們其他人來說,我認(rèn)為‘一朝被蛇咬,十年怕井繩’可能更適用于人工智能。如果人工智能不可信……那么在我看來,人工智能實(shí)際上一無是處?!?/p>

弗格森還指出,人工智能最終可能會(huì)因過于“耗電”而無法成為許多企業(yè)的高性價(jià)比工具。Amsterdam School of Business and Economics最近的一項(xiàng)研究發(fā)現(xiàn),到2027年,僅人工智能應(yīng)用的用電量就相當(dāng)于整個(gè)荷蘭的用電量。

他表示:“先不談?dòng)ミ_(dá)(Nvidia)對其芯片收取越來越高的費(fèi)用,你還必須為在服務(wù)器上運(yùn)行這些芯片支付越來越多的費(fèi)用。因此,你最終得到的是非常昂貴的東西,而且除了一些適用面狹窄的應(yīng)用之外,無法在任何地方證明它是物有所值的?!?/p>

對于投資者,尤其是那些對人工智能充滿熱情的投資者,弗格森警告說,基于可疑承諾的過度科技炒作與互聯(lián)網(wǎng)泡沫破裂前的時(shí)期非常相似。他指出,在這兩個(gè)時(shí)期,市場回報(bào)都集中在科技股上,而科技股的交易基于華爾街的超高盈利增長預(yù)期。

但是,盡管有這些高預(yù)期,互聯(lián)網(wǎng)時(shí)代的硬件巨頭思科(Cisco)和英特爾(Intel)從那時(shí)起就一直讓投資者失望。弗格森認(rèn)為,今天的人工智能硬件巨頭英偉達(dá)可能也會(huì)經(jīng)歷類似的命運(yùn),尤其是考慮到其過高的估值。

他問道:“如果你認(rèn)為英偉達(dá)在十年后可能都不再是芯片領(lǐng)域的玩家(不管目前的增長率有多高),那么英偉達(dá)的銷售額乘數(shù)是多少才劃算呢?”這暗示英偉達(dá)可能不值投資者目前支付的近40倍銷售額的價(jià)格。

盡管弗格森認(rèn)為,像英偉達(dá)這樣與人工智能相關(guān)的科技股估值過高,但他也承認(rèn),沒有人能預(yù)測泡沫何時(shí)會(huì)結(jié)束。根據(jù)這位分析師的說法,這種動(dòng)態(tài)導(dǎo)致許多看跌的投資者即使在股票看起來很貴的時(shí)候也覺得“被迫”參與市場投資,這是一種很容易受損的方式。

他解釋說:“我的意思是,這肯定是互聯(lián)網(wǎng)泡沫時(shí)期發(fā)生的情況,例如,幾乎所有不是散戶的人都會(huì)看著這些情況說,‘好吧,這不可能持續(xù)下去,但話雖如此,如果這種情況再持續(xù)一個(gè)季度,而我不參與的話,我就會(huì)失業(yè)?!?/p>

弗格森認(rèn)為,好消息是,由于目前股市的泡沫主要集中在與人工智能相關(guān)的股票上,因此仍然是有價(jià)值的。

誠然,如果人工智能泡沫破裂,投資者將普遍感到痛苦。但在那之后,弗格森建議關(guān)注目前不受青睞的美國小盤股,這些股可能會(huì)從降息中受益,而且估值并不高。

他說:“在美國有很多價(jià)值可尋。問題是,這些價(jià)值要通過傳統(tǒng)的方式來尋找,即在小盤股中搜羅,尋找那些以傳統(tǒng)方式實(shí)現(xiàn)穩(wěn)步增長的企業(yè)。”(財(cái)富中文網(wǎng))

譯者:中慧言-王芳

如今,圍繞人工智能的炒作已避無可避。高管們利用一切機(jī)會(huì)向感興趣的投資者以及興趣稍低的消費(fèi)者強(qiáng)調(diào)其人工智能能力,因此,關(guān)于個(gè)人機(jī)器人助手和神奇的癌癥治療等新發(fā)展的承諾無處不在。

然而,并非所有人都受到人工智能大肆宣傳的震撼。總部位于英國的宏觀經(jīng)濟(jì)研究公司MacroStrategy Partnership的創(chuàng)始合伙人詹姆斯·弗格森(James Ferguson)擔(dān)心,投資者對人工智能的狂熱會(huì)造成市場泡沫集中,這讓人想起互聯(lián)網(wǎng)泡沫時(shí)代。

弗格森在最新一期Merryn Talks Money播客中對彭博社記者梅里恩·薩默塞特·韋伯(Merryn Somerset Webb)說:“從歷史上看,這些泡沫都會(huì)帶來糟糕結(jié)局。因此,任何上了年紀(jì)并遇到過這種情況的人,都會(huì)傾向于相信結(jié)局會(huì)很糟糕?!?/p>

這位資深分析師認(rèn)為,幻覺——大型語言模型(LLM)傾向于編造事實(shí)、來源等——可能比最初預(yù)期的更棘手,導(dǎo)致人工智能的可行應(yīng)用大大減少。

他表示:“我認(rèn)為,人工智能仍然未經(jīng)完全證實(shí)。在硅谷,‘偽裝一切,直到成功’可能行得通,但對于我們其他人來說,我認(rèn)為‘一朝被蛇咬,十年怕井繩’可能更適用于人工智能。如果人工智能不可信……那么在我看來,人工智能實(shí)際上一無是處?!?/p>

弗格森還指出,人工智能最終可能會(huì)因過于“耗電”而無法成為許多企業(yè)的高性價(jià)比工具。Amsterdam School of Business and Economics最近的一項(xiàng)研究發(fā)現(xiàn),到2027年,僅人工智能應(yīng)用的用電量就相當(dāng)于整個(gè)荷蘭的用電量。

他表示:“先不談?dòng)ミ_(dá)(Nvidia)對其芯片收取越來越高的費(fèi)用,你還必須為在服務(wù)器上運(yùn)行這些芯片支付越來越多的費(fèi)用。因此,你最終得到的是非常昂貴的東西,而且除了一些適用面狹窄的應(yīng)用之外,無法在任何地方證明它是物有所值的。”

對于投資者,尤其是那些對人工智能充滿熱情的投資者,弗格森警告說,基于可疑承諾的過度科技炒作與互聯(lián)網(wǎng)泡沫破裂前的時(shí)期非常相似。他指出,在這兩個(gè)時(shí)期,市場回報(bào)都集中在科技股上,而科技股的交易基于華爾街的超高盈利增長預(yù)期。

但是,盡管有這些高預(yù)期,互聯(lián)網(wǎng)時(shí)代的硬件巨頭思科(Cisco)和英特爾(Intel)從那時(shí)起就一直讓投資者失望。弗格森認(rèn)為,今天的人工智能硬件巨頭英偉達(dá)可能也會(huì)經(jīng)歷類似的命運(yùn),尤其是考慮到其過高的估值。

他問道:“如果你認(rèn)為英偉達(dá)在十年后可能都不再是芯片領(lǐng)域的玩家(不管目前的增長率有多高),那么英偉達(dá)的銷售額乘數(shù)是多少才劃算呢?”這暗示英偉達(dá)可能不值投資者目前支付的近40倍銷售額的價(jià)格。

盡管弗格森認(rèn)為,像英偉達(dá)這樣與人工智能相關(guān)的科技股估值過高,但他也承認(rèn),沒有人能預(yù)測泡沫何時(shí)會(huì)結(jié)束。根據(jù)這位分析師的說法,這種動(dòng)態(tài)導(dǎo)致許多看跌的投資者即使在股票看起來很貴的時(shí)候也覺得“被迫”參與市場投資,這是一種很容易受損的方式。

他解釋說:“我的意思是,這肯定是互聯(lián)網(wǎng)泡沫時(shí)期發(fā)生的情況,例如,幾乎所有不是散戶的人都會(huì)看著這些情況說,‘好吧,這不可能持續(xù)下去,但話雖如此,如果這種情況再持續(xù)一個(gè)季度,而我不參與的話,我就會(huì)失業(yè)?!?/p>

弗格森認(rèn)為,好消息是,由于目前股市的泡沫主要集中在與人工智能相關(guān)的股票上,因此仍然是有價(jià)值的。

誠然,如果人工智能泡沫破裂,投資者將普遍感到痛苦。但在那之后,弗格森建議關(guān)注目前不受青睞的美國小盤股,這些股可能會(huì)從降息中受益,而且估值并不高。

他說:“在美國有很多價(jià)值可尋。問題是,這些價(jià)值要通過傳統(tǒng)的方式來尋找,即在小盤股中搜羅,尋找那些以傳統(tǒng)方式實(shí)現(xiàn)穩(wěn)步增長的企業(yè)?!保ㄘ?cái)富中文網(wǎng))

譯者:中慧言-王芳

There’s no avoiding the hype surrounding AI these days. Promises of new developments like personal robot assistants and miracle cancer cures are ubiquitous as executives take every opportunity to emphasize their AI chops to enthusiastic investors—and slightly less enthusiastic consumers.

Not everyone has been blown away by the AI fanfare, however. James Ferguson, founding partner of the UK-based macroeconomic research firm MacroStrategy Partnership, fears investors’ AI exuberance has created a concentrated market bubble that’s reminiscent of the dot-com era.

“These historically end badly,” Ferguson told Bloomberg’s Merryn Somerset Webb in the latest episode of the Merryn Talks Money podcast. “So anyone who’s sort of a bit long in the tooth and has seen this sort of thing before is tempted to believe it’ll end badly.”

The veteran analyst argued that hallucinations—large language models’ (LLMs) tendency to invent facts, sources, and more—may prove a more intractable problem than initially anticipated, leading AI to have far fewer viable applications.

“AI still remains, I would argue, completely unproven. And fake it till you make it may work in Silicon Valley, but for the rest of us, I think once bitten twice shy may be more appropriate for AI,” he said. “If AI cannot be trusted…then AI is effectively, in my mind, useless.”

Ferguson also noted AI may end up being too “energy hungry” to be a cost effective tool for many businesses. To his point, a recent study from the Amsterdam School of Business and Economics found that AI applications alone could use as much power as the Netherlands by 2027.

“Forget Nvidia charging more and more and more for its chips, you also have to pay more and more and more to run those chips on your servers. And therefore you end up with something that is very expensive and has yet to prove anywhere really, outside of some narrow applications, that it’s paying for this,” he said.

For investors, particularly those leaning into the AI enthusiasm, Ferguson warned that the excessive tech hype based on questionable promises is very similar to the period before the dot-com crash. He noted that during both of these periods, market returns were concentrated in tech stocks that traded based on Wall Street’s sky-high earnings growth estimates.

But despite those lofty forecasts, the dominant hardware giants of the dot-com era, Cisco and Intel, have largely disappointed investors ever since. Ferguson argued today’s AI hardware hero, Nvidia, might experience a similar fate, particularly given its elevated valuation.

“What multiple of sales is Nvidia a good deal on if you think that it might only have—no matter how stratospheric the growth rate at the moment—if you think that it’s probably not going to be a player in a decade’s time?” he asked, implying Nvidia might not be worth the current price tag of nearly 40 times sales investors are paying.

Despite his argument that AI-linked tech stocks like Nvidia are highly overvalued, Ferguson admitted that no one can predict when a bubble will end. This dynamic leads many bearish investors to feel “compelled to play” in the markets even when stocks look pricey, according to the analyst—and that’s a great way to get hurt.

“I mean, it’s certainly what was happening in the dotcom [bubble], for example, where almost anybody who wasn’t a retail punter was looking at these things and saying, ‘well, it can’t last, but having said that, if it lasts one more quarter and I’m not playing, I’ll lose my job,’” he explained.

The good news, according to Ferguson, is that because the current stock market bubble is so concentrated in AI-linked stocks, there is still value out there.

Of course, there will be widespread pain for investors if the AI bubble bursts. But after that, Ferguson recommended looking at the currently unloved U.S. small-cap stocks, which may benefit from interest rate cuts and aren’t highly valued.

“There’s a lot of value to be found in the U.S. The trouble is that that value is to be found in good old fashioned ways, trawling through small caps and looking for businesses that are growing in a good old fashioned, steady way,” he said.

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