Nvidia’s shares are up by over 150% this year and it might soon become the first $1 trillion chip company. And in today’s Finshots, we need to talk about how it got here.
30 years ago, Nvidia was a gaming company. Sort of.
They didn’t make games. But they did make these top-notch cards called graphic processing units (GPUs). Add it to a computer and it would instantly boost the computation power. And suddenly, the game could render itself so realistically that it would make it look like you could immerse yourself in the game too.
Then, Nvidia became a crypto company. Again, kind of.
Because the crypto folks found uses for these GPUs. See, miners needed powerful processing to run complex calculations that would release Bitcoins and Ethers into the world. And they figured that if they simply used multiple GPUs made by Nvidia, the computers could process multiple computations very quickly.
But in between all of this, Nvidia was quietly transforming itself into an AI company.
The famous ChatGPT that everyone loves to talk about? Well, bet you didn’t know that it has ‘Nvidia Inside’! Yup, the supercomputer behind OpenAI’s ChatGPT needed 10,000 of Nvidia’s famous chips.
But until Wednesday, no one really knew just how much demand there could be from AI-related companies for these GPUs. Nvidia announced its financial results. And then made projections that blew everyone away. It said it’ll make $11 billion in the next quarter all thanks to AI. That's a whopping 50% higher than analysts' predictions of $7 billion.
Investors loved it. The shares soared by 24% in a single day. It reached within touching distance of the $1 trillion market capitalization club. And the company is now bigger than its two largest US competitors put together — Intel and AMD.
But here’s the thing. Nvidia’s overnight success has been many years in the making.
What do we mean?
Well, legend has it that it involves a cat and took place all the way back in 2010!
Okay, not a real cat. But back in the day, Bill Dally, who is the chief scientist at NVIDIA, was breaking bread with another computer scientist named Andrew Ng. Now Ng was building something at Google. And this project involved the network being able to learn on its own. For instance, if you show it millions of YouTube videos with cats, it would be able to soon identify cats by itself.
But it wasn’t going to be easy because it would need thousands of CPUs to do the grunt work. And you can’t really get thousands of these things together for a project like this. There had to be a better way. And that’s when Dally thought that of using GPUs instead to really bump up the processing power and handle the intense workload. So he got another Nvidia researcher Bryan Catanzaro and put together just 12 GPUs, and it worked. It was faster and more efficient for training the model.
And voila, Nvidia realized what it could do to the world of AI.
Or at least that’s how the story goes.
The more boring version of this story is that Nvidia’s AI journey began way back in 2006. The team quietly began to add something that it called CUDA [compute unified device architecture] into every single one of its GPUs. This opened up the hardware for software developers to tinker with. And this was revolutionary.
Nvidia’s CEO told analysts over a call that it “will open a whole new field called GPU computing.” But no one understood its true might. No one batted an eyelid.
But the addition of CUDA dramatically changed the game for Nvidia. No other chipmaker had integrated hardware and software so seamlessly. And this took the capability of these chips to a whole new level. The chips began to do things that we all take for granted.
For instance, maybe Netflix wanted to figure out what could potentially become the next binge-worthy show. Or just figure out which image for a TV show is likely to get more people to click on it. It needs to use AI models to predict all this.
Or maybe Volkswagen wanted to develop intelligent driving systems that help drivers. Such as staying in their own lane. The computer in the car will have to calculate this using a whole host of things.
Both of these tasks needed powerful processors to do the dirty work in the background. And that’s when Nvidia’s GPUs came in. The AI revolution was happening.
But all of this was invisible work. We needed a big bang to wake us up. And that x-factor was ChatGPT. Suddenly, the change wasn’t incremental. The door was blown wide open. With just a few prompts, anyone could create content, stories, and even write code. Something of this scale had never happened before. People paid attention.
And when they did. They realized that it was Nvidia at the centre of it all.
Those 10,000 chips that were put to work for ChatGPT? Well, each chip costs a staggering $10,000. If you don’t want to do the math, that’s worth a massive $100 million.
With every company wanting to use AI, imagine the kind of money Nvidia can rake in with its GPU.
Analysts and investors just can’t stop drooling. Because 88% of the GPUs in the world are controlled by Nvidia. It’s like Nvidia’s rivals AMD and Intel aren’t even in the race. And even as Nvidia’s chips for AI business grew by 14% in the first three months of this year, AMD didn’t grow, and Intel’s business division declined by 39%.
It definitely looks like the AI race is Nvidia’s to lose now.
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