At this point, is the second L (language) a limitations to LLMs? Is reasoning in latent space directly a more efficient and more "native" inference? I remember when one researcher replicated the middle layer of deepseek model (just the "thinking" layers) and its benchmark scores got noticebly higher. All of this is moving so fast, and yet it's quite exciting.