Overview: NVIDIA’s H100 and A100 dominate large-scale AI training with unmatched tensor performance and massive VRAM capacity ...

Not every regression or classification problem needs to be solved with deep learning. For that matter, not every regression or classification problem needs to be solved with machine learning. After ...

A lot of people will tell you that PyTorch is for NVIDIA GPUs, but that's not actually true. PyTorch is platform-agnostic; it's just that many packages built on PyTorch make heavy use of NVIDIA's CUDA ...

Deep learning is changing our lives in small and large ways every day. Whether it’s Siri or Alexa following our voice commands, the real-time translation apps on our phones, or the computer vision ...

In the dynamic world of machine learning, two heavyweight frameworks often dominate the conversation: PyTorch and TensorFlow. These frameworks are more than just a means to create sophisticated ...

The DGX Spark demonstrates Nvidia’s vertical integration across silicon design, system architecture and software platforms.

AMD has delivered on its Computex 2025 promise to make PyTorch work on Windows for consumer GPUs and APUs. With the release of ROCm 6.4.4, Radeon RX 9000 (RDNA 4), RX 7000 (RDNA 3), and the new Ryzen ...

Graphics processing units (GPUs) are traditionally designed to handle graphics computational tasks, such as image and video processing and rendering, 2D and 3D graphics, vectoring, and more.