The emergence of Chinese AI startup DeepSeek has triggered a sell-off on Wall Street, raising questions about the sustainability of high investments in AI by major U.S. companies. DeepSeek's potential to build a competitive AI model at a fraction of the cost has sparked concerns about a potential shift in the AI landscape.
Wall Street experienced a downturn on Monday driven by the emergence of Chinese AI startup DeepSeek. DeepSeek has garnered significant attention over the past week for its potential to create a competitive AI model at a fraction of the cost invested by major U.S. companies like Meta Platforms and Microsoft . Early reactions from analysts and strategists indicate concerns about potential reductions in capital expenditures if DeepSeek's claims prove even partially true.
However, there is a prevailing sentiment that this situation will ultimately present a buying opportunity for AI stocks. Despite this potential long-term outlook, a substantial sell-off is currently underway. Nvidia shares are among the most significantly affected, as the demand for the company's high-performance AI chips is being questioned.JPMorgan analyst Sandeep Deshpande expressed this sentiment in a note, stating, 'The AI investment cycle may be over-hyped and a more efficient future is possible.' Analysts are closely dissecting the implications of DeepSeek's emergence. JPMorgan's Deshpande noted that investors are apprehensive, believing that U.S. restrictions on China's AI progress have spurred innovation, leading to the development of a more efficient model. He pointed out the substantial investments made by U.S. companies in AI, such as Microsoft's projected $80 billion expenditure by 2025, Meta's investments between $6 billion and $65 billion, and OpenAI's $500 million commitment over four years for infrastructure development. In contrast, DeepSeek's success with a highly efficient and resource-light model is raising questions about whether the AI investment cycle is overheated and if a more cost-effective future is attainable. Roth analyst Rohit Kulkarni echoed similar concerns, questioning whether U.S. companies, including those involved in the Stargate project, are overspending on AI data centers. He believes that the availability of abundant capital has led to a false sense of security, and as 2025 progresses, investors will demand greater transparency from Big Tech regarding their strategies for optimizing AI capital intensity. Jefferies analyst Edison Lee suggested that DeepSeek's success could trigger two potential industry responses: a continued pursuit of increased computing power for faster model development or a shift towards efficiency and return on investment, resulting in lower demand for computing power by 2026.Bernstein analyst Stacy Rasgon downplayed the potential impact of DeepSeek, stating that while the models are impressive, they are not revolutionary. He maintained outperform ratings on Nvidia and Broadcom, advising clients against succumbing to the doomsday scenarios circulating. Citi analyst Atif Malik agreed, acknowledging that DeepSeek could challenge the dominance of U.S. companies in advanced AI models but emphasized the advantage U.S. companies have in accessing more sophisticated chips in a potentially more restrictive environment. He maintained a buy rating on Nvidia. Raymond James' semiconductor analyst Srini Pajjuri offered a more nuanced perspective, arguing that if DeepSeek's innovations are widely adopted, training costs could decline significantly, even for U.S. hyperscalers. He speculated that this could challenge the projections for massive XPU/GPU clusters. However, he also suggested that DeepSeek could accelerate U.S. hyperscalers' efforts to leverage their access to GPUs to differentiate themselves from cheaper alternatives. Pajjuri reiterated buy ratings on Nvidia and ASML. Cantor analyst C.J. Muse offered a bullish outlook, stating that DeepSeek's advancements are actually positive for the AI industry, as they bring artificial general intelligence (AGI) closer to reality. He predicted that the Jevons Paradox, where increased efficiency leads to higher overall demand, will drive the AI industry to seek more computing power, not less. Muse advised buying Nvidia on any weakness
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