Nvidia comes from Envy
Did you know that Nvidia name is derived from the Latin word for “envy”?
Furthermore, as of May 2023, the company has achieved a remarkable $1 trillion market capitalization.
While Nvidia is renowned for its cutting-edge graphics and gaming, its impact extends well beyond these domains.
The company is a leader in artificial intelligence (AI), leveraging its GPUs and AI platforms in fields such as self-driving cars, healthcare, robotics, and more.
Jensen Huang, CEO of Nvidia, has been wearing a black leather biker jacket during keynotes for over a decade. This distinctive dressing style is inspired by Steve Jobs and has impressed stakeholders.
How did Nvidia attain such remarkable success, and what does its future hold? Continue reading to find out.
Early Days
Nvidia was established on April 5, 1993, by Jensen Huang, who currently serves as CEO in 2023 on his 30th birthday.
Huang is a Taiwanese-American electrical engineer with a background as the director of CoreWare at LSI Logic and a microprocessor designer at AMD.
Alongside Huang, the company was co-founded by Chris Malachowsky, an engineer with experience at Sun Microsystems, and Curtis Priem, who had previously worked as a senior staff engineer and graphics chip designer at IBM and Sun Microsystems.
The three individuals initiated the company’s inception during a meeting at a Denny’s roadside diner in East San Jose.
Nvidia’s inception was rooted in the belief that personal computers would evolve into commercial devices for enjoying video games and multimedia.
AT PRESENT
What we have today is the evolved iteration of what used to be a PC – featuring a bulky display, a noisy CPU, a cumbersome keyboard, and a trackball mouse.
During the time of its founding, there were multiple graphics chip companies, a number that saw exponential growth within three years.
Driven by their resolve and persistence, three young electrical engineers embarked on establishing Nvidia, with the goal of crafting advanced specialized chips capable of generating faster and more lifelike graphics for video games.
“There was no market in 1993, but we saw a wave coming.”
~Malachowsky
He likened their situation to a California surfing competition, where surfers are informed to gather when a wave phenomenon or storm emerges in Japan, predicting a wave’s arrival on the Californian shores in two days.
This analogy captures the early anticipation and readiness of Nvidia for the impending market wave.
In this context, the “wave” refers to the emerging market demand for GPUs (Graphic Processing Units) of that time.
In the past, these chips were sold to gamers to be integrated into a PC’s motherboard, resulting in ultra-fast 3D graphics, albeit at a steep price of up to $1,200.
Even twenty years later, these chips continue to contribute more than half of Nvidia’s total revenues.
Long shot of Nvidia
In 1993, the three founders held the belief that the most promising path for the upcoming era of computing lay in accelerated computing, specifically graphics-based computing. This direction seemed capable of tackling challenges beyond the reach of general-purpose computing.
They also recognized that video games presented both highly demanding computational problems and the potential for substantial sales volume — a rare combination.
This led to video games serving as the driving force to tap into expansive markets and provide substantial R&D funding for solving complex computational issues.
With an initial bank balance of $40,000, the company was established. Subsequently, venture capital funding of $20 million was secured, primarily from Sequoia Capital and other sources.
In its early stages, Nvidia lacked a formal name, and the founders designated all their files with “NV,” signifying “next version.”
The necessity of incorporating the company prompted a search for a name, ultimately leading them to “invidia,” the Latin term for “envy,” after reviewing words containing those two letters.
Bankruptcy of Nvidia
Nvidia’s first chip, the NV1, was a major failure.
It was designed to be a 2D and 3D graphics accelerator.
But it was too expensive, too power-hungry, and not compatible with the latest graphics APIs.
As a result, it was a commercial flop and cost Nvidia $10 million.
The failure of the NV1 nearly bankrupted Nvidia. The company was forced to lay off half of its 80 employees and move to a smaller office.
However, Nvidia’s management refused to give up. They knew that they had a good team and a promising technology, and they were determined to succeed.
In 1997, Nvidia released the Riva 128, which was a much more successful graphics chip. The Riva 128 was compatible with the latest graphics APIs and offered much better performance than the NV1.
It quickly became a popular choice for gamers and PC enthusiasts.
The success of the Riva 128 helped Nvidia to turn things around.
The company went on to release a number of other successful graphics chips, including the GeForce 256, the GeForce 3, and the GeForce 4. Today, Nvidia is one of the leading manufacturers of graphics chips in the world.
CUDA- the masterpiece of Nvidia
In the mid-2000s, they introduced something called CUDA, which is like a special tool for their GPUs (the powerful part of computers). This tool made their GPUs really good at doing AI stuff.
They used something called parallel computing, which means doing lots of tasks at the same time. This helped AI programs learn and process big amounts of data super fast.
Imagine it like this: parallel computing is like solving a big puzzle by breaking it into smaller pieces and having many people work on those pieces together.
CUDA helped their GPUs work together like a super team for AI tasks. This was much faster and better than using regular computer parts (CPUs) alone.
Because of this, Nvidia’s special GPUs with CUDA became the main reason behind big improvements in AI technology.
The graphics-focused company has consistently made significant headlines over the years.
AI & Nvidia
However, its success story goes beyond just video games and graphics. The real driving force behind its current success is artificial intelligence (AI) and deep learning.
Deep learning enables computers to learn autonomously, eliminating the need for constant oversight from the IT department on coding aspects. This results in precise image and speech recognition.
Major tech giants like Google, Microsoft, Facebook, and Amazon are procuring Nvidia’s chips in substantial quantities for their data centers.
These chips provide the necessary computational power for emerging virtual reality devices in the market.
Globally, there are around 3,000 AI startups, many of which are building their processes on Nvidia’s platforms.
They utilize the company’s GPUs in AI applications for activities such as stock trading, online shopping, and drone navigation.
Jensen Huang had a hunch that graphics chips held untapped potential beyond just powering video games.
However, he didn’t anticipate the eventual shift toward deep learning.
The adoption of this technology faced two primary challenges: the volume of data required to train algorithms and access to more substantial computing power.
While the internet addressed the data availability issue, the introduction of CUDA in 2006 resolved the latter concern.
This programming toolkit enabled developers to easily program individual pixels on a screen using a high-level language like Java or C++.
“AI Computing is the future of computing. As long as we continue to make our platform the best for AI computing, I believe we have a strong chance of securing significant business. GPUs will be integral to many companies.”
~Jensen Huang, CEO, Nvidia
Nvidia has now evolved into a formidable company that is shaping the course of 21st-century computing.
What made Nvidia a trillion dollar company
Nvidia became a trillion dollar company in May 2023, thanks to the rise of artificial intelligence (AI). The company’s GPUs are used in a wide range of AI applications, from self-driving cars to facial recognition software.
Here are some of the factors that contributed to Nvidia’s rise to trillion dollar status:
The increasing demand for AI: AI is becoming increasingly important in a wide range of industries, from healthcare to manufacturing. This has led to a surge in demand for Nvidia’s GPUs, which are used to power AI applications.
Nvidia’s leadership in AI: Nvidia is a leading innovator in the AI space. The company has developed a number of breakthrough technologies that have made it the go-to choice for AI developers.
The company’s strong financial performance: Nvidia has consistently delivered strong financial results. The company’s revenue and earnings have grown by double digits in recent years.
Strong brand reputation: Nvidia has a strong brand reputation among investors and customers. The company is seen as a leader in the semiconductor industry and a pioneer in the AI space.
Nvidia is a well-positioned company to continue to grow in the years to come. The demand for AI is expected to continue to grow, and Nvidia is well-positioned to capitalize on this trend. The company is also investing heavily in new technologies, which will help it to stay ahead of the competition.
Here are some of the areas where Nvidia is expected to grow in the future:
Self-driving cars: Nvidia is a major player in the self-driving car market. The company’s GPUs are used in most self-driving car prototypes. As the self-driving car market grows, Nvidia is expected to benefit.
Data centers: Nvidia’s GPUs are also used in data centers. Data centers are used to store and process large amounts of data, and they are becoming increasingly important as businesses adopt more AI-powered applications.
Virtual reality and augmented reality: Nvidia’s GPUs are also used in virtual reality (VR) and augmented reality (AR) headsets. VR and AR are emerging technologies with the potential to revolutionize the way we interact with computers. Nvidia is well-positioned to benefit from this growth.
Nvidia is a company that is constantly innovating. It is likely to continue to grow in the years to come, and it is possible that the company will become even more valuable in the future.
Read more: How ChatGPT made Nvidia $1T company
Failures in Nvidia Journey
Foray into Smartphone market
Certainly, Nvidia has faced its fair share of challenges along the way. They ventured ambitiously into the smartphone market with their Tegra processors but eventually realized it wasn’t their strong suit.
The Tegra processors were initially well-received, but they soon faced some challenges. One of the biggest problems was that they were power-hungry, which led to overheating issues.
They also had a poor power-to-performance ratio, meaning that they were not as efficient as other mobile processors.
In addition, Nvidia faced competition from other chipmakers, such as Qualcomm and Apple. These companies were able to offer better performance and battery life, which made it difficult for Nvidia to compete.
As a result, Nvidia decided to shift its focus away from the smartphone market and towards other areas, such as the automotive and gaming industries.
The company is still making Tegra processors, but they are now targeting more specialized applications, such as self-driving cars and augmented reality headsets.
Nvidia couldn’t buy ARM
In 2022, the company abandoned its attempt to acquire Arm, a British chip designer, due to significant regulatory challenges.
The proposed acquisition would have been the largest semiconductor chip merger in history, and it was met with opposition from regulators around the world.
The European Commission, the United States Department of Justice, and the UK Competition and Markets Authority all expressed concerns that the acquisition would give Nvidia too much control over the semiconductor industry.
They argued that the deal could stifle innovation and raise prices for consumers.
Nvidia argued that the acquisition would be beneficial for the industry, as it would allow the company to accelerate Arm’s development and make its technology more widely available.
However, the regulators were not convinced, and they ultimately blocked the deal.
Nvidia Controversies
Nvidia has found itself at the center of several significant controversies throughout its history. Let’s take a closer look at a couple of them.
GPU Class Action Lawsuit Back in 2008, Nvidia faced a class-action lawsuit regarding faulty GPUs used in laptops from Apple, Dell, and HP.
Although Nvidia didn’t specify which GPUs were affected, they reached a settlement in the autumn of 2010.
As part of this resolution, Nvidia agreed to reimburse or replace individuals who owned laptops impacted by the GPU issue.
False Advertising Lawsuit The launch of the GeForce GTX 970 in 2014 sparked a substantial controversy.
Nvidia’s advertising claimed that the graphics cards had 4 GB of memory, but in reality, the GTX 970’s memory was capped at 3.5 GB. Further investigation revealed that the card’s performance suffered significantly when it exceeded this threshold.
Following an extensive legal process over the subsequent couple of years, Nvidia ultimately settled the class-action lawsuit.
They offered a $30 refund to everyone who had purchased the GTX 970 as compensation.
Read More: History of Semiconductor Stalwarts
Conclusion
Looking forward, Nvidia’s future appears promising yet complex. There are significant geopolitical risks, including concerns about U.S.-China relations and reliance on Taiwan Semiconductor Manufacturing Company (TSMC) for chip production.
Nevertheless, Nvidia is actively addressing these challenges by exploring collaborations and investing in backup plans to ensure a secure supply chain.
The portion of specialized chips, such as GPUs used in data centers, is projected to increase to over 15% by 2026, a substantial jump from less than 3% in 2020. This indicates that Nvidia is well-positioned to continue its growth trajectory as the demand for AI and data processing capabilities continues to rise.
“I always think we’re 30 days from going out of business. That mindset hasn’t changed. It’s not a fear of failure but a fear of becoming complacent, which I never want to happen.”
~~Jensen Huang, CEO, Nvidia
