經濟學人雙語 如何投資人工智能

How to invest in artificial intelligence

如何投資人工智能

Private startups or public markets

私人初創企業還是現有科技巨頭

It has been a torrid 18 months for investors who bet on tech. SoftBank, a Japanese investment firm that epitomised the 2010s boom in venture capital for companies with rapid-growth ambitions, is still smarting from the shift to a world of higher interest rates and lower corporate valuations. But there is one area in which the firm, run by Son Masayoshi, its charismatic founder, wants to peek above the parapet: investments in artificial intelligence (ai).

對于押寶科技的投資者而言，過去的18個月異常艱難。二十一世紀第二個十年裡的風投熱潮中，日本投資公司軟銀（SoftBank）是踩在浪頭的弄潮兒；然而高利率、低公司估值的新态勢讓其添了不少傷疤。但在克裡斯馬氣質十足的創始人孫正義的上司下，總還是有那麼一個投資領域，讓這家公司好了傷疤忘了疼，忍不住想要青睐一番：人工智能（AI）。

The advances of generative-ai platforms, such as Chatgpt, have left just about every investor discussing what to make of the incipient industry, and which firms it might upturn. Mr Son sees parallels with the early period of the internet. Generative ai could provide a new pipeline of initial public offerings—and the foundation for the next generation of mega-cap tech firms.

ChatGPT等生成式AI平台的發展，讓幾乎所有投資者都在熱烈讨論如何看待這一奔騰而來的後浪，以及哪些公司會被拍在沙灘上。在孫正義看來，現下的人工智能與早期的網際網路行業有相似之處。生成式AI将造就許多新的上市公司，為下一代科技巨頭的誕生奠定基礎。

Investors face two questions. The first is which frontier technologies will make market leaders a fortune. That is difficult enough. The second, establishing whether the value will accrue to upstarts backed by venture capital or existing technology giants, is at least as tricky. Nobody knows if it is better to have the best chatbot or plenty of customers—having a head start in a whizzy new tech is not the same as being able to make money from it. Indeed, lots of the value of revolutionary innovation is often captured by existing giants.

投資者們需要回答兩個問題。第一，哪些前沿技術能使市場上司者大賺特賺？第二，搞清楚新技術創造的價值到底将花落誰家，是風投公司所支援的初創公司還是現有的科技巨頭？第一個問題已然作答不易，第二個問題的難度更是有增無減。到底是海量客戶更好，還是最強聊天機器人更香，無人能夠知曉：在新潮技術領域搶占先機并不等同于能從中獲利。事實上，革命性創新結出的果實往往都被守成巨頭摘走了。

Alphabet, Amazon and Meta are three of the seven largest listed companies in America, worth a combined $3.4trn. They were founded between 1994 and 2004, emerging at a time when internet technology was new and people were spending an increasing amount of time online. Alibaba, a Chinese e-commerce giant, is another similar example (SoftBank's early $20m stake in the company helped cement Mr Son's reputation as an investor). Spotting tech trends, and developing the best platforms, generated a gargantuan amount of value for early and even not-so-early investors. Legacy firms struggled to jump on the bandwagon.

谷歌母公司Alphabet、亞馬遜和Meta是美股七巨頭中的三家，總市值達3.4萬億美元。這些公司成立于1994年至2004年間，彼時網際網路技術初露鋒芒，人們上網沖浪的時間也越來越長。中國電商巨頭阿裡巴巴的崛起曆程也大差不差（阿裡巴巴初創之時，軟銀投資了2000萬美元，這讓孫正義作為投資者聲名鵲起）。發現技術趨勢并開發最佳平台，讓早期、乃至于稍晚一些才入場的投資者賺得盆滿缽滿。傳統公司則在這場潮流的追逐中步履維艱中落了下風。

Will the story be the same this time around? The insights of Clayton Christensen, a management guru who pioneered a theory of innovation just as the internet giants were bursting onto the scene, can provide a useful guide. Christensen noted that smaller companies often gain traction in low-end markets and entirely new ones, which the largest incumbents eschew. The incumbents focus on deploying new technology for their existing customers and lines of business. They are not incompetent or ignorant of technological progress. Instead, they follow the seemingly correct path from a profit-maximising perspective—until it is too late and they are fatally undermined.

相似的故事會否再次上演？管理學專家克萊頓·克裡斯坦森（Clayton Christensen）的見地頗有價值。網際網路巨頭紛紛湧現時，克裡斯坦森曾提出一個關于創新的理論。他指出，小公司往往在低端市場和全新賽道發力，而守成巨頭則對這些領域缺乏關注。這些守成巨頭緻力于将新技術應用于已有的業務線，為既有客戶服務。它們并非無能或對技術進步一無所知。相反，它們遵循着利益最大化原則，走在看似正确的道路上，直到為時已晚，迎來緻命一擊。

Investors like Mr Son, excited about the future of startups that focus on ai, are implicitly presuming that a period of disruptive innovation is under way. But most of the recent excitement about generative-ai platforms has focused on their potential as a new technology to be deployed, not as companies which could open up brand new markets. In the case of other recent technological innovations, incumbents have won the day. Elad Gil, a venture capitalist, has noted that the value of previous advances in machine learning, the broader category of which generative ai is a part, have accrued almost entirely to incumbents. The early internet startups have benefited, as have Microsoft and chip firms like Nvidia and Micron. The earlier stages of machine learning produced no listed firms that might be considered the Amazon or Google of their niche.

孫正義這樣的投資者對AI領域初創企業的未來感到興奮，他們隐隐感到一個颠覆性創新的時代正在到來。但近來，人們更多是興奮于生成式AI平台作為一種新技術的應用潛力，而非可以開辟全新市場的公司。在近期其他技術創新方面，守成巨頭已然大獲全勝。風險投資人埃拉德·吉爾（Elad Gil）指出，先前機器學習領域（生成式AI是機器學習的一種）的産出幾乎全部落入守成巨頭口袋之中。網際網路領域的先來者收益豐厚，微軟如此，英偉達和美光（Micron）等晶片公司也是如此。在早期階段，機器學習并沒有哺育出自己的亞馬遜或谷歌。

Christensen’s insights make clear that revolutionary innovation does not always end up being revolutionary in business terms. Yet existing tech firms are now spending enormous sums on ai, suggesting they should be well-placed if the tech does turn out to revolutionise business. It is possible an investment in a broad index fund tracking existing listed tech firms will end up outperforming the equivalent investment in private, strictly ai-focused startups.

克裡斯坦森的見解明确了一點，那就是革命性創新并非總能引發商業革命。然而，守成科技巨頭們用砸向AI行業的重金表明了自己的決心：如果這一技術真的能革了現有商業模式的命，那麼它們要擁有絕對優勢。相比于投資專注AI賽道的私人初創公司，在跟蹤現有上市科技公司的廣泛指數基金撒币的效果可能要更好一些。

Theories about why innovation is sometimes disruptive and sometimes not are more often discussed by students of business and management than stockpickers. But the difference between the two possibilities is crucial in assessing whether the next generation of listed tech companies, with market capitalisations in the hundreds of billions of dollars, is to be found among private ai firms. As things stand, it looks more likely that the market value of the technology will end up as a new string to the bow of already giant tech firms.

為何創新有時是颠覆性的，有時又不是——探讨這樣理論的更多是商學和管理學專業的學生，而非選股專家們。然而，若要評估私人AI公司中是否會誕生千億美元市值的下一代上市科技公司，這兩種可能性之間的差異就至關重要了。就目前情況而言，AI技術将成為守成科技巨頭皇冠上新的明珠。