3 ms·

If you mean CoT, it's mostly fake https://www.anthropic.com/research/reasoning-models-dont-say-think https://www.anthropic.com/research/reasoning-models-dont-sa

• Davidzheng 1y ago
  very few humans are as good as these models at arithmetic. and CoT is not "mostly fake" that's not a correct interpretation of that research. It can be deceptive but so can human justifications of actions.
  • andrepd 1y ago
    Humans can learn the symbolic rules and then apply them correctly to any problem, bounded only by time, and modulo lapses of concentration. LLMs fundamentally do not work this way, which is a major shortcoming. They can convincingly mimic human thought but the illusion falls flat at further inspection.
  • jimbo808 1y ago
    What? Do you mean like this??? https://www.reddit.com/r/OpenAI/comments/1mkrrbx/chatgpt_5_has_unrivaled_math_skills/ https://www.reddit.com/r/OpenAI/comments/1mkrrbx/chatgpt_5_h... Calculators have been better than humans at arithmetic for well over half a century. Calculators can reason?
• diggan 1y ago
  > If you mean CoT, it's mostly fake If that's your take-away from that paper, it seems you've arrived at the wrong conclusion. It's not that it's "fake", it's that it doesn't give the full picture, and if you only rely on CoT to catch "undesirable" behavior, you'll miss a lot. There is a lot more nuance than you allude to, from the paper itself: > These results suggest that CoT monitoring is a promising way of noticing undesired behaviors during training and evaluations, but that it is not sufficient to rule them out.