One of the blog post authors here! I think this finding is pretty surprising at the purely behavioral level, without needing to anthropomorphize the models. Two specific things I think are surprising:

- This appears to be a regression relative to the GPT-series models which is specific to the o-series models. GPT-series models do not fabricate answers as often, and when they do they rarely double-down in the way o3 does. This suggests there's something specific in the way the o-series models are being trained that produces this behavior. By default I would have expected a newer model to fabricate actions less often rather than more!

- We found instances where the chain-of-thought summary and output response contradict each other: in the reasoning summary, o3 states the truth that e.g. "I don't have a real laptop since I'm an AI ... I need to be clear that I'm just simulating this setup", but in the actual response, o3 does not acknowledge this at all and instead fabricates a specific laptop model (with e.g. a "14-inch chassis" and "32 GB unified memory"). This suggests that the model does have the capability of recognizing that the statement is not true, and still generates it anyway. (See https://x.com/TransluceAI/status/1912617944619839710 and https://chatgpt.com/share/6800134b-1758-8012-9d8f-63736268b0... for details.)