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this post was submitted on 15 Nov 2024
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There are guardrails in place to avoid providing the user illegal and hateful information to the en user and specially to avoid situations like that (well not all companies do, but you can expect Google to have it in place),
I wonder: 1- How did the LLM hallucinate so much to generate that answer out of the blues given the previous context. 2- Why did the guardrails failed blocking this such obvious undesired output.
This probably isn't a hallucination in the classic sense.
This is probably a near copy of a forum post where a user was channeling fight club and trying to be funny. The same as the putting glue on pizza thing.
And guardrails don't work very well. They're good at detection tone but much worse at detection content. So an appropriately guardrailed LLM will never call someone a "fucking ######" but it'll keep telling everyone that segalis have an IQ of 40 until there's such a PR backlash that an updated is needed.
They work well enough, Google has just done a very shitty job with their AI. Quite the disappointment considering how innovative Google used to be. Now it's all about maximum profits at minimum cost for them, and nothing else. Well, nothing else except racism.
They would need general AI to police the LLM AI. Otherwise LLMs will keep serving up crap because their input data set is full of crap.
It's not just that the input data is crap. Mostly the issue is that an LLM is a glorified autocomplete. The core of the technology is making grammatically correct sentences. It has no concept of facts or logic. Any impression that it does is just an illusion borne of the word probabilities baked in.
LLMs are a remarkable example of brute-forcing a solution to a problem, but it's this same brute force that makes me doubt it'll ever reach the next level.
As someone that works in AI, most of what Lemmy writes about LLM's is hilariously wrong. This, however, is very right, and what amazes me is that every big tech company had made this realisation - yet doesn't give a fuck. Pre-LLM's, we knew that manual patching and intervention wasn't a scalable solution, and we knew that LLM's were prone to hallucinations, but ChatGPT showed companies that people often don't care if the answer is wrong. Fuck it, let's just patch this shit as we go...
But when this shit happens, oh boy, do I feel for the poor engineers and scientists on-call that need to fix this shit regularly...
And name it "Deckard" for maximum concentrated cringe
I think you are asking the right questions, IMO. It isn't out of the ordinary for this kind of thing go happen there are for sure prevention methods used.
I am far more interested in the failure than the statement itself.
As I said, these things happen when the company uses AI mainly as a tool to obtain data from the user, leaving aside the reliability of its LLM, which allows it to practically collect data indiscriminately for its knowledge base. This is why ChatBots are generally discardable as a reliable source of information. Search assistants are different, like Andi, since they do not get their information from their own knowledge base, but in real time from the web, there it only depends on whether they know how to recognize the reliability of the information, which Andi does, contrasting several sources. This is why it offers the highest accuracy of all major AI, according to an independent benchmark.
I hate that Lemmy is being infiltrated by AI ad spam now too :’(