NVIDIA is widely considered to be better than AMD for AI (Artificial Intelligence), and this is for several reasons.
Firstly, NVIDIA has invested heavily in developing specialized hardware for AI applications. They have created several GPU (Graphics Processing Unit) models, including the Tesla and Titan series, which are optimized for AI workloads. These GPUs have dedicated hardware for running matrix multiplication algorithms, which are essential for deep learning applications.
Secondly, NVIDIA has developed the CUDA programming language, which is widely used in AI research and development. CUDA allows developers to write code that can harness the full power of NVIDIA GPUs, and it is supported by many popular machine learning libraries, such as TensorFlow and PyTorch.
Thirdly, NVIDIA has built a strong ecosystem of AI partners and developers. They offer a range of tools, libraries, and SDKs (Software Development Kits) that make it easier for developers to build and deploy AI applications. Additionally, NVIDIA has established partnerships with leading cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud, all of whom offer NVIDIA GPUs for AI workloads.
Finally, NVIDIA has a track record of innovation and investment in AI. They have been developing AI hardware and software for over a decade, and they continue to invest heavily in R&D to stay ahead of the competition.
Overall, while AMD has made some strides in the AI space, NVIDIA remains the leader in this area due to their specialized hardware, programming language, ecosystem, and investment in AI innovation.