AI, or artificial intelligence, has taken the world by storm for the reason that launch of Chat GPT in late 2022 — shaking the windows and rattling the partitions of each institution, from governments and universities to Fortune 500 corporations and trade unions.
Proponents claim it would usher in a recent era of economic productivity, prosperity, and human flourishing, while critics worry it would cause chaos and instability in every sector of the job market — from call center laborers to Hollywood screenwriters — exacerbating the wealth divide and turning hundreds of thousands of employees out on the road.
Some AI “doomers” worry that artificial intelligence will grow to be 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 businesses and individuals constructing and harnessing the technology.
Nvidia, which manufactures the leading computer chips powering the AI revolution, has grow to be the poster child for a way an organization can unlock billions, and even trillions, in value on this recent age.
Like AI itself, Nvidia is an “overnight success story” many a long time within 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 corporate released the first-ever GPU (graphics processor unit), a strong chip that would 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 massive 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 use their chips to all manner of tasks, type of like equipping a Formula 1 race automobile with an automatic transmission and cruise control.
In comparison with traditional chips like CPUs — the workhorses which have powered computers from the mainframes of the Fifties to today’s PCs and smartphones — GPUs are generally superior in training AI models and powering responses to our limitless AI prompts.
That’s since the so-called “machine learning algorithms” behind popular AI models require computers to perform multiple tasks directly.
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, alternatively, is more like a soccer team.
Each player is probably not as versatile because the decathlete — and so they may not even be as fast or strong.
But they work together to realize something the decathlete never could: operating as a team to advance the ball up the sphere and rating.
Today, GPUs are the dominant chip in AI — and Nvidia is the dominant player.
Based on 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 precise moment they’re needed to power the AI revolution?
CEO Jensen Huang said in a March 2023 interview: “We had the great wisdom to go put the entire company behind it,” a decade ago. The fact is somewhere in between. Luck, in spite of everything, is the mixture 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 grow to be the phenomenon it has today.
However, the corporate 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 to not.
From 3D graphics to PC gaming to blockchains to AI, NVIDIA has often found itself on the forefront of the most important 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 largely 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 only over a yr.
Much of that is driven by lofty expectations that the corporate will proceed to grow at a breakneck speed.
Wall Street analysts estimate the corporate 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 sort of 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 will be a mistake to think Nvidia has been alone in investing in AI.
Indeed, greater than a dozen other corporations 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 corporate’s many other AI applications.
Amazon, the worldwide leader in cloud computing — those data centers that power the computing needs of corporations from Pfizer to McDonald’s — has its AI-focused chips often known 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 have to be serious about silicon.”
Nvidia is swimming in a pond with many other powerful corporations stuffed with smart people and seemingly limitless resources, and when you find yourself at 100% market share (or 99.7%, within the case of Nvidia’s share of GPUs in data centers) there’s nowhere to go but down.
Still, it might be a mistake to easily assume that legacy players or Nvidia’s customers can throw enough money to compete with Nvidia with no fight.
Moreover, if AI prognosticators are correct, AI chips will power a completely recent industrial revolution, which is able to allow Nvidia to succeed whilst 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 worth of the corporate.
The identical could occur for Nvidia. In spite of everything, they don’t just earn money from AI; last yr, the corporate 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 most 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 guts of the worldwide tech industry.
Today, Fairchild now not exists. For a period within the Nineteen Sixties and ’70s, Digital Equipment Corp (DEC) was the most important computer company on the earth with so-called “minicomputers,” nevertheless it too got swept away, this time with the rise of the notebook computer or PC.
In 2007, Nokia sold one in every two phones globally.
That very same yr, 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 one 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 writer of the book “Web3: Charting the Web’s Next Economic and Cultural Frontier.”
