Will the race to artificial general intelligence (AGI) lead us to a land of financial plenty \u2013 or will it end in a 2008-style bust? Trillions of dollars rest on the answer.<\/p>\n
The figures are staggering: an estimated $2.9tn (\u00a32.2tn) being spent on datacentres<\/a>, the central nervous systems of AI tools; the more than $4tn stock market capitalisation of Nvidia, the company that makes the chips powering cutting-edge AI systems; and the $100m signing-on bonuses offered by Mark Zuckerberg\u2019s Meta to top engineers at OpenAI, the company behind ChatGPT.<\/p>\n These sky-high numbers are all propped up by investors who expect a return on their trillions. AGI, a theoretical state of AI where systems gain human levels of intelligence across an array of tasks and are able to replace humans in white-collar jobs such as accountancy and law, is a keystone of this financial promise.<\/p>\n It offers the prospect of computer systems carrying out profitable work without the associated cost of human labour \u2013 a hugely lucrative scenario for companies developing the technology and the customers who deploy it.<\/p>\n There will be consequences if AI companies fall short: US stock markets, boosted heavily by the performance of tech stocks, could fall and cause damage to people\u2019s personal wealth; debt markets wrapped up in the datacentre boom could suffer a jolt that ripples elsewhere; GDP growth in the US, which has benefited from the AI infrastructure, could falter, which would have knock-on effects for interlinked economies.<\/p>\n David Cahn, a partner at one leading Silicon Valley investment firm, Sequoia Capital, says tech companies now have to deliver on AGI.<\/p>\n \u201cNothing short of AGI will be enough to justify the investments now being proposed for the coming decade,\u201d he wrote in a blog published in October<\/a>.<\/p>\n It means there is a lot hanging on progress towards advanced AI, and the trillions being poured into infrastructure and R&D to achieve it. One of the \u201cgodfathers\u201d of modern AI, Yoshua Bengio, says the progress of AGI could stall and the outcome would be bad for investors.<\/p>\n \u201cThere is a clear possibility that we will hit a wall, that there\u2019s some difficulty that we don\u2019t foresee right now, and we don\u2019t find any solution quickly,\u201d he says. \u201cAnd that could be a real [financial] crash. A lot of the people who are putting trillions right now into AI are also expecting the advances to continue fairly regularly at the current pace.\u201d<\/p>\n But Bengio, a prominent voice on the safety implications of AGI<\/a>, is clear that continued progress towards a highly advanced state of AI is the more likely endgame.<\/p>\n \u201cAdvances stalling is a minority scenario, like it\u2019s an unlikely scenario. The more likely scenario is we continue to move forward,\u201d he says.<\/p>\n The pessimistic view is that investors are backing an unrealistic outcome \u2013 that AGI will not happen without further breakthroughs.<\/p>\n David Bader, the director of the institute for data science at the New Jersey Institute of Technology, says trillions of dollars are being spent on scaling up \u2013 tech jargon for growing something quickly \u2013 the underlying technology for chatbots, known as transformers, in the expectation that increasing the amount of computing power behind current AI systems, by building more datacentres, will suffice.<\/p>\n \u201cIf AGI requires a fundamentally different approach, perhaps something we haven\u2019t yet conceived, then we\u2019re optimising an architecture that can\u2019t get us there no matter how large we make it. It\u2019s like trying to reach the moon by building taller ladders,\u201d he says.<\/p>\n Nonetheless, big US tech companies such as Google\u2019s parent Alphabet<\/a>, Amazon and Microsoft are ploughing ahead with datacentre plans with the financial cushion of being able to fund their AGI ambitions through the cash generated by their hugely profitable day-to-day businesses. This at least gives them some protection if the wall outlined by Bengio and Bader comes into view.<\/p>\n But there are other more worrying aspects to the boom. Analysts at Morgan Stanley, the US investment bank, estimate that $2.9tn will be spent on datacentres between now and 2028, with half of that covered by the cashflow from \u201chyperscalers\u201d such as Alphabet and Microsoft.<\/p>\n The rest will have to be covered by alternative sources such as private credit, a corner of the shadow banking sector<\/a> that is activating alarm bells at the Bank of England<\/a> and elsewhere. Meta, the owner of Facebook and Instagram, has borrowed $29bn from the private credit market to finance a datacentre in Louisiana.<\/p>\n AI-related sectors account for approximately 15% of investment grade debt in the US, which is even bigger than the banking sector, according to the investment bank JP Morgan.<\/p>\n Oracle, which has signed a $300bn datacentre deal with OpenAI<\/a>, has had an increase in credit default swaps, which are a form of insurance on a company defaulting on its debts. High-yield, or \u201cjunk debt\u201d, which represents the higher-risk end of the borrowing market, is also appearing in the AI sector via datacentre operators CoreWeave and TeraWulf. Growth is also being funded by asset-backed securities \u2013 a form of debt underpinned by assets such as loans or credit card debt, but in this case rent paid by tech companies to datacentre owners \u2013 in a form of financing that has risen sharply in recent years.<\/p>\n It is no wonder that JP Morgan says the AI infrastructure boom will require a contribution from all corners of the credit market.<\/p>\n Bader says: \u201cIf AGI doesn\u2019t materialise on expected timelines, we could see contagion across multiple debt markets simultaneously \u2013 investment-grade bonds, high-yield junk debt, private credit and securitised products \u2013 all of which are being tapped to fund this buildout.\u201d<\/p>\n Share prices linked to AI and tech are also playing an outsized role in US stock markets. The so-called \u201cmagnificent 7\u201d of US tech stocks \u2013 Alphabet, Amazon<\/a>, Apple, Tesla, Meta, Microsoft, and Nvidia \u2013 account for more than a third of the value of the S&P 500 index, the biggest stock market index in the US, compared with 20% at the start of the decade.<\/p>\n