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SuccessNvidia

Departing Nvidia VP salutes Jensen Huang’s leadership, and pinpoints the 3 key principles he taught her

Orianna Rosa Royle
By
Orianna Rosa Royle
Orianna Rosa Royle
Associate Editor, Success
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Orianna Rosa Royle
By
Orianna Rosa Royle
Orianna Rosa Royle
Associate Editor, Success
Down Arrow Button Icon
June 26, 2024, 7:15 AM ET
Nvidia's outgoing VP said that her boss Jensen Huang taught her about the importance of first principles thinking, zero-billion dollar markets and speed-of-light execution.
Nvidia's outgoing VP said that her boss Jensen Huang taught her about the importance of first principles thinking, zero-billion dollar markets and speed-of-light execution.Gene Wang—Getty Images

Nvidia VP Simona Jankowski has just bid the $3.1 trillion tech giant farewell—and paid homage to her boss and CEO Jensen Huang on her way out.

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“Working with Jensen has been the experience of a lifetime,” she concluded of her time reporting into the billionaire from humble beginnings. 

After nearly seven years of running investor relations and strategic finance at the chipmaker, she gushed on LinkedIn that Huang is “in a class of his own” before sharing the three leadership lessons he taught her: “First principles thinking, zero-billion dollar markets, speed-of-light execution and so much more.”

“He inspired me to reach to the limits, made me laugh to tears, and taught me the harmony of work and family,” Jankowski added.

The world’s most valuable company—thanks to Huang’s first principles thinking and zero-billion dollar market concepts

After an initial foray into developing graphics processors for computer games, the company invented one of the first AI-friendly GPUs and now it’s dominating the market, selling over 70% of all AI chips.

Last week, Nvidia briefly topped Microsoft to become the world’s most valuable company with a market capitalization of $3.34 trillion.

Since Jankowski joined Nvidia in 2017, she boasted that she’s watched its revenue grow tenfold and its earnings and market cap have jumped by more than 20 times.

“Perhaps even more impressively, the AI compute performance delivered by NVIDIA’s flagship GPU is up over 1,000X, while the size of frontier AI models has grown by over 20,000X,” she added. “Living through exponentials like these is rare and thrilling, and keeps the learning curve steep and exciting.”

But Nvidia’s GPU success was no accident—it clearly demonstrates Huang’s habit of applying first principles thinking (that is, questioning every assumption to get to the basic element of a problem) to find innovative solutions instead of mimicking existing models, and forging a business in a zero-billion dollar market (that is, a nascent but potentially giant market).

Previously, CPUs—the most common computer chips, which date back to the 1950s—were great for executing complex calculations one at a time, but they didn’t quite fit the needs of data scientists when deep learning and AI research intensified in the 2010s. 

But GPUs can perform many simple calculations at once—and as it turned out, Nvidia’s GPUs were a perfect fit for the type of computing systems AI developers needed to build and train large language models.

“Jensen is a visionary and saw the trends of GPU adoption in data centers early on and aligned the company’s strategy to that vision,” a semiconductors senior research analyst, Tristan Gerra, told Fortune. 

One of its prescient moves included creating CUDA, a high-level programming tool the company built in 2007 to help unlock the full capability of its GPUs in a straightforward way. 

CUDA is now so widely used that it’s difficult for companies building large language models like OpenAI’s ChatGPT to imagine themselves using other tech.

As Huang himself previously pointed out, that’s precisely what it means to operate in a zero-billion-dollar market: 

“Almost all of our purposes should be to go and do something that hasn’t been done before, that is insanely hard to do, that if you achieve it could make a real contribution,” he told Stripe’s CEO Patrick Collison on stage last month.

“That market is probably zero billion dollars in size because it’s never been done before—I’d rather be a market maker than a market taker.”

Who is Simona Jankowski?

Jankowski, a Stanford University alum, worked at Goldman Sachs for her entire career before joining Nvidia.

But even then, Jankowski revealed that she had been working closely with the chipmaker for quite some time. 

“As a newly minted equity research analyst at Goldman Sachs in 2001, my first assignment was building the NVDA financial model, and I met Jensen Huang as part of our initiation of coverage,” she explained in her LinkedIn post.

Following the company’s “cool product launches, rapid technology advances, supply chain trips to Taiwan” and “Q&As with Jensen”, she said, helped her make her name as an analyst. 

Jankowski worked her way up the ranks, covering the semi-conductor industry within Goldman’s Global Investment Research division for years before being promoted to managing director.

Now, she’s off to join the world of startups as a chief financial officer—but she’s not yet revealed the venture in question.  

Fortune has reached Jankowski for comment.

Join us for a virtual Fortune 500 Europe C-suite conversation, in partnership with Syndio, on mastering workforce decisions and pay transparency in the age of AI. Built for global and regional HR leaders, this session, moderated by Fortune editor Francesca Cassidy, will take place Wednesday, March 25, at 2:30 p.m. GMT (10:30 a.m. EDT) and feature senior HR leaders from Hilton and Syndio. Together we'll explore how CHROs are using AI to drive smarter pay decisions, manage regulatory risk, and strengthen workforce trust. Register now.
About the Author
Orianna Rosa Royle
By Orianna Rosa RoyleAssociate Editor, Success
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Orianna Rosa Royle is the Success associate editor at Fortune, overseeing careers, leadership, and company culture coverage. She was previously the senior reporter at Management Today, Britain's longest-running publication for CEOs. 

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