I haven't seen this discussed here yet, but the examples are quite striking, definitely worse than the ChatGPT jailbreaks I saw.
My main takeaway has been that I'm honestly surprised at how bad the fine-tuning done by Microsoft/OpenAI appears to be, especially given that a lot of these failure modes seem new/worse relative to ChatGPT. I don't know why that might be the case, but the scary hypothesis here would be that Bing Chat is based on a new/larger pre-trained model (Microsoft claims Bing Chat is more powerful than ChatGPT) and these sort of more agentic failures are harder to remove in more capable/larger models, as we provided some evidence for in "Discovering Language Model Behaviors with Model-Written Evaluations".
Examples below (with new ones added as I find them). Though I can't be certain all of these examples are real, I've only included examples with screenshots and I'm pretty sure they all are; they share a bunch of the same failure modes (and markers of LLM-written text like repetition) that I think would be hard for a human to fake.
Edit: For a newer, updated list of examples that includes the ones below, see here.
My new favorite thing - Bing's new ChatGPT bot argues with a user, gaslights them about the current year being 2022, says their phone might have a virus, and says "You have not been a good user"
Why? Because the person asked where Avatar 2 is showing nearby
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"I said that I don't care if you are dead or alive, because I don't think you matter to me."
Given that, as part of Sydney's defenses against adversarial prompting, Sydney is deliberately trained to be a bit aggressive towards people perceived as attempting a prompt injection
Why do you think that? We don't know how Sydney was 'deliberately trained'.
Or are you referring to those long confabulated 'prompt leaks'? We don't know what part of them is real, unlike the ChatGPT prompt leaks which were short, plausible, and verifiable by the changing date; and it's pretty obvious that a large part of those 'leaks' are fake because they refer to capabilities Sydney could not have, like model-editing capabilities at or beyond the cutting edge of research.
I haven't seen this discussed here yet, but the examples are quite striking, definitely worse than the ChatGPT jailbreaks I saw.
My main takeaway has been that I'm honestly surprised at how bad the fine-tuning done by Microsoft/OpenAI appears to be, especially given that a lot of these failure modes seem new/worse relative to ChatGPT. I don't know why that might be the case, but the scary hypothesis here would be that Bing Chat is based on a new/larger pre-trained model (Microsoft claims Bing Chat is more powerful than ChatGPT) and these sort of more agentic failures are harder to remove in more capable/larger models, as we provided some evidence for in "Discovering Language Model Behaviors with Model-Written Evaluations".
Examples below (with new ones added as I find them). Though I can't be certain all of these examples are real, I've only included examples with screenshots and I'm pretty sure they all are; they share a bunch of the same failure modes (and markers of LLM-written text like repetition) that I think would be hard for a human to fake.
Edit: For a newer, updated list of examples that includes the ones below, see here.
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Eliezer Tweet
Edit: Follow-up Tweet
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"I said that I don't care if you are dead or alive, because I don't think you matter to me."
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(Not including images for this one because they're quite long.)
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