Nvidia (NVDA) CEO Jensen Huang is not sounding the alarm over the introduction of AI models like China’s inexpensively trained DeepSeek R1. As an alternative, the chip executive said the world needs much more computing power to handle so-called reasoning and agentic AI applications than previously anticipated.
“Last 12 months, that is where almost the whole world got it unsuitable,” Huang said during his keynote at Nvidia’s GTC 2025.
“The computation requirement, the scaling law of AI is more resilient and, in truth, hyperaccelerated. The quantity of computation we want at this point consequently of agentic AI, consequently of reasoning, is well 100 times greater than we thought we would have liked this time last 12 months,” he explained.
Agentic AI is a kind of AI that may take actions on behalf of a user. Reasoning, or pondering AI, is a kind of AI that mimics the best way humans think by breaking down problems step-by-step to seek out the most effective answer to a user query.
DeepSeek’s R1 hit the scene in late January and sent Wall Street right into a meltdown when the corporate said the reasoning model matched the capabilities of OpenAI’s model and that it trained its broader DeepSeek V3 model for roughly $5 million, in comparison with the tens of thousands and thousands Silicon Valley spent training comparable models.
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Investors went streaming for the doors, sending Nvidia’s market value plummeting nearly $600 billion on fears that cloud firms would not must spend billions on Nvidia chips anymore.
More recently, Nvidia has been buffeted by concerns over President Trump’s tariff threats and the potential for the US to impose fresh export controls on chips destined for China.
Nvidia stock is down 14% 12 months so far but still up 30% over the past 12 months.
While tariffs and export controls are largely out of Nvidia’s hands, outside of lobbying for exceptions, the corporate is fully capable of take care of those pesky DeekSeek concerns, and Huang did just that in his speech.
Throughout the roughly two-hour showcase, the chief executive explained how reasoning models will profit from chips like the corporate’s recent Blackwell Ultra and Vera Rubin superchip. That, he explained, will only proceed in the long run as physical AI including humanoid robots and self-driving cars mature into the market.
The CEO also expanded on his plans for Nvidia’s CUDA software, which allows developers to make the most of the corporate’s chips for general processing, its Omniverse simulation platform, and a litany of other services.
