DeepSeek, a China-based startup, unveiled an AI assistant last week that is 20 to 50 times cheaper to train and operate than OpenAI's models. This triggered a massive selloff of tech stocks that had been driven by the rise of AI. The selloff wiped nearly $600 billion from Nvidia’s market value as investors believed that demand for its processors would decrease. However, ex-Intel CEO Pat Gelsinger argues that compute performance is never enough and that high demand for processors from tech giants will remain.
The reaction to DeepSeek's breakthrough has overlooked three critical lessons from five decades of computing, according to Gelsinger's post over at LinkedIn. First, lowering the cost of computing resources expands the market, not contracts it. Just as cheaper technologies like PCs and mobile devices drove explosive growth, making AI more affordable will integrate it into more applications and will trigger broader adoption.
"The market reaction is wrong, lowering the cost of AI will expand the market," Gelsinger wrote. "Today I am an Nvidia and AI stock buyer and happy to benefit from lower prices."
The market reaction is wrong
ex-Intel CEO Pat Gelsinger
Second, engineering thrives under constraints, Gelsinger notes. DeepSeek’s team faced export restrictions and limited resources but created a world-class solution at a fraction of the usual cost. This ingenuity resonates with insights from computer science pioneers, who often state that they achieved their best work under significant limitations.
Third, openness fosters innovation, Gelsinger contends. The shift toward proprietary AI models stifles transparency and collaboration. Open ecosystems, as proven by Linux, Wi-Fi, and USB, consistently lead to better outcomes by encouraging scrutiny, ethical introspection, and broader adoption. DeepSeek’s open approach offers a much-needed reminder of the importance of shared innovation in AI.
“Open wins every time it is given a proper shot,” Gelsinger wrote. “AI is much too important for our future to allow a closed ecosystem to ever emerge as the one and only in this space.”
Gelsinger is not alone in his assessment that the market reaction is wrong; other market observers believe that the reaction was exaggerated. AMD, Broadcom, Intel, and Nvidia remain essential for building AI data centers and training large AI models.
"The real money in AI is providing the chips for the data centers from the likes of Nvidia, AMD, and Broadcom," Daniel Morgan, senior portfolio manager at Synovus Trust Company, told Reuters. "Overall, I view the AI tech selloff today as an opportunity to add high-quality tech shares on weakness."
DeepSeek’s model can be used locally on PCs and even smartphones, which is its fundamental advantage over ChatGPT's o1 and o4 models that reside on the cloud. However, training the model still requires advanced data center-grade hardware. Although DeepSeek reduces requirements for training hardware, companies like Anthropic and OpenAI could increase the number of parameters for their models while still consuming their vast computing resources.
To that end, demand for advanced processors in large-scale computing environments is expected to persist. Also, it is unclear how much resources — both computational and financial — DeepSeek consumed while prepping to train its model and developing all the optimizations to reduce requirements for the training cluster. Thus, the implications of DeepSeek’s breakthrough on the hardware market remain to be determined.
As a result, experts suggest that the selloff could present a buying opportunity for long-term investors in tech stocks like AMD, Broadcom, Intel, and Nvidia.
