The future of AI is a double-edged sword, and the stakes are incredibly high. With trillions of dollars at risk, the race to Artificial General Intelligence (AGI) could either lead us to unprecedented financial prosperity or plunge us into a devastating bust, akin to the 2008 financial crisis.
The numbers are mind-boggling: an estimated $2.9 trillion invested in datacenters, the lifeblood of AI tools; the staggering $4 trillion market capitalization of Nvidia, the powerhouse behind cutting-edge AI systems; and the $100 million signing bonuses offered by Meta to top engineers at OpenAI, the creators of ChatGPT. These astronomical figures are a testament to the faith investors have in the potential of AGI.
AGI, a theoretical pinnacle of AI, promises systems with human-level intelligence across diverse tasks, capable of replacing humans in white-collar jobs like accountancy and law. It offers the tantalizing prospect of profitable work without the associated costs of human labor, a scenario that could revolutionize industries and generate immense wealth.
However, there are potential pitfalls. If AI companies fail to deliver on their promises, the consequences could be severe. US stock markets, heavily reliant on tech stocks, could plummet, impacting personal wealth. Debt markets, intertwined with the datacentre boom, could suffer a shockwave, affecting other sectors. GDP growth in the US, which has benefited from AI infrastructure, could stall, with knock-on effects on interconnected economies.
David Cahn, a partner at Sequoia Capital, a leading Silicon Valley investment firm, emphasizes the need for AGI. He believes that nothing short of AGI will justify the proposed investments for the coming decade. This underscores the critical importance of progress towards advanced AI and the trillions being invested in infrastructure and research.
Yoshua Bengio, one of the 'godfathers' of modern AI, warns that progress towards AGI could stall, leading to a financial crash. He highlights the possibility of unforeseen difficulties, emphasizing that investors expect continuous advancements at the current pace.
The pessimistic view argues that investors are betting on an unrealistic outcome, with AGI requiring further breakthroughs. David Bader, director of the institute for data science at the New Jersey Institute of Technology, believes that trillions are being spent on scaling up the underlying technology for chatbots, known as transformers, with the expectation that increasing computing power will suffice.
Despite these concerns, tech giants like Alphabet, Amazon, and Microsoft are forging ahead with datacentre plans, financially cushioned by their profitable core businesses. This provides some protection against potential setbacks.
However, the boom has worrying aspects. Morgan Stanley estimates a $2.9 trillion spend on datacenters by 2028, with half funded by cashflow from hyperscalers like Alphabet and Microsoft. The remaining funding sources, such as private credit, are raising concerns at the Bank of England and other institutions.
AI-related sectors now account for approximately 15% of investment-grade debt in the US, surpassing the banking sector. This reliance on credit markets for AI infrastructure funding is a cause for concern.
Bader warns that if AGI fails to materialize on expected timelines, there could be a contagion across multiple debt markets simultaneously, impacting investment-grade bonds, high-yield debt, private credit, and securitized products.
The role of AI and tech-linked share prices in US stock markets is also significant. The 'magnificent 7' of US tech stocks account for over a third of the S&P 500 index's value, compared to 20% at the decade's start. This concentration raises concerns about a potential bubble.
The Bank of England has warned of a 'sharp correction' in US and UK markets due to the inflated valuations of AI-linked tech companies. Central bankers and the International Monetary Fund are concerned about a potential dotcom-style bubble, with stock markets slumping if AI fails to live up to expectations.
Even tech executives acknowledge the speculative nature of the boom. Sundar Pichai, CEO of Alphabet, warns of 'elements of irrationality,' while Jeff Bezos, founder of Amazon, describes the AI industry as an 'industrial bubble.' Sam Altman, CEO of OpenAI, agrees, stating that 'many parts of AI are bubbly right now.'
Despite these concerns, optimists argue that generative AI, encompassing chatbots and video generators, will transform industries and justify the expenditure. Benedict Evans, a technology analyst, compares the AI capex figures to other industries like oil and gas extraction, emphasizing the potential for huge opportunities.
The expectation for AGI is multitrillion-dollar, and the consequences of achieving it are both exciting and alarming. The cost of failure could also be significant, impacting pension funds, stock markets, and debt markets. The potential for messy transactions and circular deals unraveling adds to the complexity.
The future of AI is a high-stakes game, and the outcome remains uncertain. Will AGI revolutionize our world, or will it lead to a devastating crash? The answer lies in the progress and breakthroughs yet to come.
