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Roula Khalaf’s Favourite Stories
The AI Boom: A Shift in Outlook
Remember when China’s DeepSeek sent tremors through the US artificial intelligence industry and stunned Wall Street? That was last month. To listen to AI executives and investors now, you might think the world has moved on. Nvidia, the hardest hit, has recovered more than half the $630bn it lost.
The Speed of Recovery
The speed with which equilibrium has returned owes a lot to the assertion by the biggest US tech companies that they will spend even more than expected on AI infrastructure this year. But it also shows how quickly the investment case for AI has been rewritten. The question is how much this reflects a genuine change in outlook, and how much is just industry spin.
The Changing Landscape
The case for buying Nvidia stock once rested on claims such as those from Anthropic chief executive Dario Amodei, who barely six months ago predicted that the training costs for a cutting-edge large language model would soon reach $100bn. In the wake of DeepSeek, Amodei is still anticipating a huge jump in demand for AI chips — only now, it is for the completely different reason that they are needed for more complex tasks like reasoning, rather than the costs of model training.
Uncertainty and the Future of AI
No wonder investors are feeling an acute whiplash and a greater sense of uncertainty about the sustainability of the AI boom. The Chinese company’s breakthroughs increased the risk that even the most advanced large language models will quickly be turned into commodities. This came just as model-builders were facing another existential threat: throwing ever-greater amounts of computing power into training no longer produces the advances it once did.
The Shift to Complete Systems
OpenAI chief executive Sam Altman signalled the obvious strategic response in a post on X this week. No longer will OpenAI release its large language models as standalone products. Rather, they will be packaged together with its other technologies, such as "reasoning", into more complete systems. From now on, he said, the AI will "just work", whatever task a user throws at it.
Implications for the Industry
This is a familiar strategy in the tech industry. Moving "up the stack" — building more valuable technologies on the foundation of earlier products as they are commoditised — has long been seen as the way to defend prices and profit margins. If the cost of components that once provided a good margin collapse, so much the better: it brings down the overall cost and leads to faster uptake.
Conclusion
The Chinese company’s breakthroughs have just turned up the pressure on the AI industry, and the time for spin is over. The AI boom will depend much more on the actual usage of AI, not just the massive upfront spending that has gone into building models and infrastructure. The AI companies need to show they can provide real value to end customers.
FAQs
Q: What happened to the AI industry after the DeepSeek breakthrough?
A: The industry has recovered quickly, with the biggest US tech companies announcing they will spend even more on AI infrastructure.
Q: What is the new focus for OpenAI?
A: OpenAI will now package its large language models with other technologies, such as "reasoning", into complete systems.
Q: What are the implications for the AI industry?
A: The industry will shift towards providing more complete systems, and the focus will be on usage, not just massive upfront spending.
