DDIM does: deterministic sampling for faster generation with fewer steps

gradient accumulation simulates larger batch sizes without more memory

Gradient accumulation reduces memory usage by dividing a large batch into smaller mini-batches, accumulating gradients before updating model weights

batch size affects generalization: larger batches find sharper minima

Larger batch sizes lead to sharper minima, enhancing generalization by providing more accurate gradient estimates

Stable Diffusion

Stable Diffusion generates images from text descriptions

Flashbulb memory

Flashbulb memories are vivid but not always accurate

Attention Is All You Need

O(n) complexity for long sequences

quantization to INT8 doubles throughput

Quantization to INT8 doubles throughput because tensor cores process INT8 2x faster