• Nvidia CEO Jensen Huang said investors misinterpreted DeepSeek’s AI advancements.
  • DeepSeek’s large language models were built with weaker chips, rattling markets in January.
  • In a pre-taped interview released Thursday, Huang emphasized the importance of AI post-training.

Nvidia’s (NASDAQ: NVDA) meteoric rise faced turbulence after a surprising challenge from Chinese AI firm DeepSeek, triggering a massive stock sell-off. Now, Nvidia CEO Jensen Huangas responded, setting the record straight on why investors misread the situation a virtual event aired Thursday regarding Busines Insider.

What Happened?

DeepSeek, backed by Chinese hedge fund High-Flyer, unveiled its AI model “DeepSeek R1” in January, claiming it was trained using lower-cost, less advanced chips compared to those required by Nvidia’s hardware. This revelation sparked fears that Nvidia’s dominance in AI infrastructure could be at risk, leading to a $600 billion market cap wipeout and a 20% drop in Huang’s personal net worth.

The market panic was swift—retail and institutional investors rushed to offload Nvidia shares, betting that DeepSeek’s efficiency breakthrough could weaken demand for Nvidia’s premium AI chips.

Jensen Huang Fires Back: “The Market Got It Wrong”

In response to the market’s reaction, Huang pushed back hard, arguing that investors misunderstood how AI models work.

🔹 The Real AI Bottleneck Is Post-Training, Not Pre-Training

“From an investor perspective, there was a mental model that the world was pre-training and then inference. And the inference was, you ask an AI a question, and it instantly gives you an answer. I don’t know whose fault it is, but obviously, that paradigm is wrong.” Huang explained.

Pre-training is still important, Huang said, but post-training is the “most important part of intelligence” and “where you learn to solve problems.”

DeepSeek’s innovations energize the AI world, he said. “It is so incredibly exciting. The energy around the world as a result of R1 becoming open-sourced — incredible

According to Huang, while pre-training is an important step, post-training—which refines AI models and enhances their intelligence—is where Nvidia’s technology plays a crucial role. DeepSeek’s efficiency claims only account for pre-training, but high-end chips like Nvidia’s are still critical for optimizing AI models before real-world deployment.

🔹 AI Evolution Still Needs High-Performance Compute Power

Even if firms experiment with alternative training techniques, mass adoption of AI in industries like healthcare, robotics, and finance will demand more advanced hardware, not less.

Huang reassured investors that Nvidia’s dominance in AI infrastructure is not under immediate threat. Instead, he believes that as AI models grow more sophisticated, demand for high-performance chips will increase, not decrease.

Nvidia Stock—What’s Next?

Despite the initial panic-driven sell-off, Nvidia’s stock has regained much of its losses, signaling renewed investor confidence. Analysts suggest that DeepSeek’s announcement was a wake-up call for AI markets but not an existential threat to Nvidia’s long-term growth.

✅ Bullish Case: Nvidia’s continued innovation in AI training and data center technology reinforces its moat in high-end computing. If post-training remains the most critical part of AI development, Nvidia’s chips will still be the industry standard.

❌ Bearish Risks: If alternative training techniques continue to evolve, Nvidia may face pricing pressure from new AI competitors, forcing it to adjust its long-term strategy.

For now, Nvidia remains at the heart of the AI revolution, and despite the DeepSeek scare, its grip on the AI chip market isn’t slipping anytime soon.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

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