10-02-2025
AI's civil war will force investors to pick sides
In their satirical history of the United Kingdom, '1066 And All That', the authors W C Sellar and R J Yeatman cast the English civil war of the 17th century as a conflict between the 'Wrong but Romantic' Cavaliers and the 'Right but Revolting' Roundheads. The aftermath of the release last month of Chinese startup DeepSeek's R1 artificial intelligence model, which matches or outperforms existing offerings from US technology titans at a fraction of the cost, has exposed a similar divide among the world's leading innovators in the field of machine learning.
On one side are those who strive for artificial general intelligence (AGI), the point where machines match or surpass human capabilities. Let's call them AI Cavaliers. Facing them are AI Roundheads who are focused on the more mundane goal of solving specific problems as efficiently as possible. Deciding which side to back in this AI civil war will be a defining decision for investors in the world's hottest technology.
The AI revolution that has gripped global stock markets for the past two years is driven by three epochal trends. The first is the generation of vast volumes of machine-readable data by the digitisation of almost every aspect of daily life.
The second is the collapse in cost of computing power prompted by ever more efficient chips. The third is a dramatic improvement in machine learning algorithms — the software that computers use to extract the signal from the noise in data sets. Together these developments have sparked a step-change in the accuracy of predictive modelling.
Every technologist agrees that this revolution is a momentous shift for the world. Where they diverge is on the question of where it can be most valuably applied. DeepSeek's dramatic intervention has thrown the differences between two visions for AI into stark relief.
The AI Cavaliers have a romantic vision of what the new machine learning algorithms can achieve. They see it as the royal road to the creation of thinking machines empowered with AGI. Their champions are well-known chatbots such as OpenAI's ChatGPT and Anthropic's Claude.
Their weapon of choice is the large language model (LLM), which uses AI's prodigious powers of pattern recognition to predict the next word in a string of text, with mind-bogglingly coherent results. The data they aspire to crunch is no less than the totality of human knowledge — or at least, everything that can be scraped from the internet.
Their appetite for computing power is therefore similarly vast. Indeed, in principle, it's limitless.
This intoxicating vision is the stuff of science fiction. So it's no surprise that the launch of ChatGPT's original iteration in November 2022 seized the public imagination and ignited a stock market boom. Yet it is haunted by three big questions.
The first is the fiercely disputed technical conundrum of whether LLMs can achieve AGI. The second is the commercial dilemma over whether the models have any enduring competitive advantage. Finally, there is the great financial unknown of how much capital spending these ventures will require in the form of semiconductors, data centres and energy.
The release of DeepSeek's model amplified all these doubts. Shares in Nvidia, the leading AI chip producer, dropped 17% in a day, wiping out a record of $600 billion of market value. Energy companies whose stocks had risen on forecasts of galloping electricity demand for AI training also took a hit. In the fortnight since, shares in both Microsoft and Google owner Alphabet sank following trading updates which cast doubt on their vast investments in computing capex. Put bluntly, DeepSeek has cast doubt on the return on investment in AGI. — Reuters
