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The Thinking Machine: Jensen Huang, Nvidia, and the World's Most Coveted Microchip

Shows how Jensen Huang turned a maker of graphics cards for gamers into the company whose chips run modern AI. It also covers the leadership style and the risks that came with that success.

Table of Content

Most people think of artificial intelligence as software, yet the machines behind it run on a chip first built for teenagers playing shooting games. In The Thinking Machine, journalist Stephen Witt tells how Jensen Huang turned Nvidia, a maker of graphics cards, into the supplier of the computing power behind tools like ChatGPT. The story turns on one stubborn choice. For years Huang poured money into academic research that earned almost nothing, and he let gaming sales pay the bill.

That bet put Nvidia among the world’s three most valuable companies. It also left the company leaning on one combative man and on factories on one contested island. The story runs from a Kentucky boarding school to a record earnings call. Along the way it shows how a long-shot bet becomes an industry, what kind of leader makes that happen, and which risks the winner would rather not see.

A ten-year-old who barely spoke English was sent alone to a rough school in rural Kentucky by mistake. What he did there explains a great deal about the company he would later build.

Three engineers, one rejected idea and a series of late meetings at a roadside diner. The way they split the work, and the bar Huang set before saying yes, still holds lessons for anyone starting something risky.

Nvidia’s first chip sold well, then became useless almost overnight because of a decision made in another company’s office. With 35 engineers left, Huang chose a gamble that could have ended everything.

Chips built to draw explosions for teenagers turned out to solve a problem AI researchers had struggled with for decades. Huang spotted it early, then spent years on a project that lost money.

A quiet student in Toronto, a demo that named dog breeds, and a Google team that walked out. Each step pulled Nvidia from the gaming aisle to the center of the AI race.

In one day, Nvidia gained more market value than Coca-Cola is worth. Witt looks past the celebration and finds two weak points that no amount of profit can fix.

Nvidia’s machines now draw as much power as whole homes, and some of AI’s own pioneers fear where it leads. When the author asked Huang about it, the answer came at full volume.

The Thinking Machine is the portrait of a bet and of the man who would not let go of it. Nvidia never set out to power artificial intelligence. It set out to sell faster graphics cards, and by solving parallel computing for games it built the very machine scientists were waiting for. What turned that accident into an industry was Huang’s refusal to abandon CUDA through its money-losing years, while gamers covered the cost.

That refusal has a darker side. Nvidia has no successor and one essential supplier on a contested island. Its power demands keep rising, and its leader shouts down doubt. That makes the company strong and exposed at the same time.

The story carries lessons into ordinary work. Look at what your profitable product could fund that nobody is paying for yet. When a launch fails, as the NV1 did, cut hard and commit to one fast bet. Keep people close who can tell you that you are wrong without fearing your temper.

Huang started on a salary of $28,700. Decades later, his company gained $277 billion in value in a single day. He refuses to take one question seriously: whether the machine he built ends up serving us or outrunning us.

About this book

What is this book about?

In the early 2000s, Nvidia was a name most people knew only from gaming. Its graphics chips sat in glowing see-through PC cases. Two decades later, those same chips power the machine learning behind tools like ChatGPT, and Nvidia ranks among the most valuable companies on Earth. Stephen Witt explains how that happened. His answer centers on Jensen Huang. Huang was a bullied immigrant boy in rural Kentucky who grew into a famously intense founder. He nearly lost his company when its first chip became obsolete. He saved it with a risky all-in bet. Then, for years, he kept funding CUDA, a way to turn gaming chips into scientific supercomputers, even though it lost money. Gamers paid the bill until AI researchers in Toronto proved what the hardware could do. Witt follows the story to Nvidia's record earnings in 2024 and then looks at the weak points: a company with no successor to Huang, a dependence on factories in Taiwan, soaring electricity use, and a leader who waves away fears about AI. Readers get the story of how a long-shot bet becomes an industry, and a clear view of what it costs.

Book Information

Rating:

Genre:

Entrepreneurship & Startups, Technology & the Future

Topics:

Artificial Intelligence, Innovation, Leadership

Publisher:

Penguin Random House

Language:

English

Narrator:

Cole

First published:

April 8, 2025

Pages:

272

Length:

16 min 06 sec

Get the book:

Amazon

Who it's for

  • Founders and business operators

    Founders and operators who want to see a company survive a failed launch and bet years ahead of its market.

  • Professionals needing AI context

    Professionals in tech, finance or policy who need to understand why one chipmaker sits at the center of AI.

  • Curious about the CEO

    Ambitious readers curious about the drive, and the temper, behind a famous CEO.

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About the Author

Stephen Witt

Stephen Witt is an American journalist and non-fiction author, born in 1979, with degrees in mathematics and journalism. He worked in economic development and the stock market before writing full time. His book How Music Got Free, a history of the mp3, was a finalist for the Financial Times and McKinsey Business Book of the Year Award and was adapted into a Paramount Plus documentary. He writes business and technology profiles for The New Yorker and lives in Los Angeles.

Ratings & Reviews

Ratings at a glance

4.7

Overall score based on 40 ratings.

What people think

Listeners find the book exceptionally easy to follow, with one highlighting how it simplifies advanced technical topics. Beyond that, the work is thoroughly researched and stands as a top-tier biography; one listener defines it as an absorbing trek through generative AI. They also praise the superior writing quality and how entertaining the narrative is.

Top reviews

Emily

Wow, Stephen Witt has managed to turn the dry, often impenetrable world of semiconductor manufacturing into a propulsive narrative that feels almost cinematic. I was struck by how accessible he makes the transition from the gaming-focused NV1 chips of the 1990s to the world-dominating H100s of today. The research is clearly exhaustive, capturing the high-stakes atmosphere of the 1995 graphics card wars with impressive clarity. While the book leans heavily into Jensen Huang’s unique personality, it never feels like a dry corporate history. Witt’s prose is sharp and fast-paced, ensuring that even the technical explanations of parallel processing don't bog down the flow. Personally, I found the anecdote about the 'Wrath of Huang' to be the highlight, showing the raw intensity driving NVIDIA’s success. It’s a rare tech biography that balances deep-dive engineering details with genuine entertainment value. Highly recommended for anyone trying to understand the silicon foundation of our current AI moment.

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Hazel

Finally got around to reading this after hearing so much buzz about Witt’s investigative skills, and he certainly delivers on the hype. The Thinking Machine isn't just a biography of a man; it’s a fascinating journey into the very heart of the generative AI explosion. Witt’s ability to explain parallel processing using clear metaphors makes the technical hurdles NVIDIA faced feel visceral and exciting. I was particularly fascinated by the story of how a small group of renegade engineers defied Wall Street to bet everything on a software-first future. The book moves at a breakneck speed, occasionally skipping over the darker implications of the technology to maintain its propulsive energy. Truth is, even if you aren't into computers, the human drama behind the corporate veil is worth the price of admission. It’s easily one of the most engaging business books I’ve read in years.

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Thongchai

Not what I expected from a standard tech biography, as Witt brings a level of literary flair that you rarely see in this genre. The prose is punchy and the anecdotes—especially the one about the AI-dispatched janitors—are both fascinating and slightly chilling to contemplate. I loved the deep dive into the 'family business' connection between Huang and AMD’s Lisa Su, which adds a personal layer to the corporate rivalry. Witt’s research is impressive, and he manages to make the birth of neural networks feel like a revolution happening in real-time. Sure, a few of the middle chapters felt like a mandatory checklist of product launches that slowed the pace. However, the overall narrative arc is so strong that it’s easy to overlook those minor lulls. It’s a brilliant look at how serious people doing serious work ended up changing the world forever.

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Suthinee

This book is a fascinating journey through the history of AI, framing the development of the GPU as the catalyst for everything we see today. Witt’s writing is sharp and frequently witty, making even the discussion of atmospheric layers and climate simulations feel urgent. I was impressed by how he traced the evolution from 3.5-inch floppies to the massive energy-hungry supercomputers of the modern era. The narrative does an excellent job of showing that NVIDIA’s success wasn't just luck, but a result of breaking Moore’s Law through sheer architectural will. Look, some might find the focus on Jensen’s personality a bit much, but it’s hard to deny his impact on the world. It’s a well-paced, entertaining book that manages to be both a biography and a technical history at once. Truly a great read for tech enthusiasts and casual readers alike.

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Jirapat

Gotta say, Stephen Witt has followed up his work on the music industry with another absolute winner here. The Thinking Machine captures the propulsive energy of a company that is currently redefining what it means to be human. I found the stories of the early renegade engineers particularly inspiring, showing that even in a world of giants, a small team with a radical vision can win. The book is impressively researched and handles the 'alignment problem' and AI safety debates with a balanced, if slightly skeptical, hand. Witt’s prose is consistently engaging, making the 30-year history of a chip company feel like a high-stakes adventure. Admittedly, the final chapters get a little defensive regarding the author's relationship with the CEO, but it doesn't take away from the overall quality. If you want to understand the machines that are currently eating the world, start here.

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Niramai

Ever wonder how a niche company that made video game hardware managed to become one of the most valuable entities on the planet? Witt answers this by tracing NVIDIA’s history from its origins to its current status as the backbone of generative AI. The book is well-researched and avoids the typical jargon that makes most tech books unreadable for a general audience. I particularly enjoyed the sections on how CUDA became the 'secret sauce' that rivals simply couldn't replicate. Frankly, the narrative gets a bit bogged down in product launch specifics toward the middle, but the momentum picks back up quickly. Seeing the connection between early neural nets like 'Jellyfish' and today’s massive clusters provides a great sense of perspective. It’s an essential read for anyone following the AI revolution, even if you don't know your CPU from your GPU.

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Narongrit

As someone who has followed the industry since the days of 3dfx and Matrox, I appreciated how Witt captures the chaotic energy of the early 90s hardware market. This isn't just a dry list of specs; it’s a story about a stubborn entrepreneur who refused to play by the established rules of Silicon Valley. The book does a stellar job of explaining why NVIDIA’s bet on CUDA was the most consequential gamble in modern computing history. From my perspective, most tech biographies fail to explain the 'why' behind the success, but Witt nails it here. My only real gripe is that the ending felt a bit passive-aggressive regarding the author's final interactions with Jensen. Still, the writing quality is top-tier and the historical context provided is invaluable for understanding our current tech landscape. It manages to be both informative and genuinely fun to read.

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Montri

Picked this up on a whim and was immediately sucked into the story of how NVIDIA almost went bankrupt multiple times before striking gold. Witt has a gift for making high-tech subjects accessible without dumbing them down too much for the experts. I particularly enjoyed the sections describing the visceral tension in the boardroom during the early years. The book highlights how NVIDIA isn't just a hardware company, but a software powerhouse that has successfully locked in its customers through CUDA. Gotta say, the description of Jensen’s refusal to engage with science fiction perspectives was one of the most revealing moments in the entire book. It explains a lot about the current 'full steam ahead' culture of AI development. It’s a compelling, fast-paced read that serves as a great primer for anyone curious about the companies shaping our digital lives.

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Tun

The chapter on the NV1 launch in 1995 was a fun trip down memory lane, but I found the author’s tone a bit too reverent toward Jensen Huang at times. While Witt is a fantastic writer, there’s an air of hagiography here that makes some sections feel more like a tribute than a rigorous analysis. He touches on the 'sci-fi' nature of AI, yet he mostly stays on the surface rather than interrogating the potential for a monopoly. Look, the book is incredibly readable and the reporting is clearly high-quality, but I wanted more critical pushback on the environmental costs of these massive data centers. To be fair, the interview scenes where Huang loses his temper are gold and offer a rare, unvarnished look at a billionaire CEO. It’s a good starting point for history, though I wouldn't call it the definitive word on the ethics of the industry.

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Teng

Frankly, while the reporting in this book is incredibly thorough, I left feeling like it glossed over the most important questions about our future. Witt spends a lot of time on the 'visionary' aspect of Jensen Huang while only dedicating a tiny fraction of the text to the dangers of monopoly power. We need books that question the system, not just polish the throne of the latest billionaire. The technical history of GPUs and parallel processing is well-explained and undeniably interesting, especially for those who lived through the PC gaming boom. However, the author seems more interested in the 'Wrath of Huang' than the structural forces that allow one company to control the future of intelligence. It’s a very readable, entertaining book, but it lacks the critical edge I was hoping for. A solid history, but a bit too uncritical for my tastes.

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Questions about this book

It is a biography of Jensen Huang and the story of Nvidia. Witt traces Huang from a rough Kentucky boarding school to co-founding Nvidia, nearly losing it when the NV1 chip became obsolete, and saving it with the Riva 128. He then shows how Huang kept funding CUDA, which turned gaming chips into scientific supercomputers. That made Nvidia’s hardware the backbone of modern AI.

Nvidia’s gaming chips solved parallel computing, running many calculations at once, which is exactly what neural networks need. A Stanford student, Ian Buck, showed scientists could borrow the chips for heavy computation, and Huang hired him to help build CUDA in 2006. Years later, Alex Krizhevsky in Geoffrey Hinton’s Toronto group used CUDA and Nvidia GPUs to build AlexNet, and the machine learning boom followed.

Witt points to four. Huang has no successor or second-in-command, so the company depends heavily on one person. Nvidia relies on TSMC in Taiwan, which is vulnerable to pressure from China. Its chips drive a sharp rise in electricity use and emissions. And Huang dismisses fears about AI’s threat to humanity, while other executives may be too afraid of his temper to challenge him.

Witt’s story shows that a profitable core business can fund a long bet nobody else will pay for, as gaming sales funded CUDA. When the NV1 failed, Huang cut deep and went straight to production using an emulator instead of prototypes. The book also warns that a leader who shouts down disagreement can leave a company with no one willing to raise risks.

It suits founders and operators interested in how a start-up survives near-collapse and bets ahead of its market. It also serves professionals who want to understand why one chipmaker became central to AI, cloud computing and cryptocurrency mining. Readers curious about Silicon Valley leadership get a candid portrait of Jensen Huang, including his public outbursts.

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The Thinking Machine

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