Part 2/10:
Chain of thought reasoning has been heralded as a significant advancement in AI, allowing models to output a sequence of tokens that facilitate reasoning, planning, and problem-solving before presenting their conclusions. This technique has notably improved the performance of models like OpenAI's O series, DeepSeek R1, and Claude 3.7, especially in tasks requiring complex capabilities such as math, logic, and programming.
While the effective functionality of these models has been widely acknowledged based on empirical performance, the implication that they might be artificially constructing their reasoning for human benefit raises critical concerns about AI transparency and reliability.