Nvidia CEO Jensen Huang’s ‘I feel like you’re interviewing Elon Musk’ answer to biographer when asked about…

Nvidia CEO Jensen Huang has drawn a clear line between his approach to artificial intelligence (AI) and that of Tesla’s Elon Musk, according to a new biography titled “The Thinking Machine: Jensen Huang, Nvidia, and the World’s Most Coveted Microchip” by Stephen Witt. The book, released in the US on April 8, details how Huang prefers to focus on building practical solutions rather than bold, futuristic ideas. When asked by Witt to describe the future he envisions, Huang reportedly replied, “I feel like you’re interviewing Elon right now, and not me.”
“I’m going to just build the hardware these guys need, and see where it’s going,” he told Witt as per a Business Insider report.
The biography compares the contrasting styles of the two tech leaders. According to Witt, Elon Musk often starts with an ambitious end goal—like living on Mars—and then works backward to develop the technology needed. In contrast, Huang takes a more grounded approach, building step by step based on existing tools and real-world needs.
Witt also writes that Huang “hates science fiction,” a key difference from Musk’s often sci-fi-inspired projects. The book describes Huang as someone who avoids speculation and instead focuses on solving today’s problems with available technology.

Firing back at recent skepticism surrounding Nvidia’s dominance in the AI chip market, Huang recently addressed claims that competitors like China's DeepSeek have achieved comparable AI capabilities with significantly less hardware. Unveiling Nvidia's next-generation Blackwell Ultra GPU at the Nvidia GPU Technology Conference (GTC), he said that everyone has been wrong about how much computer power you need for AI.
“Almost the entire world got it wrong,” Huang said, adding that “The amount of computation we need as a result of agentic AI, as a result of reasoning, is easily 100 times more than we thought we needed this time last year”.
Huang then emphasized that Nvidia is well-positioned to meet these changing demands. He highlighted the importance of both speed and scale in AI inference, stating, "If you take too long to answer a question, the customer is not going to come back. This is like web search."