Nvidia’s Jensen Huang on Leadership, ‘Tokenization,’ and GenAI Workforce Impact

The GPU chipmaking giant’s CEO says it’s important for CIOs to get started with AI and called for a more positive outlook on the emerging tech’s impact on the workforce.

Nvidia CEO Jensen Huang speaks to an audience of CIOs at Gartner's IT Symposium/XPO.
Nvidia CEO Jensen Huang speaks to an audience of CIOs at Gartner's IT Symposium/XPO.(Credit: Shane Snider)

Orlando, Fla. – Wearing his trademark black leather jacket, Nvidia CEO Jensen Huang on Tuesday delivered a highly anticipated keynote at Gartner’s IT Symposium/Xpo – where he talked about a range of leadership topics.

Nvidia has experienced meteoric success with its graphics processing units (GPUs). Once thought of mainly as a processor to handle graphics intense workloads, like video games, it turned out that the high-performance units were also efficient tools for large language models (LLMs). The near overnight success of Open AI’s ChatGPT after launching two years ago has created an arms race for companies to build GenAI platforms. Nvidia has profited well from that race, launching it to the top of the world’s most valuable companies.

So, CIOs were eager to hear from Huang about finding similar success. Hundreds of attendees lined up more than an hour before the doors to Huang’s keynote started opening.

Huang sat for an interview with Daryl Plummer, a Gartner analyst and vice president.

“Nvidia showed us a different path, from graphics chips to data centers to large scale generative AI, they released computing power that hits AI, the game, then world changing phenomenon that it is today,” Plummer said before Huang came onto the stage.

Fielding a question from Plummer about his personal style – which consists of the same publicly worn all-black attire – and if that simplicity leaves room for his leadership vision, Huang said his leadership has more to do with leaning into the future than focusing on style.

“When you see something impactful, something surprising and unexpected, you’ve got to ask yourself, ‘What does this mean and what’s the impact long term?’ … Now the next part is that if you deeply believe something, are going to do something about it. The best technique is to get started.”

Read the rest of this article in InformationWeek.

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Infrastructure for AI
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