How to invest in artificial intelligence

Iit was t A rough 18 months for investors who bet on technology. Softbank, a Japanese investment firm that epitomized the 2010 boom in venture capital funding for companies with rapid growth ambitions, is still adjusting to the shift to a world of higher interest rates and lower corporate valuations. But there’s one area where the company, run by Son Masayoshi, its charismatic founder, wants to peek over the barrier: investments in artificial intelligence (AI).ai).

generative progression-ai Platforms, such as chatgpt, left almost every investor debating what to make of the emerging industry, and which companies can develop. Son sees parallels with the early period of the Internet. generative ai It could provide a new set of initial public offerings — and the foundation for the next generation of big tech companies.

Investors face two questions. The first is what groundbreaking technologies will make market leaders a fortune. This is hard enough. And second, determining whether the value will accrue in favor of venture capital-backed startups or incumbent tech giants is, at the very least, difficult. No one knows yet whether it is better to have the best chatbot or a lot of customers; Being ahead of a vibrant new technology does not mean being able to make money from it. In fact, much of the value of revolutionary innovation is often captured by the current giants.

Alphabet, Amazon, and Meta are three of the seven largest listed companies in America, collectively worth $3.3 trillion. Founded between 1994 and 2004, it emerged at a time when internet technology was new and people were spending an increasing amount of time online. Alibaba, the Chinese e-commerce giant, is another similar example (Softbank’s early $20 million stake in the company helped boost Son’s reputation as an investor). Spotting technology trends, and developing the best platforms, has generated an enormous amount of value for early and even not so early investors. Legacy companies struggled to get on the bandwagon.

Will the story be the same this time? Insights from Clayton Christensen, the management expert who pioneered innovation theory just as internet giants were exploding on the scene in the 1990s, can provide a useful guide. Christensen noted that small companies often gain traction in down markets and entirely new markets, which the largest incumbents avoid. The incumbents focus on deploying new technology to their existing clients and lines of business. They are not incompetent or ignorant of technological progress, but they are following the seemingly correct path from a profit maximization perspective – until it is too late and they are fatally undermined.

Investors like Mr. Son, are excited about the future of the startups they focus on ai, they implicitly assume that a period of disruptive innovation is underway. But most recent excitement about obstetrics-ai The platforms focused on their potential as a new technology to be deployed, rather than as companies that could open up entirely new markets. And in the case of other recent technological innovations, today’s incumbents won. Elad Gil, a venture capitalist, noted that the value of previous advances in machine learning, which represents the broader category ai is a part, almost entirely accrued to the incumbents. Early Internet startups benefited, as did Microsoft and chip companies such as Nvidia and Micron. The early stages of machine learning did not produce any listed companies that could be considered Amazon or Google in their respective fields.

Christensen’s insights show that revolutionary innovation does not always end up being revolutionary only in commercial terms. However, today’s technology companies are now spending huge amounts of money on it ai, suggesting that they should be in good stead if the technology is indeed revolutionary. An investment in a broad index fund that tracks existing listed technology companies could end up exceeding strictly the equivalent investment in the private sector aiFocused startups.

Theories about why innovation is sometimes disruptive and sometimes not are discussed more often by students of business and management than by stock pickers. But the difference between the two possibilities is important in assessing whether the next generation of listed technology companies with a market capitalization of hundreds of billions of dollars exists among the private sector. ai companies. With the current situation, it seems more likely that the market value of the technology as a new chain will end up on top of the tech giants already.

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