Comment by x3haloed
13 hours ago
This topic is bringing out the hallucination-panic crowd.
It's perfectly safe to use LLMs to surface underlying data and knowledge without having to trust that it's giving you correct advice.
Use the LLM as search technology: string match -> semantic search -> search intelligence.
This is especially helpful when you don't know the right question to ask. Semantics only help you find text that is semantically near the input query. Semantics won't help you when what you are looking for is connected to what you have by something other than semantics, like causation, mechanism, or interpretation.
Trying to figure out why your crops aren't growing well will likely require you to read several articles across a range of sciences, probably scoped to the specific conditions you are dealing with. A semantic search is not going to surface those first.
Allowing an LLM to chain together several sources for you to read first does not require you to ask it for a conclusion.
The readme on Github does say the system produces hallucinated sources https://github.com/anonnerdfrenzy/survival-llm#how-the-model..., but really you're correct, for this kind of highly targeted use case the LLM's summary could probably be ignored entirely and the system could work extremely well even just as a search engine: index all of the content up front, chunked by paragraph and maybe enriched with a HyDE step, have the LLM facilitate running a handful of hybrid keyword/semantic searches based on the user's question and reranking the results, and show the exact pieces of text in the corpus that are most responsive to their question. No summary needed.
Not sure what the LLM is adding there then other than injecting a step into your search that could hallucinate.
A great strength of LLMs is how they provide useful answers even if the prompt has glaring spelling or grammatical mistakes. If your prompt is not great, as you said, they will reply in a way that helps you identify that flaws, and learn how to steer the model better.
They're amazingly useful tools, but they're nowhere the level believers want them to be, not yet.
Yes this has been very useful for me this week. I trapped my middle finger on my right hand in a door and it really messed up my typing.
I tried using dictation but I really disliked speaking to it.
You can write a really messed up sentence and it almost always worked out what I meant.
Quite amazing actually
The summarization is the main issue here. A fuzzy search is far less controversial. The LLM companies have done a good job synonymizing "AI" with their products however.
In a true emergency, there are often many cases where you need not just information retrieval, but "thinking and reasoning" to deal with unprecedented situations, right? Is it technically possible to balance lightweight local performance with thinking capability, while avoiding the risk of hallucinations in life-or-death instructions?
Can a bad LM implementation surface bad references? Yes. Are LMs overwhelmingly useful for research? Yes.
Is a bad LM implementation still useful for research? Shmaybe.
But at this point why even bring a full model into scope in the first place.. just run some cheap embedding retriever
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Nevermind hallucinations, the donkey-work is important; why bypass the hours of research, which trains our in-built LLM and can lead to new realizations, and get the carrot without much effort? This LLM stuff feels like a candybar; the anticipation of the magic feels good, the thing tastes good while you're eating it, and everything thereafter is shit, but we easily forget, and reach for the next candybar. I appreciated Blindboy Boatclub's take in his podcast episode "Artificial intelligence is Disgusting and it will never replace Artists" from 2026 March 17. I also appreciate Electrical Engineer & Computer Scientist Timnit Gebru's perspective on these stochastic parrots. While intraspecies diversity confers, up to a point, a survival benefit, consider the long-term consequences of playing this particular game. We don't have to eat every candybar the rich mostly-guys ply us with.
The premise in this case is to get answers quickly in an emergency situation. You don’t want to tell the person with a burn injury to wait a bit since you always wanted to learn how burns are treated.
You also don’t want to get advice like that cooking advice to make a glue pizza.