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How to invest in artificial intelligence: Private startups or public markets?
如何投资人工智能：私人初创公司还是公开市场？
It has been a torrid 18 months for investors who bet on tech.
对于押注科技行业的投资者来说，过去的18个月很不好过。
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.
2010年代，对有快速增长雄心的公司出现了风险投资热潮，日本投资公司软银就是其中的典型代表，但现在它仍在为世界转向高利率、低企业估值而痛苦不已。
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).
但有一个领域，这家公司（其极富人格魅力的创始人为孙正义）还想冒险窥探一下：人工智能投资。
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.
ChatGPT等生成式人工智能平台的进步，让几乎每个投资者都在讨论如何理解这个新兴行业，以及它可能会颠覆哪些公司。
Mr Son sees parallels with the early period of the internet.
孙正义看到了生成式人工智能与早期互联网的相似之处。
Generative AI could provide a new pipeline of initial public offerings—and the foundation for the next generation of mega-cap tech firms.
生成式人工智能可能会提供一条新的IPO赛道，也会为下一代超高市值的科技公司打下基础。
Investors face two questions.
但投资者面临两个问题。
The first is which frontier technologies will make market leaders a fortune.
第一个问题是，哪些前沿技术会让市场领军者大赚一笔。
That is difficult enough.
这个问题已经够难的了。
The second, establishing whether the value will accrue to upstarts backed by venture capital or existing technology giants, is at least as tricky.
第二个问题是，确定技术的价值是会由风险资本支持的初创公司获得，还是由现在的科技巨头获得，这个问题至少也同样棘手。
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.
没有人知道是拥有最好的聊天机器人更好，还是拥有大量客户更好，在先进的新技术中抢占先机并不等同于能够从这个技术中赚钱。
Indeed, lots of the value of revolutionary innovation is often captured by existing giants.
事实上，革命性创新的许多价值往往被现有的巨头捕捉到。
Alphabet, Amazon and Meta are three of the seven largest listed companies in America, worth a combined $3.4trn.
Alphabet、亚马逊和Meta是美国七家最大的上市公司中的三家，总市值为3.4万亿美元。
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.
它们成立于1994年至2004年，那时互联网技术刚刚兴起、人们上网的时间越来越长。
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).
中国电子商务巨头阿里巴巴是另一个类似的例子(软银早期以2000万美元入股该公司，从而巩固了孙正义作为投资者的声誉)。
Spotting tech trends, and developing the best platforms, generated a gargantuan amount of value for early and even not-so-early investors.
发现技术趋势并开发最好的平台，这为早期甚至不算很早期的投资者创造了巨大的价值。
Legacy firms struggled to jump on the bandwagon.
传统公司很难加入这一潮流。
Will the story be the same this time around?
这一次还会是同样的故事吗？
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.
管理大师克莱顿·克里斯滕森的见解可以提供有用的指导。就在互联网巨头涌现之际，克里斯滕森开创了一种创新理论。
Christensen noted that smaller companies often gain traction in low-end markets and entirely new ones, which the largest incumbents eschew.
他指出，较小的公司往往在低端市场和全新的市场最有吸引力，而现有的大公司则会避开这些市场。
The incumbents focus on deploying new technology for their existing customers and lines of business.
现有公司专注于为其已有的客户和业务线部署新技术。
They are not incompetent or ignorant of technological progress.
他们并非在技术进步方面无能为力或一无所知。
Instead, they follow the seemingly correct path from a profit-maximising perspective—until it is too late and they are fatally undermined.
相反，他们从利润最大化的角度出发，走上了看似正确的道路，直到为时已晚，逐渐被削弱到致命的地步。
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.
像孙正义这样的投资者对专注于人工智能的初创企业的未来感到兴奋，他们暗示，颠覆性创新的时期正在到来。
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.
但最近人们对生成式人工智能平台的兴奋，大多集中在它们作为一种可应用的新技术的潜力上，而不是作为可以打开全新市场的公司。
In the case of other recent technological innovations, incumbents have won the day.
在最近的其他技术创新中，现有公司赢得了胜利。
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.
风险投资者埃拉德·吉尔指出，机器学习(包含生成式人工智能的更广泛的大类)之前的进步所产生的价值几乎全部归于现有公司。
The early internet startups have benefited, as have Microsoft and chip firms like Nvidia and Micron.
早期的互联网初创公司有受益，但微软和英伟达和美光等芯片公司也同样受益。
The earlier stages of machine learning produced no listed firms that might be considered the Amazon or Google of their niche.
机器学习的早期阶段没有产生可能被视为这一利基市场上的亚马逊或谷歌的上市公司。
Christensen’s insights make clear that revolutionary innovation does not always end up being revolutionary in business terms.
克里斯滕森的见解清楚地表明，革命性创新并不总是在商业上具有革命性。
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.
然而，现有的科技公司正在人工智能上投入巨额资金，这表明，如果这项技术真的能给商业带来革命性变化，那么这些公司应该处于有利地位。
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.
投资跟踪现有上市科技公司的宽基指数基金，最终收益可能会超过向严格专注于人工智能的非上市初创公司投资相等金额的收益。
Theories about why innovation is sometimes disruptive and sometimes not are more often discussed by students of business and management than stockpickers.
为什么创新有时具有颠覆性，有时不具有颠覆性，关于这个问题的理论更多的是工商管理专业的学生在讨论，而不是选股票的人。
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.
但在评估下一代市值数千亿美元的上市科技公司是否会在非上市人工智能公司中产生时，这两种可能性之间的差异至关重要。
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.
就目前情况来看，这项技术的市场价值最终更有可能成为本已庞大的科技巨头之弓上的一根新弦。
