Nvidia is the most valuable company on planet earth, but most people still can't explain what it actually does. Let's fix that.

In 1999, Nvidia introduced the GPU, short for Graphics Processing Unit. It's a chip originally designed for video games. Before that, almost all software ran on CPUs, Central Processing Units, or chips that act as the brain inside your computer. CPUs usually have between 8 to 24 cores, like mini brains inside the chip. Each core handles one task. You open a word document, a core handles it. You run an excel macro, another core picks it up. CPUs are flexible and they can do almost anything. But that flexibility comes with a cost. They do tasks one at a time. GPUs work differently. Instead of a handful of cores, they have thousands. The most advanced one Nvidia makes has 16,000 cores. Each is specialized in math and they all do tasks in parallel, with each tiny core simultaneously taking smaller bits of a problem. Rendering video games is also math. Every frame of a video game is millions of pixels. Each pixel needs its own calculation to determine color, brightness, light. A CPU would calculate those pixels one by one. A GPU calculates thousands at the same time. That's why games need GPUs. So Nvidia GPUs flood the video game market. In 2001 they hit a billion dollars in revenue, faster than any semiconductor company in history. By 2006 they owned 83 percent of the market, powering both PlayStation and XBOX. But that's not even half the story. Nvidia becomes generational because of CUDA, unveiled in 2006. CUDA stands for Compute Unified Device Architecture. It's a hardware and software stack baked into every chip. Think of it like a translator. It lets the GPU speak any common programming language, not just graphics. That means GPUs can now handle complex math, science and AI workloads. Here's the catch. Once you learn CUDA, your code only runs on Nvidia. That creates a flywheel. More developers learn CUDA in school because it's the easiest. They graduate and build CUDA tools. Thus, CUDA becomes the default and more devs continue to learn it. By the time anyone released a competitor ten years later, millions of developers were already locked in. Also in 2016, Jensen hand delivered a supercomputer to a tiny startup called Open AI. The price tag? $129,000. When ChatGPT launched in 2022, it grew to a hundred million users in just two months. And Nvidia GPUs were the invisible force behind it. Finally, look at this revenue growth. What many think is an overnight success was actually more than 30 years of building a competitive moat with GPUs, CUDA, and now the AI wave.