Nvidia’s $589bn DeepSeek rout is largest in market history
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The semiconductor maker led a broader selloff in technology stocks after DeepSeek’s low-cost approach reignited concerns that big US companies have poured too much money into developing artificial intelligence. The Chinese firm appears to provide a comparable performance at a fraction of the price.
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The latest AI model of DeepSeek, released last week, is widely seen as competitive with those of OpenAI and Meta Platforms Inc. The open-sourced product was founded by quant-fund chief Liang Wenfeng and is now at the top of Apple’s App Store rankings.
Read: Nasdaq futures tumble as DeepSeek rattles tech market
“Concerns have immediately emerged that it could be a disruptor to the current AI business model, which relies on high-end chips and extensive computing power and hence energy,” Jefferies analysts said in a note to clients.
Nvidia has been the biggest beneficiary of the influx in spending on AI because they design semiconductors used in the technology. While that heavy spending looks poised to continue, investors may grow wary of rewarding companies that aren’t showing a sufficient return on the investment.
Meta announced plans on Friday to boost capital expenditures on AI projects this year by about half to as much as $65 billion, sending its shares to a record high. That came on the heels of OpenAI, SoftBank Group Corp. and Oracle Corp. announcing a $100 billion joint venture called Stargate to build out data centres and AI infrastructure projects around the US.
In a bid to stall China’s progress in AI, the US has banned the export of advanced semiconductor technologies to the country and is limiting sales of advanced Nvidia AI chips to others. But DeepSeek’s progress suggests Chinese AI engineers have found a way to work around the export bans, focusing on greater efficiency with limited resources.
Nvidia said in a statement Monday that DeepSeek’s model is an “excellent AI advancement” and indicated that the Chinese company didn’t violate US restrictions that limit access to advanced US chips in creating its technology. It also added that inference, or the work of running AI models, requires “significant numbers of Nvidia GPUs and high-performance networking.”
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