Chinese AI startup DeepSeek is making waves, not just in the AI sector but in the stock market as well. Nvidia, the dominant force in AI chips, saw its stock value drop by around $600 billion on Monday as investors grew concerned about the long-term sustainability of AI spending. The rapid rise of DeepSeek has reignited discussions about whether AI investments are spiraling out of control.

Tech giants in the U.S. have poured billions into AI infrastructure, fueling Nvidia’s meteoric rise. However, if companies start scaling back their spending, Nvidia—whose business heavily relies on AI firms buying its chips in bulk—could face trouble. DeepSeek’s success also suggests that China may not be as dependent on Nvidia as previously believed. With Chinese firms developing their own chips, such as Huawei’s Ascend processors, and optimizing AI models to function on less powerful hardware, Nvidia's future sales could take a hit.

Some investors are now questioning whether it’s time to cash out. Nvidia’s stock had skyrocketed thanks to the AI boom, and when a stock reaches such heights, even minor concerns can trigger profit-taking. DeepSeek’s emergence may have provided the perfect opportunity for some investors to secure their gains before the AI hype cools.

This market shakeup extends beyond Nvidia. Nuclear power stocks, which were expected to benefit from the AI-driven demand for electricity, also suffered heavy losses. Shares of companies like Constellation Energy and Vistra fell over 20%, despite AI data centers requiring massive amounts of power. The issue isn’t the absence of demand but rather the realization that growth may not be as rapid as initially anticipated. As AI spending slows, nuclear power providers may not see the immediate surge they had counted on.

Ultimately, DeepSeek’s rise has forced investors to reassess their positions in AI and related industries. While the AI boom isn’t over, there is now a sense of caution, leading to increased market volatility. The key question remains: Is this just a temporary adjustment, or does it signal a broader reset in AI investments?