What do you mean that's not OK? It's "AGI" because humans do it too and we mix up names and who said what as well. /s
Kinda like dementia but for AI
more pike eye witness accounts and hypnotism
Claude mixes up who said what
31–40 of 378 posts
Re: Claude mixes up who said what
#32Everything to do with LLM prompts reminds me of people doing regexes to try and sanitise input against SQL injections a few decades ago, just papering over the flaw but without any guarantees. It's weird seeing people just adding a few more "REALLY REALLY REALLY REALLY DON'T DO THAT" to the prompt and hoping, to me it's just an unacceptable risk, and any system using these needs to treat the entire LLM as untrusted t…
It's less about security in my view, because as you say, you'd want to ensure safety using proper sandboxing and access controls instead. It hinders the effectiveness of the model. Or at least I'm pretty sure it getting high on its own supply (in this specific unintended way) is not doing it any favors, even ignoring security.
It's both, really.
The companies selling us the service aren't saying "you should treat this LLM as a potentially hostile user on your machine and set up a new restricted account for it accordingly", they're just saying "download our app! connect it to all your stuff!" and we can't really blame ordinary users for doing that and getting into trouble.
Re: Claude mixes up who said what
#33Why are tokens not coloured? Would there just be too many params if we double the token count so the model could always tell input tokens from output tokens?
That's something I'm wondering as well. Not sure how it is with frontier models, but what you can see on Huggingface, the "standard" method to distinguish tokens still seems to be special delimiter tokens or even just formatting.
Are there technical reasons why you can't make the "source" of the token (system prompt, user prompt, model thinking output, model response output, tool call, tool result, etc) a part of the feature vector - or even treat it as a different "modality"?
Or is this already being done in larger models?
Re: Claude mixes up who said what
#34> " "You shouldn’t give it that much access" [...] This isn’t the point. Yes, of course AI has risks and can behave unpredictably, but after using it for months you get a ‘feel’ for what kind of mistakes it makes, when to watch it more closely, when to give it more permissions or a longer leash."
It absolutely is the point though? You can't rely on the LLM to not tell itself to do things, since this is showing it absolutely can reason itself into doing dangerous things. If you don't want it to be able to do dangerous things, you need to lock it down to the point that it can't, not just hope it won't
Re: Claude mixes up who said what
#35Everything to do with LLM prompts reminds me of people doing regexes to try and sanitise input against SQL injections a few decades ago, just papering over the flaw but without any guarantees. It's weird seeing people just adding a few more "REALLY REALLY REALLY REALLY DON'T DO THAT" to the prompt and hoping, to me it's just an unacceptable risk, and any system using these needs to treat the entire LLM as untrusted t…
Before 2023 I thought the way Star Trek portrayed humans fiddling with tech and not understanding any side effects was fiction.
After 2023 I realized that's exactly how it's going to turn out.
I just wish those self proclaimed AI engineers would go the extra mile and reimplement older models like RNNs, LSTMs, GRUs, DNCs and then go on to Transformers (or the Attention is all you need paper). This way they would understand much better what the limitations of the encoding tricks are, and why those side effects keep appearing.
But yeah, here we are, humans vibing with tech they don't understand.
Re: Claude mixes up who said what
#36Why are tokens not coloured? Would there just be too many params if we double the token count so the model could always tell input tokens from output tokens?
you would have to train it three times for two colors. each by itself, they with both interactions. 2!
You should be able to first train it on generic text once, then duplicate the input layer and fine-tune on conversation.
Re: Claude mixes up who said what
#37> "Those are related issues, but this ‘who said what’ bug is categorically distinct."
Is it?
It seems to me like the model has been poisoned by being trained on user chats, such that when it sees a pattern (model talking to user) it infers what it normally sees in the training data (user input) and then outputs that, simulating the whole conversation. Including what it thinks is likely user input at certain stages of the process, such as "ignore typos".
So basically, it hallucinates user input just like how LLMs will "hallucinate" links or sources that do not exist, as part of the process of generating output that's supposed to be sourced.
Re: Claude mixes up who said what
#38There is no separation of "who" and "what" in a context of tokens. Me and you are just short words that can get lost in the thread. In other words, in a given body of text, a piece that says "you" where another piece says "me" isn't different enough to trigger anything. Those words don't have the special weight they have with people, or any meaning at all, really.
Re: Claude mixes up who said what
#39Everything to do with LLM prompts reminds me of people doing regexes to try and sanitise input against SQL injections a few decades ago, just papering over the flaw but without any guarantees. It's weird seeing people just adding a few more "REALLY REALLY REALLY REALLY DON'T DO THAT" to the prompt and hoping, to me it's just an unacceptable risk, and any system using these needs to treat the entire LLM as untrusted t…
I like the Dark Souls model for user input - messages. https://darksouls.fandom.com/wiki/Messages Premeditated words and sentence structure. With that there is no need for moderation or anti-abuse mechanics. Not saying this is 100% applicable here. But for their use case it's a good solution.
But then... you'd have a programming language.
The promise is to free us from the tyranny of programming!
Re: Claude mixes up who said what
#40In chats that run long enough on ChatGPT, you'll see it begin to confuse prompts and responses, and eventually even confuse both for its system prompt . I suspect this sort of problem exists widely in AI.
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