>With the advent of the revolutionary Chain-of-Thought ("COT") models introduced in the past year, most noticeably in OpenAI's flagship O1 model (but very recently in DeepSeek's new R1 model, which we will talk about later in much more detail), all that changed. Instead of the amount of inference compute being directly proportional to the length of the output text generated by the model (scaling up for larger context windows, model size, etc.), these new COT models also generate intermediate "logic tokens"; think of this as a sort of scratchpad or "internal monologue" of the model while it's trying to solve your problem or complete its assigned task.
Is this right? I thought CoT was a prompting method and are we calling the reasoning models as CoT models?