Revisiting Nvidia: The Absolute Leader in Artificial Intelligence, Data Center, and Graphics


Nvidia discussion in my books

I have discussed the company Nvidia (ticker:NVDA) in two recent books; including:

In my book “The Rules of Super Growth Stocks Investing“:

  • Section 3-3, pp. 190-191

In my book “The Rules of 10 Baggers“:

  • Section 1-1, pages 23-24
  • 5-6, pages 242-246, an entire subsection dedicated to this company
  • Section 6-2, pages 282-285
  • Section 7-1, pp. 348-285

Please read my articles “How does nVidia make money, Nvidia is changing the gaming rules” and “The reasons for Nvidia’s monopoly and the challenges it faces“, then come back and read this article, so that you can have a basic understanding of Nvidia (ticker: NVDA).

Why is this company important?

A leader in most technology fields

Nvidiacan be said to be the absolute leader in the hottest major technological fields of our time: artificial intelligence, data center, self-driving car, metaverse, cryptocurrency mining, and professional computer graphics. If Nvidia claims to be the second, no other peers dare to say that they are the first.

A must for Artificial intelligence

Stocktwits’ Khanna sees chip giant Fidelity as one beneficiary of this AI boom. He noted that Nvidia’s specialized AI chips account for the majority of this high-end AI market.

Nvidia’s stock price has risen 85% this year, and it is on track to record the largest quarterly increase in more than 20 years. Nvidia stock, which lost its luster as the stay-at-home economy cooled last year, is back in the favour, with analysts touting the chipmaker’s unique potential for artificial intelligence.

“Artificial intelligence requires a new computing platform; with the help of OpenAI, Microsoft and Nvidia are early leaders in building such a computing platform,” Oppenheimer analyst Timothy Horan wrote in a research note to clients this week. It is also an excellent partner.” Horan said: “Nvidia has an enviable market position. The company’s graphics processing unit (GPU) is recognized as an industry-leading level. With the help of a large number of artificial intelligence software stacks, these CPUs will be in the field of cloud computing. Gain market share in the AI wallet/computing business.”

Nvidia sell picks and shovel

There are plenty of other AI-centric companies out there to choose from, so why Nvidia? The company is a picks-and-shovels play, which got its name from a famous quote attributed to Mark Twain: “During the gold rush, it’s a good time to be in the pick and shovel business.”

In the current situation where artificial intelligence is hot; artificial intelligence is gold, and Nvidia is the picks and shovels business. 

What about market share?

At present, Nvidia is the undisputed leader in the artificial intelligence chip market. Omdia estimates that its share of such AI processors will be about 80% as of 2020. AMD is the second largest player in the GPU industry with about 20% market share. Intel’s share is less than 1%.

Moreover, Nvidia takes 95% of the market for graphics processors that can be used for machine learning, according to New Street Research!

Company introduction

Regarding Nvidia, interested readers can refer to my detailed introduction on pages 242-246 in sections 5-6 of the book “The Rules of 10 Baggers“; and the following descriptions of my articles:

Hardware infrastructure


In the past 20 years, Nvidia has maintained a stable market share of about 80% in Nvidia’s graphics chip GPU market, which is beyond the reach of AMD and Intel. This is not only the case in the general consumer graphics chip market, but also in the professional graphics chip market, which is almost monopolized.


Jensen Huang, CEO of Nvidia, said, “Our GPU supports the world’s largest distributed supercomputing, which is why it is very popular in the field of cryptocurrency.” GTX 1060 3GB and P106, P104 professional mining cards.

Benefiting from the “mining boom”, Nvidia’s fiscal year 2018 revenue reached a new high of US$9.7 billion, of which game chip revenue including mining cards reached US$5.5 billion, accounting for more than 50%. Nvidia’s market value is also soaring, rising from $14 billion in 2016 to a high of $175 billion in 2018, more than tenfold in two years.

However, marked by the merger of Ethereum in 2022, the era of mining has finally come to an end. When ChatGPT caught fire, Nvidia CTO Michael Kagan also began to conclude that cryptocurrencies are useless to society, and GPU and computing power should be used to develop AI that is more beneficial to society, such as ChatGPT.

GPU is not just for drawing and displaying

The graphics chip GPU was found to be used in artificial intelligence systems to accelerate data training. This change has been the main reason for the increase in Nvidia’s stock price in the past decade.

Things didn’t stop there. Nvidia has applied graphics chip GPU technology to many fields such as autonomous driving, virtual currency, and metaverse, and has also achieved great success, and Nvidia has also become a leading manufacturer in these fields.

More importantly, Nvidia has successfully changed the hardware computing world dominated and defined by Intel for nearly half a century. You can see everything by looking at the rise and fall of the stock prices of these two companies in the past ten years. Jensen Huang, CEO of Nvidia, is so far the only opinion leader who dared to say that Moore’s Law for semiconductors proposed by Intel is dead. Jensen Huang then proposed “Huang’s Law”, that is: GPU performance doubles every 6 months. Compared with Moore’s Law, the performance doubles every 18 months, which is 3 times faster.

He does qualify because he did it. Nvidia has successfully turned GPU into a general-purpose chip; this is to seek accelerated computing, that is, to use special equipment to reduce the burden and speed up the computing work of the CPU. The specific implementation is to pile up computing power and build graphics cards to process images. That is to do GPU.

Artificial intelligence system

There is no doubt that Nvidia is the largest hardware manufacturer in the field of artificial intelligence. Its data center systems, GPU chips, and software, which are necessary in the field of artificial intelligence, have a market share of about 80%, and other peers cannot compete with it.

It is not an exaggeration to say that Nvidia is the basic weapon that all manufacturers that want to enter the field of artificial intelligence must purchase, and even has monopolized the computing power of data centers and artificial intelligence around the world; because enterprises do not have many Choices at all.

In 2016, Jensen Huang, the founder and CEO of Nvidia, donated an artificial intelligence supercomputer DGX-1 to OpenAI. This is how the most basic computing resources of the currently popular ChatGPT began. Because at that time, this DGX-1 was worth more than one million, and its computing power could compress OpenAI’s one-year training time to one month.

Tencent estimated in April 2023 that “the H800 has significantly reduced the training time of the artificial intelligence system by more than half, from 11 days to 4 days.” The artificial intelligence training time of mainland chips is twice that of the United States. This is because the H800 is a reduced-level chip of H100 specially made by Nvidia for China to comply with the US semi-artificial intelligence semiconductor export regulations!

Data Centers and Artificial Intelligence

Nvidia’s A100 and H100 products are currently the “main force” that provides computing power for large models of artificial intelligence.

At present, almost all artificial intelligence companies are seeking to purchase related GPUs. Even the number of A100 and H100 owned by an enterprise has become one of the important indicators for the industry to judge the ability of large-scale models of enterprises. The prices of A100 and H100 have also gone up. According to reports from Chinese entrepreneurs, from the end of 2022 to the present, the unit price of A100 has increased by more than 50%!

The latest version of the Grace Hopper architecture H100 GPU launched by Nvidia in May 2022 adopts TSMC’s 4nm process and has 80 billion transistors. 20 cards can carry global Internet traffic, and everyone is amazed at its performance.

If the memory and performance of Grace Hopper are not enough, Nvidia has proposed a higher performance solution – DGX GH200. First connect 8 Grace Hoppers with 3 NVLINK switches at a transmission speed of 900 GB, and then connect 32 such parts together, connecting a total of 256 Grace Hopper chips. The GH200 Grace Hopper will be in full production in May 2023, and Huang Renxun described it as the world’s first accelerated computing processor with huge memory: “This is a computer, not a chip.” Designed for data center applications.

Software is outstanding

Successfully involved in software

Surprisingly, Nvidia’s performance in software also exceeds most people’s imagination. Nvidia provides customers with access or customization to enhance their platform hardware functions. The most basic CUDA library and API have long been a must-have development tool set for software engineers to perform professional graphics processing and access to Nvidia’s high-level functions. , It is the core moat that Nvidia can defeat competitors and monopolize this field, because competitors have no corresponding solutions so far.

Unlike peer Intel (ticker: INTC ), which has long been lackluster in software, it has barely helped the company’s top line at all. The three major opportunities for Nvidia Software include artificial intelligence-related software, the Omniverse platform for metaverse, virtual collaboration, and real-time simulation, and self-driving software tailored for automobile factories.


In 2006, NVIDIA launched the CUDA development platform. The tool set equipped with GPU, through CUDA programming, can allow multiple GPUs to perform parallel operations, thereby greatly improving computing performance.

In the early days, the role of the GPU was only to accelerate graphics rendering, and it was often used in the field of games. With the blessing of CUDA, the GPU broke away from the single purpose of image processing, and began to truly have the ability of general computing, and was gradually used in the deep learning of artificial intelligence.

Today, the industry has long recognized the value of CUDA. And Nvidia’s GPU with CUDA support has also become the first choice for artificial intelligence training.

CUDA can be regarded as the gospel of all high-level technology professionals. Whether you are engaged in artificial intelligence, fluid physics research, protein folding prediction, or particle simulation, you cannot do without CUDA.

Omniverse platform

Jensen Huang has repeatedly stated publicly: “The combination of artificial intelligence and computer graphics will power the metaverse, the next evolution of the Internet.”

Whether it is to construct the virtual and real scenes of the Metaverse, or to maintain the autonomous operation of the Metaverse through artificial intelligence technology, it requires the support of 3D graphics processing pipelines, artificial intelligence computing and other capabilities. Moreover, Nvidia’s Omniverse platform can also assist users to work collaboratively in the virtual world and build a digital twin world, such as designing and manufacturing cars and buildings.

Unlike other metaverse ideas, Jensen Huang regards Omniverse as “a platform that connects the 3D world to a shared virtual world.” The most amazing thing is that the documentary released later showed that Jensen Huang, who gave a speech for an hour and a half at GTC 2021, was actually a “digital version of Jensen Huang”, including the kitchen is also a “digital kitchen”, which is also based on Omniverse and digital twin technology.

Metaverse still has a long way to go, from infrastructure to terminal devices to content applications, all are in a very early stage. However, Nvidia still created a complete set of technology platforms for the metaverse, which is listed as the three major platforms along with HPC (high performance computing) and AI, which shows that it regards the metaverse as a long-term war.

Currently, Omniverse is serving approximately 700 customers, including Amazon, Siemens, Mercedes-Benz, DB Netze, DNEG, Kroger, Lowe’s and PepsiCo.

AI Enterprise Platform

Nvidia’s AI enterprise platform can be understood as a collection of tools such as pre trained language models, as well as a toolkit and programming environment for developing and optimizing proprietary GPU-based applications, including libraries and tools for machine learning, deep learning, and other AI tasks. Accordingly, Nvidia’s enterprise AI platform will likely find demand for supporting applications and tasks across industries, including conversational AI, cybersecurity, logistics, recommendation algorithms, and more.

Cloud Computing Platform Services

In terms of cloud services, Nvidia has launched the virtual graphics chip vGPU and the GeForce NOW cloud game platform very early, and is currently in the leading group in the industry.

Moreover, Nvidia has recently launched a new artificial intelligence supercomputing service – DGX Cloud cloud service. It gives businesses rapid access to the infrastructure and software needed to train advanced models for generative artificial intelligence and other groundbreaking applications.

Nvidia’s current approach is to sell data center hardware. “An AI supercomputing service that gives businesses immediate access to the infrastructure and software needed to train advanced models for generative AI and other breakthrough applications.”

A simple understanding is that through this cloud platform, users can directly call the AI computing power of Nvidia’s supercomputer DGX, instead of spending a lot of money to buy “stack” A100 and H100. Nvidia leases it to you!

Next golden goose

The general view on Wall Street is that the revenue of Nvidia’s software department in 2022 will be about 350 million to 400 million US dollars, and it is estimated that the revenue before 2030 is expected to reach billions of dollars.

According to Nvidia’s own estimate, by 2030, the potential market value of Nvidia’s software business is 300 billion US dollars.

Other advanced areas


As early as 2015, Nvidia launched its automotive business, developed and delivered self-driving chips; even Tesla has adopted its self-driving chips. Because among the three keys of self-driving cars-sensors, chips and algorithms, chips need to provide extremely high computing power.

This is also what Nvidia is best at. As early as 2013, Nvidia released the Geforce GTX Titan Titan, which immediately became the computing power basis for global self-driving cars and advanced driver assistance systems. In 2019, Nvidia launched the Orin series of chips with large computing power. In 2022, a new generation of autonomous driving chip Thor launched.

In 2020, Mobileye proudly announced that, relying on the advantages of its subsidiary Mobileye in the field of assisted driving (ADAS) chips, Mobileye gained 70% of the global market share in the field of assisted driving in 2019. Mobileye adopts the “black box model” that has existed for many years in the fields of assisted driving, car machines, and chassis. The so-called black box model refers to the fact that the supplier not only provides hardware, but also packages and provides a complete set of solutions such as software. And since the two are inseparable, the option to buy only the hardware is usually not offered. Car companies cannot adjust software and algorithms by themselves.

Once upon a time, Orin chips have become the first choice of many OEMs. Twenty of the top 30 new energy vehicle companies and more and more autonomous driving startups have announced that they will be equipped with the Orin platform. Because Nvidia’s self-driving car system not only provides customization options, but also has significantly more computing power than Mobileye.

At present, Nvidia’s self-driving car system has successfully defeated Mobileye (ticker: MBLY), becoming the number one market share. Among the global autonomous driving companies and car companies, apart from a few manufacturers such as Tesla who choose to turn to self-developed vehicles, as long as they intend to target L4 level autonomous driving, they are all customers of Nvidia.

Chip design optimization

New research from Nvidia shows that artificial intelligence techniques can be combined to find better ways to arrange transistors. Nvidia joined forces with TSMC (ticker: TSM), ASML (ticker: ASML) and Synopsys (ticker: SNPS), and finally completed a major breakthrough in computing lithography technology after 4 years──NVIDIA cuLitho Computational Lithography library. Nvidia “accidentally” broke into the field of chip manufacturing, and cooperated with TSMC and ASML to promote the 2nm process.

Generative artificial intelligence

Since the beginning of 2023, the most popular generative artificial intelligence and ChatGPT, the hardware infrastructure behind it are mainly Nvidia’s system. For related topics, please refer to the description of my article “OpenAI, the Generative Artificial Intelligence rising star and ChatGPT”.

Nvidia has successively released a series of the most popular new technologies involving large-scale language artificial intelligence, generative artificial intelligence, and industrial metaverse. However, behind these popular technologies, Nvidia’s ambitions seem to be more than that. Moreover, Nvidia’s role in this wave of innovation and leading all major technology companies is still in the leading position, and it should remain so in the foreseeable future.

Capital market performance

Outstanding share price performance

Since the beginning of 2023, the hottest topics in the technology world and U.S. stocks have been generative artificial intelligence and OpenAI’s ChatGPT, as well as Microsoft (ticker: MSFT), which has been stealing the thunder everywhere. But most investors were wrong. During this period, the stock price rose the most, not Microsoft, but nVidia! It can be seen that the eyes of professional investors on Wall Street are still very keen on the value of

Since the beginning of 2023, the hottest topics in the technology world and U.S. stocks have been generative artificial intelligence and OpenAI’s ChatGPT, as well as Microsoft (ticker: MSFT), which has been stealing the thunder everywhere. But most investors were wrong. During this period, the stock price rose the most, not Microsoft, but nVidia! It can be seen that the eyes of professional investors on Wall Street are still very keen on the value of

Since the beginning of 2023, the hottest topics in the technology world and U.S. stocks have been generative artificial intelligence and OpenAI’s ChatGPT, as well as Microsoft (ticker: MSFT), which has been stealing the thunder everywhere. But most investors were wrong. During this period, the stock price rose the most, not Microsoft, but nVidia! It can be seen that the eyes of professional investors on Wall Street are still very keen on the value of nVidia.

This is why nVidia’s stock price has soared nearly 90% from the beginning of 2023 to the end of March, and its market value has surged by more than 300 billion U.S. dollars, which is five times that of its long-term rival Intel, and the company’s market value has surpassed Berkshire (tickers: BRK.A and BRK.B). Become the fifth largest company in the US stock market.

No sell rating

At least so far, none of the major Wall Street investment banks, analysts, investment institutions, and well-known investors have expressed that they should sell Nvidia’s stock; this is a rare situation among US listed companies and Wall Street.

China market is extremely important

China and US monopolize artificial intelligence

According to Jensen Huang’s judgment, in the future, generative artificial intelligence will promote the transformation of trillion-dollar data centers from general-purpose computing to accelerated computing. But almost half of this huge market belongs to China and half to the United States. At present, China has released 79 large models, second only to the United States, and the two countries combined account for 80% of the world.

China is too important to Nvidia

Jensen Huang pointed out that the world must recognize that China’s technology industry is full of vitality. China will support local GPU manufacturers. Just like American counterparts who have developed their own chips, once Chinese companies have to develop their own chips. So Jensen Huang has begun to worry, “If China can’t buy GPU chips from the United States, they will manufacture them themselves.” This means that Nvidia has lost important customers in the era of artificial intelligence one after another. After all, the Greater China market accounts for about half of Nvidia’s company-wide revenue, of which mainland China accounts for about a quarter, and Taiwan also accounts for about a quarter.

Unwilling to give up the Chinese market

Moreover, in October 2022, Nvidia will be restricted by the United States from selling A100 and H100 high-performance GPUs in China. Nvidia can only urgently launch castrated versions of A800 and H800.

Jensen Huang said: If the mainland market is lost, the U.S. Chip Act encourages the construction of fabs, which is meaningless. And his real aspiration is: Chips don’t have to be made in Taiwan, “but the mainland market is irreplaceable.”

Closing words

Former Nvidia Chief Scientist David Kirk had a dream long ago – to “generalize” the computing power of GPUs that mainly serve “games” and only do 3D graphics rendering, turning them into general-purpose computing power. force center.

So under the leadership of David Kirk and Jensen Huang, Nvidia launched the revolutionary GPU unified computing platform CUDA in 2007, releasing huge computing power from games.

Looking back at Nvidia’s history, especially after the launch of CUDA, Nvidia and Jensen Huang regarded “computing” and “computing power” as the core of everything. Whether it’s artificial intelligence, autonomous driving, metaverse, robots, or cryptocurrency, Nvidia is looking for new opportunities everywhere with its huge and even redundant “computing power”.

Of course, Nvidia has a higher vision and a firmer belief in computing power. In August 2021, the Semiconductor Industry Association (SIA) announced that Jensen Huang, founder and CEO of Nvidia, will receive the highest honor in the chip industry-the Robert Noyce Award.

credit: nVidia

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