A closer look

"The Journey of Jensen Huang"

Waking up this morning, news about Jensen Huang has already flooded the screens. Coincidentally, just as AI tech stocks are experiencing violent volatility and Wall Street is constantly questioning the AI bubble, the most representative figure of the global AI industry has once again been pushed to the center of the storm.

Having previously read "The Thinking Machine" by Stephen Witt, I had some understanding of Jensen Huang's experiences. Today I suddenly wanted to look back and see how this 63-year-old man actually walked step by step to where he is today.

In 1963, Jensen Huang was born in Taiwan, lived in Thailand during his childhood, and was later sent to the United States by his parents. In his youth, he worked in a restaurant, graduated from high school at 16, and entered Oregon State University to study electrical engineering. There, he met Lori Mills, the wife who would accompany him for over forty years.

At the time, Jensen Huang was in his teens, and Lori was two years older than him; the two were assigned as lab partners. He later recalled that he looked like a 12-year-old child at the time, and wanting to pursue a girl, he could only rely on academic grades to attract her. Thus, he invited Lori to do homework together every week, and even completed the problems in advance so as to appear a bit smarter in front of her. 😂 Later, the two really got together. When Jensen Huang was young, he also told Lori that he would definitely become a CEO before he was 30. The two married about five years after they met.

Lori herself was also a chip engineer, working in Silicon Valley in her early years, and her income was even higher than Jensen Huang's. Later, she left the workforce and took on more responsibility for the family and the upbringing of their two children. Jensen Huang continued to work, pursued a master's degree at Stanford, and eventually embarked on the path of entrepreneurship.

In 1993, Jensen Huang founded NVIDIA with Chris Malachowsky and Curtis Priem, fulfilling the promise he made to Lori back then. But NVIDIA did not initially do any AI; instead, it did gaming graphics chips. The early product NV1 encountered setbacks, and the company was once on the brink of bankruptcy. It wasn't until the success of RIVA 128 in 1997 that NVIDIA gradually gained a firm foothold. In 1999, GeForce 256 was released, and NVIDIA began to establish its position in the GPU market.

What truly changed NVIDIA's fate was Jensen Huang's subsequent long-term investment in GPU general-purpose computing. In 2006, NVIDIA launched CUDA, allowing developers to use GPUs for general-purpose parallel computing. Who could have thought at the time that graphics cards, originally mainly used for playing games, would one day become the core computing power for AI training?

Speaking of GPUs, I also remember those mining graphics cards in Huaqiangbei back in the day. 😂 Later, the rise of cryptocurrency mining once drove GPU demand. However, Bitcoin mining subsequently shifted gradually toward ASIC, while GPU mining concentrated more on other cryptocurrencies.

The truly powerful part of CUDA is not mining, but the software ecosystem NVIDIA built around the GPU. Development tools, compilers, mathematical libraries, scientific computing, and deep learning frameworks—NVIDIA has been investing continuously. Even when no significant commercial return was visible at the time, Jensen Huang did not give up. In 2012, AlexNet achieved a breakthrough in the field of deep learning, and the value of GPU-accelerated training began to be recognized by more and more people. In 2022, ChatGPT ignited generative AI, and NVIDIA's years of investment finally met with an explosion.

Looking back, the most impressive thing about Jensen Huang is not just that he made NVIDIA into a tech giant, but that he saw the potential of GPUs beyond graphics computing very early on and was willing to invest continuously in this direction for over ten years. For the past few decades, computers have mainly relied on CPUs to execute general tasks. In the AI era, the demand for large-scale matrix operations and parallel computing has risen sharply, and the GPU has become one of the core computing engines.

NVIDIA has also long ceased to be a company that simply sells graphics cards; GPU, CPU, NVLink, InfiniBand, Ethernet, CUDA, and then a whole AI computing system have gradually formed a massive hardware and software ecosystem.

As someone who has worked in the supply chain for over ten years, my feeling toward this transformation may be more direct. From TSMC's advanced processes and CoWoS advanced packaging, to HBM from SK Hynix, Samsung, and Micron; from optical communications and high-speed networking to servers, liquid cooling, power, and data center construction, the entire industry chain has been driven forward. Previously, when we talked about the semiconductor cycle, we focused more on consumer electronics, PCs, mobile phones, and server demand. Now, AI brings not only growth in chip demand but also involves the upgrade of the entire computing architecture, storage, networking, packaging, and power supply systems. Several tech giants invest massive capital expenditures every year; behind this is the expansion, R&D, equipment procurement, and capacity layout of a large number of global suppliers. AI is no longer just a competition of software and algorithms, but a global industrial competition involving energy, manufacturing, infrastructure, and capital investment.

For ordinary people, AI is also changing work and life. Writing code, searching for information, researching drugs, analyzing data, and even future robots and automated production may all be affected. Of course, this technical revolution was not completed by Jensen Huang alone. Researchers, cloud vendors, open-source communities, chip design companies, wafer fabs, and the entire supply chain all made irreplaceable contributions. But Jensen Huang indeed is one of the important drivers; his persistence in GPU general-purpose computing and the software ecosystem NVIDIA built over the long term have profoundly influenced the development direction of the global computing industry.

Looking back at his story with Lori, from two young people in a college lab, to a Silicon Valley engineer couple, then to the founding of NVIDIA, nearing bankruptcy, the long investment in CUDA, and today's AI empire. For over forty years, Lori witnessed almost every important stage of his life and bore much for the family.

Precisely when NVIDIA is at its most glorious and Jensen Huang's personal prestige has reached its peak, he publicly admitted to an extramarital affair. On November 8, through NVIDIA's official channels, Jensen Huang apologized to his wife, family, employees, and shareholders, admitting his infidelity to his wife and stating his willingness to take responsibility.

On the same day, the NVIDIA board announced the launch of an independent investigation to review reports regarding Jensen Huang becoming a target of foreign intelligence activities. The board stated that there is currently no reason to believe that national security or company secrets have been compromised, while reaffirming their confidence in Jensen Huang and the management team. The investigation has not yet ended, and relevant allegations cannot be taken directly as facts.

What makes me most emotional about this is still Lori. Two people walked the path from youth to today, and she gave a lot for this family. For such a thing to happen now is indeed sigh-inducing. But I still feel that making a mistake and contributing to the AI industry should be viewed separately.

Jensen Huang spent over thirty years leading a graphics chip company that was once on the brink of bankruptcy to the center of the global AI industry. GPU accelerated computing, the CUDA software ecosystem, and the AI infrastructure construction pushed by NVIDIA have had a profound impact on the global semiconductor industry. These contributions will not cease to exist because of his personal mistakes. Similarly, no matter how great the achievements in career, they cannot become a reason to evade personal responsibility.

From an investment perspective, Jensen Huang's personal influence is indeed great, but NVIDIA's competitiveness today no longer relies solely on him. The CUDA ecosystem, R&D teams, product roadmaps, customer relationships, and supply chain systems are all accumulated over decades.

In the short term, the market may continue to fluctuate due to valuation pressure, AI capital expenditures, financing risks, and this incident. But I still am optimistic about the long-term development of AI, and I do not believe that one person's private turmoil can change the technical direction of the entire industry. Of course, technical development and stock returns are two different things. Even the best company may undergo a significant adjustment because of an overly high valuation.

Looking back at the journey of Jensen Huang, from that inconspicuous young man back then to the entrepreneur today driving the transformation of the global computing industry, it truly makes one feel emotional.

Merits are merits, faults are faults! One cannot use his achievements to excuse him, nor is there a need to deny his contributions to the AI industry because of his mistakes...

$NVDA

Reference materials: Stephen Witt "The Thinking Machine", NVIDIA official history, The New Yorker profile interview, NVIDIA official statement on November 8, 2026.