The article discusses methods for improving inference speed in language models using speculative decoding techniques, particularly through the implementation of MTP heads and novel attention mechanisms. It highlights challenges such as the trade-offs in accuracy and performance when using custom attention masks and the intricacies of CPU-GPU synchronization during inference.