Can China break NVIDIA’s grip? |
For more than a decade, NVIDIA’s CUDA platform has been the backbone of modern artificial intelligence. It is not just a software framework but a deeply embedded ecosystem that powers how AI models are trained, deployed, and scaled. China now recognises that NVIDIA’s dominance does not come from hardware alone but from this tightly integrated ecosystem built over decades. As a result, Huawei is developing CANN as an alternative, and emerging models such as DeepSeek V4 may soon deploy on it.
CUDA enables developers to harness the parallel processing power of GPUs for complex computations. Unlike traditional CPUs that handle tasks sequentially, GPUs process thousands of operations simultaneously. This makes them ideal for AI workloads, particularly deep learning, which relies heavily on matrix computations. However, CUDA’s strength lies beyond raw performance. It integrates hardware, compilers, libraries, and developer tools into a unified ecosystem. Frameworks such as PyTorch and TensorFlow are deeply optimised for CUDA, making it the default platform for AI development globally. Over time, this has created a powerful lock in effect.
Developers, enterprises, and researchers are all deeply embedded with in the CUDA ecosystem. Geopolitical pressures, particularly restrictions on advanced GPU exports, have accelerated China’s push for technological independence. Huawei’s CANN platform is at the centre of this effort. Designed as a CUDA like environment, it provides libraries,........