LLMs already do this. Their many wide layers allow for this, and as a final fallback, their output adjusts based on every token they generate (it's not all deci

LLMs already do this. Their many wide layers allow for this, and as a final fallback, their output adjusts based on every token they generate (it's not all decided at once). All your statement really means is a vague "well it should do it more!" which yeah, is the goal of each iteration of GPT etc.