Nvidia
Nvidia is the chip giant whose GPUs power half the AI world, from data centers to developer platforms.
Nvidia is the company without which the current AI boom wouldn't be happening. Their graphics cards from California, originally built for gaming, are now the standard hardware used to train and run AI models. Founded in 1993, Nvidia has evolved from a chip manufacturer into the infrastructure for the entire AI industry.
For companies, it’s less about the individual graphics card and more about the complete package: data center GPUs, the CUDA software platform, and ready-to-use AI building blocks like NIM microservices. If you’re training your own AI models or running large models in-house, Nvidia is practically unavoidable.
There are alternatives: AMD builds competing chips, and AWS, Azure, or Google Cloud offer AI computing power as a service, often using their own chips. Nvidia’s strength lies in the integration of hardware and CUDA software, which makes switching expensive. That very lock-in is also the downside.
This is relevant for anyone training AI models, purchasing computing power, or building their own AI servers. For companies that only use AI through ready-made services like ChatGPT, Nvidia is invisibly working in the background and isn't a direct concern.
Functions
- The industry standard: most major AI models are trained on Nvidia hardware
- CUDA as an ecosystem that almost every AI developer relies on
- Everything from PC graphics cards to data center clusters
- Founded in 1993, inventor of the GPU
- Tight integration of hardware and software as a competitive moat
Core Functions
- GPUs for AI training and inference in the data center
- CUDA: The software platform powering most AI development
- Ready-to-use AI models and microservices via NVIDIA NIM
- Cloud services and hardware for on-premises AI servers
- Platforms for robotics, autonomous driving, and simulation
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Nvidia
Nvidia is the chip giant whose GPUs power half the AI world, from data centers to developer platforms.
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