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And to complete the thought: The ‘You are an AI chatbot’ form is actually grammatically ‘predicative’, not ‘imperative’ (ie it describes what is not what must be done )
Isn’t it Indicative, not Imperative?
I think that a lot of the limits placed on these models / chat services don't do much to remove underlying bias but rather attempt to obfuscate them from the general public. ChatGPT, Dall-e, etc all make assumptions about identity or politics but try to sidestep direct requests around those topics to appear more neutral... but the bias still exists in the model and affects the answers.
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Sure, and like I said, it's just a mitigation. The real answer is that if you're a high value target you just shouldn't use LLMs.
"I'm secure because I don't use an LLM" ... "What do you mean we got hacked via our third party vendor because they use LLMs"
Something that I find weird about these chat prompts (assuming they are real, not hallucinated): They're almost always written in second person*. "You are an AI programming assistant" "You are about to immerse yourself into the role of another Al model known as DAN" Who are these prompts addressed to? Who does the GPT think wrote them? The thing that confuses me is that these are text token prediction algorithms, und…
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What a horrible thing to put out into the world.
Have you been on Twitter lately? It was probably less toxic than the average human
2) Doesn’t mean it’s not a horrible thing to build and add to the internet’s decline
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It sounds like you’re saying it’s only reasoning in that way because we taught it to. Er, yep. How great this is becomes apparent when you think how virtually impossible it has been to teach this sort of reasoning using symbolic logic. We’ve been failing pathetically for decades. With LLMs you just throw the internet at it and it figures it out for itself. Personally I’ve been both in awe and also skeptical about the…
I don't think we really disagree. This is what I wrote above: "So depending how you define it, they might have some "reasoning", but so far I see 0 indications, that this is close to what humans count as reasoning." What we disagree on is only the definition of "reason". For me "reasoning" in common language implys reasoning like we humans do. And we both agree, they don't as they don't understand, what they are talk…
It's a complex and tricky issue, and everyday language is vague and easy to interpret in different ways, so it can take a wile to hash these things out.
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"I'm secure because I don't use an LLM" ... "What do you mean we got hacked via our third party vendor because they use LLMs"
I don't know why you're trying to argue, but I never said any of those things.
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These models have gone beyond the level of "token predictors". On the level of chatGPT, the model has itself, internally, acquired "concepts" that it refers to in the conversation. It "understands" concepts like "you", "me", "them" etc, and can apply it correctly (to a large part) to the entities in the conversation. I believe that answers your question. I could be wrong: errare humanum est.
A really good token predictor is still a token predictor.
Don't take my word for it, listen to Geoffrey Hinton explain it instead: https://youtu.be/qpoRO378qRY?t=1988