âPrimingâ reuses pretrained Transformer weights to build models with more efficient architectures at less than 1% of the original training cost and with throughputs up to twice as high.
Using the Neuron Kernel Interface, a ReactorâAWS collaboration tackled the dynamic shapes, memory access patterns, and cache management that make real-time autoregressive diffusion hardâbuilding techniques that generalize across models.
