Nvidia defended the economics of the artificial intelligence spending boom after “Big Short” investor Michael Burry questioned the life cycle of its advanced chips and whether buyers will ever see a profit on them. On the earnings call late Wednesday, Chief Financial Officer Colette Kress said Nvidia’s hardware remains productive far longer than critics claim, thanks to efficiencies driven by the company’s CUDA software system. “The long useful life of NVIDIA’s CUDA GPUs is a significant Total Cost of Ownership advantage over accelerators,” Kress said, according to a transcript of the call by FactSet. “CUDA’s compatibility in our massive installed base extend the life [of] NVIDIA systems well beyond their original estimated useful life. Thanks to CUDA, the A100 GPUs we shipped six years ago are still running at full utilization today, powered by vastly improved software stack.” Kress said that Nvidia’s CUDA platform preserves the economic life of its graphics processing units, meaning customers get more long-term value even as new generations of chips deliver big efficiency gains. Nvidia’s argument addressed a growing concern on Wall Street: As Nvidia’s chips make rapid advances in power and efficiency, earlier generations may lose value before corporate buyers can monetize their AI investments. “Nvidia did a good job hinting at how depreciation schedules at their big customers are accurate as software updates prove to extend lives of older chips,” analyst Ben Reitzes at Melius Research said in a note to clients. Burry’s thesis Still, Burry and other critics are seizing on a contradiction. Nvidia says the newest chips are superior in performance, efficiency and capability, at the same time as it promises that older chips remain economically valuable. One of those defenses has to give. Burry agreed with this idea in an email to CNBC. The widely followed investor turned heads recently by disclosing a sizeable bearish position in Nvidia as well as Palantir . He took to X again following Nvidia’s blockbuster quarterly report, repeating his thesis that newer GPUs consume far less power, making older hardware uncompetitive. Therefore, companies may feel they have to invest in AI hardware to keep up, not because the investments are profitable yet. “Just because something is used does not mean it is profitable,” Burry wrote on X. “If that is the direction you are going, chances are you have to be doing it, and it is not pleasant.”
