Gelsinger bets on Nvidia after DeepSeek disruption; Altman promises groundbreaking AI
Gelsinger bets on Nvidia after DeepSeek disruption; Altman promises groundbreaking AI
Industry icons debate whether AI cost-cutting means growth or competition.
An entire Netflix, plus one Sony, and then some. That’s roughly the value Nvidia lost in a single trading day on Monday. $589 billion—more than half a trillion dollars—was wiped out, sparked by a groundbreaking announcement from a Chinese company, DeepSeek. The firm achieved what was previously thought impossible: developing an advanced AI model without relying on Nvidia's expensive, high-performance chips.
DeepSeek's innovation has shaken the global chip and AI industries, challenging the long-held belief that only vast computing power can drive breakthroughs in AI. However, experts argue this may not spell doom for Nvidia. Instead, the situation could open new opportunities in the rapidly growing AI sector. Former Intel CEO Pat Gelsinger took to LinkedIn to assert, “The market reaction is wrong, lowering the cost of AI will expand the market. Today I’m an Nvidia and AI stock buyer and happy to benefit from lower prices.”
In 1979, when the first spreadsheet program, VisiCalc, was released for the Apple II, it was widely believed that the accounting industry would face a significant decline. Previously, accountants managed spreadsheets manually, a labor-intensive process requiring substantial manpower and hours of work. The transition to digital spreadsheets was expected to make many workers in the field redundant and shrink the industry significantly. In reality, the opposite occurred: VisiCalc and its successors dramatically reduced the cost of accounting services while increasing demand. More people and businesses utilized these services more widely and frequently. Rather than shrinking, the industry expanded dramatically.
In Gelsinger's view, DeepSeek's model could signal a similar turning point for the AI industry: “Computing obeys the gas law. This means, it fills the available space as defined by available resources (capital, power, thermal budgets etc),” Gelsinger wrote. “As we saw in CMOS, PCs, multicore, virtualization, mobile and numerous others; making compute resources broadly available at radically lower price points, will drive an explosive expansion, not contraction, of the market.”
DeepSeek’s breakthrough significantly reduces the computing power needed to train its model. However, running the model—called inference—still requires substantial resources. Dr. Walter Goodwin, CEO of Fractile, a British startup specializing in inference chips, noted, “While DeepSeek has kept training costs for its model staggeringly low, it’s important to point out that it’s not had a revolutionary impact on inference costs,” said Goodwin. “What we’re seeing here is evidence of a flip, where the cost of training AI models becomes increasingly marginal compared to the cost of inference. It’s inference where we’ll see increased competition for incumbents like Nvidia in the long-run, as the costs remain exceptionally high.”
Nvidia echoed this sentiment, stating that inference "requires significant numbers of NVIDIA GPUs and high-performance networking." The shift in demand—from training chips to inference chips—may ultimately sustain or even grow Nvidia's market. Additionally, with open-source models like DeepSeek’s becoming available, companies may run these models locally, increasing demand for high-performance chips.
The change also provides opportunities for Intel, which has lagged in training chips but offers competitive solutions for inference systems. Intel claims its chips deliver better cost-benefit ratios than Nvidia’s, and expanding demand for inference computing could bolster its position in the AI market.
AI leaders like OpenAI appear unshaken. Founder Sam Altman wrote on X, “DeepSeek’s R1 is an impressive model, particularly around what they're able to deliver for the price. But mostly we are excited to continue to execute on our research roadmap and believe more compute is more important now than ever before to succeed at our mission.” Altman reiterated that expensive processors and massive infrastructure—like OpenAI’s $500 billion data center project with SoftBank and Oracle—remain essential for pushing the boundaries of AI. While Altman’s confidence reflects the industry consensus, the disruptive success of DeepSeek serves as a reminder: paradigms can shift in an instant.
