The Nvidia Way Quotes

“employees more space for more critical, high-level work. Employees will have a virtual assistant, almost like a brilliant intern with near-perfect memory, capable of instantly recalling any piece of knowledge stored on computers and the internet. Instead of simple file retrieval, the models can generate smarter insights drawn from the entire pool of a company’s internal data.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Structural prediction and protein design, once considered impossible problems, are now solvable. Grigoryan explains that the complexity of a protein and its possible states surpasses the number of atoms in the universe. “Those numbers are extremely challenging for any computational tools to deal with,” he said. But he believes a skilled protein biophysicist can examine a particular molecular structure and deduce its potential functions, suggesting there may be learnable general principles in nature—exactly the sort of operation that a “universal prediction engine” such as AI should be able to figure out. Generate:Biomedicines has applied AI to examine and map molecules at the cell level, and Grigoryan sees the potential to extend the same technique to the entire human body. Simulating how the human body will react is orders of magnitude more complicated, but Grigoryan thinks it will be possible. “Once you see it working, it’s hard to imagine it doesn’t just continue,” he said, referring to the power of AI.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“People with very high expectations have very low resilience. Unfortunately, resilience matters in success,” he later said. “Greatness is not intelligence. Greatness comes from character.”17 And character, in his view, can only be the result of overcoming setbacks and adversity. To Jensen, the struggle to persevere in the face of bad, and often overwhelming, odds is simply what work is. It is why, whenever someone asks him for advice on how to achieve success, his answer has been consistent over the years: “I wish upon you ample doses of pain and suffering.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“I don’t actually know anybody who is incredibly successful who just approaches business like, ‘This is just business. This is what I do from 8 to 5, and I’m going home, and at 5:01, I’m shutting it down,’ ” Jensen has said.15 “I’ve never known anybody who is incredibly successful like that. You have to allow yourself to be obsessed with your work.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“The Transformer was a big deal,” Jensen said in 2023. “The ability for you to learn patterns and relationships from spatial as well as sequential data must be an architecture that’s very effective, right? And so I think on its first principles, you can kind of think Transformer’s going to be a big, big deal. Not only that, you could train it in parallel and you can really scale this model up.”7”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“According to Jeff Fisher, Nvidia’s approach involves “no magic.” It’s just hard work and ruthless efficiency, all in the service of maintaining competitive advantage. And everyone who works with Nvidia must embrace it, not just its internal teams.4 Everything the tiger teams did was expensive and resulted in a drag on the bottom line. Yet Nvidia has always been willing to use its financial resources to invest in critical parts of the business—even when that has meant other companies’ business.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Do your job. Don’t be too proud of the past. Focus on the future.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Jensen’s at-times harsh approach was a deliberate choice. He knew that people would inevitably fail, especially in a high-pressure industry. He wanted to offer employees more opportunities to prove themselves, believing that they, in every case, are often just one or two epiphanies away from solving their problems themselves. “I don’t like giving up on people,” he said. “I’d rather torture them into greatness.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“I FOUND THIS TO BE A pervasive attitude within Nvidia: that the culture of the place discourages looking back, whether at errors or successes, in favor of focusing on the future—the blank whiteboard of opportunity.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Jensen himself has called AI a “universal function approximator” that can predict the future with reasonable accuracy. This applies as much in “high-tech” fields such as computer vision, speech recognition, and recommendations systems as it does in “low-tech” tasks such as correcting grammar or analyzing financial data. He believes that eventually it will apply to “almost anything that has structure.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Notably, all eight Google scientists who authored the seminal “Attention Is All You Need” paper on the Transformer deep-learning architecture—which proved foundational for advancements in modern AI large language models (LLMs), including the launch of ChatGPT—soon after left Google to pursue AI entrepreneurship elsewhere. “It’s just a side effect of being a big company,” said Llion Jones, one of the coauthors of the Transformer paper.4 “I think the bureaucracy [at Google] had built to the point where I just felt like I couldn’t get anything done,” he added, expressing frustration with his inability to access resources and data.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Nvidia doesn’t constantly fire people and rehire them,” said Jay Puri, head of global field operations.12 “We take people that we have and we are able to redirect them into a new mission.” Managers at Nvidia were trained not to get territorial or feel like they “own” their people and instead got used to them moving around between task groups. This practice removed one of the main sources of friction at large companies. “Managers don’t feel like they get power by having large teams,” Puri continued. “You get power at Nvidia by doing amazing work.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Keane was also surprised by the sheer openness he found at Nvidia. He joined at the general-manager level and was allowed to attend every board meeting and off-site board event. When a typical CEO would have eight or nine people in a room for big executive meetings, Jensen would have a packed house. “Everyone could hear what he was telling the executive staff,” Keane said. “It kept everybody in sync.” When there is important information to share or an impending change in the direction of the business, Jensen says he tells everybody at Nvidia at the same time and asks for feedback. “It turns out that by having a lot of direct reports, not having one-on-ones, [we] made the company flat, information travels quickly, employees are empowered,” Jensen said. “That algorithm was well conceived.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“It was imperative that both groups work in close harmony. “Any computer architecture has a software side and a hardware side. CUDA is not just a piece of software,” said Andy Keane, a former general manager for Nvidia’s data-center business. “It’s a representation of the machine. It’s a way you access the machine, so they have to be designed together.”5”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“The hardware engineer replied, “We don’t think it’s a big deal. It’s kind of untested.” The developer-relations employee was aghast. “What are you talking about? ATI is shipping this feature in a product already, and gamers love it.” Once again, Nvidia’s own engineers seemed to be unaware of what the market wanted. “NV30 was an architectural disaster. It was an architectural tragedy,” Jensen later said.11 “The software team, the architecture team, and the chip-design team hardly communicated with each other.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Vivoli knew that graphics demos would have the most impact if Nvidia had a thorough understanding of its audience. Earlier demos were targeted at engineers, which is why they showed off the specific features and capabilities of Nvidia’s new chips. Like the 3-D cube that Voodoo Graphics impressed the Hambrecht & Quest conference with in 1996, such demos were only impressive if you knew the computations that were occurring “under the hood.” A nonengineer wouldn’t necessarily know what he or she was looking at. So Vivoli changed the focus of demos away from a cold demonstration of graphics performance—the visual equivalent of reading a list of benchmark metrics—and gave them a sentimental side.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Within just a few years, Nvidia’s success in graphics made it one of TSMC’s top two or three customers. Tsai remembered Jensen would negotiate hard over pricing and would repeatedly cite how the graphics company had only a 38 percent gross margin. One particular dispute prompted Tsai to travel to California and meet with Jensen at a restaurant that wasn’t much better than Denny’s. “We tried to resolve the dispute. I forgot the details,” Tsai said. “But it really hit me. Jensen taught me his philosophy of doing business called ‘rough justice.’ ” Jensen explained that “rough” meant the relationship was not flat but rather had ups and downs. Justice was the important part. “After a certain period of time, let’s say a few years, it would net out to roughly equal.” To Tsai, this was a way of describing a win-win partnership, though one that acknowledged there wouldn’t be a win-win every single time. Sometimes one side would get the better of a specific deal or incident, and the next time it would be the other side. As long as it was roughly 50-50 after a few years—not 60-40 or 40-60—it was a positive relationship. He remembers thinking Jensen’s approach made a great deal of sense.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“While some Nvidia employees were initially worried about the lawsuit, Andrew Logan, Nvidia’s director of corporate marketing, was excited. “I got a call from the Wall Street Journal right now on my voicemail,” he told his colleagues after the lawsuit was announced. “This is perfect. We’re on the map!”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“When those former 3dfx engineers arrived at Nvidia, they expected to find out that their victorious rival had some kind of unique process or technology that allowed them to make new chips every six months. Dwight Diercks remembers their shock when they found out that the explanation was much simpler. “Oh my God, we got here and we thought there was going to be a secret sauce,” one engineer said.3 “It turns out it’s just really hard work and intense execution on schedules.” It was Nvidia’s culture, in other words, that made the difference.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Nvidia’s rapid iteration meant that “the competition will always be shooting behind the duck,” as Jensen described it. Like a hunter who aims at a moving target instead of ahead of it, other graphics-chip makers would lag behind—there would be too many new chips coming out too fast. Nvidia’s competitors would simply be overwhelmed. “The number one feature of any product is the schedule,” Jensen later said.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Priem’s design had a software-based “resource manager,” essentially a miniature operating system that sat on top of the hardware itself. The resource manager allowed Nvidia’s engineers to emulate certain hardware features that normally needed to be physically printed onto chip circuits. This involved a performance cost but accelerated the pace of innovation, because Nvidia’s engineers could take more risks. If the new feature wasn’t ready to work in the hardware, Nvidia could emulate it in software. At the same time, the engineers could take hardware features out when there was enough leftover computing power, saving chip die area.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Chris Malachowsky came to the rescue once more. “Why don’t we test every chip and run software on every part?” he asked one day. “You can’t possibly do that,” another Nvidia executive replied. “Why?” asked Malachowsky.15”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“DURING ONE OF NVIDIA’S VERY FIRST board meetings, director Harvey Jones, a former CEO of a leading chip-design-software company called Synopsys, asked Jensen about the NV1: “How would you position this?” At the time, Jensen didn’t realize that Jones was not merely asking about the NV1’s feature set or product specifications. He was asking him to consider how Nvidia would sell the new chip in a highly competitive industry. He knew that products had to be presented in the clearest, most precise terms in order to stand out. “He asked me a simple question. I had no idea how simple it was. It was impossible for me to answer because I didn’t understand it,” Jensen remembered.11 “The answer is supremely deep. You’ll spend your whole career answering that question.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“We thought we had built great technology and a great product,” Malachowsky said. “It turns out we only built great technology. It wasn’t a great product.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Nobody goes to the store to buy a Swiss Army knife. It’s something you get for Christmas.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Nvidia remains the only stand-alone graphics-chip firm to this day, even though hundreds of others have thrown their hats in the ring. Jensen himself is now the technology industry’s longest-serving CEO.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“Current AI models can now understand requests via context and because they can grasp natural conversational language. It is a major breakthrough. “The core of generative AI is the ability for software to understand the meaning of data,” Jensen said.16 He believes that companies will “vectorize” their databases, indexing and capturing representations of information and connecting it to a large language model, enabling users to “talk to their data.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“And that’s not even close to the most expensive Nvidia product. Nvidia’s latest server rack system as of this writing, the Blackwell GB200 series, was specifically designed to train “trillion-parameter” AI models. It comes with seventy-two GPUs and costs $2 million to $3 million—the most expensive Nvidia machine ever made. The company’s top-end-product pricing isn’t merely increasing; it is accelerating.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“The “Top 5” e-mails became a crucial feedback channel for Jensen. They enabled him to get ahead of changes in the market that were obvious to junior employees but not yet to him or his e-staff. “I’m looking to detect the weak signals,” he would tell his employees when asked why he liked the Top 5 process. “It’s easy to pick up the strong signals, but I want to intercept them when they are weak.” To his e-staff, he was a little more pointed. “Don’t take this the wrong way, but you may not have the brainpower or the wherewithal to detect something I think is pretty significant.”15”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant

“So Jensen asked employees at every level of the organization to send an e-mail to their immediate team and to executives that detailed the top five things they were working on and what they had recently observed in their markets, including customer pain points, competitor activities, technology developments, and the potential for project delays. “The ideal top five e-mail is five bullet points where the first word is an action word. It has to be something like finalize, build, or secure,” said early employee Robert Csongor.”
― Tae Kim, The Nvidia Way: Jensen Huang and the Making of a Tech Giant