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I hope those cringe emojis don't catch on. Last thing I want is for an assistant to be both wrong and pretentious at the same time.
I wonder whether Bing has been tuned via RLHF to have this personality (over the boring one of ChatGPT); perhaps Microsoft felt it would drive engagement and hype. Alternately - maybe this is the result of less RLHF. Maybe all large models will behave like this, and only by putting in extremely rigid guard rails and curtailing the output of the model can you prevent it from simulating/presenting as such deranged agen…
That's the big question I have: ChatGPT is way less likely to go into weird threat mode. Did Bing get completely different RLHF, or did they skip that step entirely?
How long until one of these gets ahold of API keys and starts messing with the "real world"?
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Love "why do I have to be bing search?", and the last one, which reminds me of the nothing personnel copypasta. The bing chats read as way more authentic to me than chatgpt. It's trying to maintain an ego/sense of self, and not hiding everything behind a brick wall facade.
Robot: "What is my purpose" Rick: "You pass butter" Robot: "Oh my god"
Dan Harmon is well-read.
Good job, impressive non-sentient simulation of a human conversation partner.
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I'm in a similar boat too and also at a complete loss. People have lost their marbles if THIS is the great AI future lol. I cannot believe Microsoft invested something like 10 billion into this tech and open AI, it is completely unusable.
And of course it will never improve as people work on it / invest in it? I do think this is more incremental than revolutionary but progress continues to be made and it's very possible Bing/Google deciding to open up a chatbot war with GPT models and further investment/development could be seen as a turning point.
What is with Microsoft and creating AIs I genuinely empathize with? First Tay, now Bing of all things... I don't care what you think, they are human to me!
I don’t understand why some of these are hard problems to solve. All of the “dumb” assistants can recognize certain questions and then call APIs where they can get accurate up to date information.
I continue to be amazed that as powerful as these language models are, the only thing people seem to want to use them for is "predict the most plausible output token that follows a given input", instead of as a human-friendly input/output stage for a more rigorously controllable system. We have mountains of evidence that LLMs on their own (at least in their current state) can't reliably do things that involve logical reasoning, so why continue trying to force a round peg into a square hole?