That means developers will soon be able to run MLX models directly on NVIDIA GPUs, which is a pretty big deal. Here’s why.

They also demonstrate running a 1.3 billion parameter model at 23.8 tokens per second on a GPU that was accelerated by a custom-programmed FPGA chip that uses about 13 watts of power (not counting ...

The cloud rendering company Otoy is claiming to have invented a new software translation layer that would allow Nvidia's CUDA to run on a variety of alternate GPUs, including AMD.

OpenAI claims Triton can deliver substantial ease-of-use benefits over coding in CUDA for some neural network tasks at the heart of machine learning forms of AI such as matrix multiplications.