AI, or artificial intelligence, has taken the world by storm since the launch of Chat GPT in late 2022 — shaking the windows and rattling the partitions of each institution, from governments and universities to Fortune 500 companies and trade unions.
Proponents claim it is going to usher in a latest era of economic productivity, prosperity, and human flourishing, while critics worry it is going to cause chaos and instability in every sector of the job market — from call center laborers to Hollywood screenwriters — exacerbating the wealth divide and turning tens of millions of employees out on the street.
Some AI “doomers” worry that artificial intelligence will change into self-aware and switch on its human creators, à la Skynet in “The Terminator” and other sci-fi works.
But what everyone seems to agree on is that AI will create tremendous wealth for the companies and individuals constructing and harnessing the technology.
Nvidia, which manufactures the leading computer chips powering the AI revolution, has change into the poster child for a way an organization can unlock billions, and even trillions, in value in this latest age.
Like AI itself, Nvidia is an “overnight success story” many many years in the making.
Formed in 1993 by CEO Jensen Huang and co-founders Chris Malachowsky and Curtis Priem, NVIDIA initially aimed to bring 3D technology to gaming and media.
In 1999 the company released the first-ever GPU (graphics processor unit), a robust chip that might render 3D graphics in real time.
The primary Xbox gaming console and the PlayStation 3 ran on NVIDIA’s formidable chip technology.
Later, Nvidia chips became the backbone of blockchain networks like Ethereum, which, until recently, required the large computing power of GPUs to secure transactions and store data.
Nvidia was also a pioneer in constructing a software toolkit called CUDA that made it easier for programmers to apply their chips to all manner of tasks, sort of like equipping a Formula 1 race automobile with an automatic transmission and cruise control.
Compared to traditional chips like CPUs — the workhorses which have powered computers from the mainframes of the Nineteen Fifties to today’s PCs and smartphones — GPUs are generally superior in training AI models and powering responses to our infinite AI prompts.
That’s because the so-called “machine learning algorithms” behind popular AI models require computers to perform multiple tasks without delay.
GPUs, unlike CPUs, can break down AI tasks into smaller chunks and run them concurrently, dramatically improving speed and performance.
Consider a CPU as a decathlete who competes in 10 different track and field events.
Like a CPU, a decathlete can do multiple tasks thoroughly, but only in sequence; you may’t take your shot put into the swimming pool.
A GPU, on the other hand, is more like a soccer team.
Each player might not be as versatile as the decathlete — they usually may not even be as fast or strong.
But they work together to achieve something the decathlete never could: operating as a team to advance the ball up the field and rating.
Today, GPUs are the dominant chip in AI — and Nvidia is the dominant player.
According to Mercury Research, in Q3 of 2023, NVIDIA sold $11.1 billion in chips, cards, and related hardware, representing a 99.7% share of GPU systems in data centers worldwide.
So was Nvidia just lucky to have developed the best-in-class GPU at the exact moment they’re needed to power the AI revolution?
CEO Jensen Huang said in a March 2023 interview: “We had the good wisdom to go put the whole company behind it,” a decade ago. The truth is somewhere in between. Luck, in any case, is the combination of preparation and good timing.
In 2012 when Nvidia released its first AI product, it could hardly have anticipated that in a decade, AI was going to change into the phenomenon it has today.
On the other hand, the company could never have seized this moment if it hadn’t began investing in AI long before its peers.
Other chip makers like Intel could have prepared higher for the AI age but simply selected not to.
From 3D graphics to PC gaming to blockchains to AI, NVIDIA has often found itself at the forefront of the biggest paradigm shifts in technology. And this has translated right into a historic windfall for shareholders.
The day Chat GPT launched in November 2022, NVIDIA was a $400 billion company — enormous even then, thanks in large part to the success of its gaming and graphics business.
But since then, its market value has swelled by a staggering trillion dollars to greater than $1.4 trillion, the equivalent of about 4 Bank of Americas, in market capitalization in just over a 12 months.
Much of that is driven by lofty expectations that the company will proceed to grow at a breakneck speed.
Wall Street analysts estimate the company will greater than double revenue between 2023 and 2024, and nearly double again in 2025.
Growth of that magnitude for such a big company is almost unheard of.
This raises several questions.
For one, is such growth actually achievable?
And in that case, won’t other chip makers race to construct Nvidia killers?
It could be a mistake to think Nvidia has been alone in investing in AI.
Indeed, greater than a dozen other companies crowd the market with their very own offerings, including legacy chipmakers like AMD, Intel, and IBM, and lesser-known upstarts equivalent to Graphcore and Groq.
Moreover, big tech platforms, which all have huge computing needs, have been developing their very own chips.
For instance, the Google Cloud TPU (tensor processing unit) was launched in 2015 and was updated in 2021.
Today, it powers Google’s Bard chatbot and the company’s many other AI applications.
Amazon, the global leader in cloud computing — those data centers that power the computing needs of companies from Pfizer to McDonald’s — has its AI-focused chips referred to as Tranium/Inferentia, launched in 2020.
Chinese technology conglomerate Alibaba announced its own AI chip, the Hanguang 800, back in 2019.
As industry analyst Ben Bajarin wrote on X shortly after Microsoft announced its own AI hardware offering, “Those serious about platforms need to be serious about silicon.”
Nvidia is swimming in a pond with many other powerful companies filled with smart people and seemingly infinite resources, and when you’re at 100% market share (or 99.7%, in the case of Nvidia’s share of GPUs in data centers) there’s nowhere to go but down.
Still, it could be a mistake to simply assume that legacy players or Nvidia’s customers can throw enough money to compete with Nvidia and not using a fight.
Moreover, if AI prognosticators are correct, AI chips will power a completely latest industrial revolution, which is able to allow Nvidia to succeed at the same time as competition grows.
Henry Ford sold quite a bit more cars in 1929 than in 1919 when half the automobiles on the road were Model Ts — despite the fact that competitors had consolidated and copied his methods, despite his market share steadily declining.
His share of the market went down but total sales went up, as did the value of the company.
The identical could occur for Nvidia. In any case, they don’t just earn cash from AI; last 12 months, the company generated about $12 billion from non-AI products.
Still, Nvidia’s long-term success is removed from guaranteed.
Fairchild Semiconductor was once the standard-bearer for American innovation.
It supplied lots of the chips for the Apollo Lunar guidance system.
Its success helped transform a quiet valley of California apple orchards into Silicon Valley, and the heart of the global tech industry.
Today, Fairchild now not exists. For a period in the Nineteen Sixties and ’70s, Digital Equipment Corp (DEC) was the biggest computer company in the world with so-called “minicomputers,” but it surely too got swept away, this time with the rise of the pc or PC.
In 2007, Nokia sold one in every two phones globally.
That very same 12 months, the iPhone got here out. Today Nokia accounts for just 3% of all sales.
And let’s not ignore Blackberry — remember them?
In technology, the only constant is change. Nvidia’s future success will rest on its ability to navigate that change.
Alex Tapscott is the managing director of the Ninepoint Digital Asset Group at Ninepoint Partners and the creator of the book “Web3: Charting the Web’s Next Economic and Cultural Frontier.”