Training has a lot of extra functionality like calculating how to update the weights of the model during training to make it more performant on the dataset(backpropagation and gradient descent) and much more
Meanwhile inference is mostly running the weights of the model as they are. The model isn’t being adjusted in any way. And Nvidia holds a strong grip on training libraries through Cuda
That’s all software, I don’t think anyone is doing back prop in hardware. Your are right about cuda, but z.ai just demonstrated that moat is evaporating quick
Running refers to inference usually
If they can be used for inference, I would assume they can be used for training
Training has a lot of extra functionality like calculating how to update the weights of the model during training to make it more performant on the dataset(backpropagation and gradient descent) and much more
Meanwhile inference is mostly running the weights of the model as they are. The model isn’t being adjusted in any way. And Nvidia holds a strong grip on training libraries through Cuda
They can be used for training…
That’s all software, I don’t think anyone is doing back prop in hardware. Your are right about cuda, but z.ai just demonstrated that moat is evaporating quick