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ch_smtoday at 3:26 PM5 repliesview on HN

here‘s what i don‘t get about this whole discussion. AI companies already store all prompts and responses for future training.

just make an API that returns the string distance between a previously generated paragraph and the query?

that would sidestep this whole problem class.

regulators could even specify how that has to work.

what am i missing?


Replies

mirashiitoday at 4:14 PM

> AI companies already store all prompts and responses for future training.

They store some prompts and responses, not all, that's what you're missing.

bonoboTPtoday at 4:56 PM

> AI companies already store all prompts and responses for future training.

They claim to only do this when you agree to this in your personal settings. Though Google does say they will train on it, unless you disable history and only use ephemeral chats. Anthropic has a setting for it and claims not to train by default.

Also it would be vulnerable to attacks and privacy problems. You could search for substrings about some suspected information, like "John Smith's medical records show advanced cancer" etc. Of course you'd have to guess the phrasing but still.

echoangletoday at 5:07 PM

Wouldn't this become pretty difficult to do at scale over time? Is there a way to compare the similarity in a database of responses without doing a search over every entry and comparing them? Because that would probably become pretty slow if literally every LLM output is saved and has to be scanned.

johnnyotoday at 5:02 PM

1. AI company buys and trains on an author’s book when it gets published, it’s now part of the training data.

2. Attacker asks the LLM for the opening sentences of the book, it goes into the generated responses database.

3. Later, a malicious user shows that the first few sentences of the authors book are identical to a previously generated response.

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dpoloncsaktoday at 3:30 PM

Local models?

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