this post was submitted on 26 Sep 2025
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Source: https://mastodon.social/@Daojoan/115259068665906083

As a reminder, "hallucinations" are inevitable in LLMs

Explanation of hallucinations from 2023

I always struggle a bit with I'm asked about the "hallucination problem" in LLMs. Because, in some sense, hallucination is all LLMs do. They are dream machines.

We direct their dreams with prompts. The prompts start the dream, and based on the LLM's hazy recollection of its training documents, most of the time the result goes someplace useful.

It's only when the dreams go into deemed factually incorrect territory that we label it a "hallucination". It looks like a bug, but it's just the LLM doing what it always does.

At the other end of the extreme consider a search engine. It takes the prompt and just returns one of the most similar "training documents" it has in its database, verbatim. You could say that this search engine has a "creativity problem" - it will never respond with something new. An LLM is 100% dreaming and has the hallucination problem. A search engine is 0% dreaming and has the creativity problem.

All that said, I realize that what people actually mean is they don't want an LLM Assistant (a product like ChatGPT etc.) to hallucinate. An LLM Assistant is a lot more complex system than just the LLM itself, even if one is at the heart of it. There are many ways to mitigate hallucinations in these systems - using Retrieval Augmented Generation (RAG) to more strongly anchor the dreams in real data through in-context learning is maybe the most common one. Disagreements between multiple samples, reflection, verification chains. Decoding uncertainty from activations. Tool use. All an active and very interesting areas of research.

TLDR I know I'm being super pedantic but the LLM has no "hallucination problem". Hallucination is not a bug, it is LLM's greatest feature. The LLM Assistant has a hallucination problem, and we should fix it.

Okay I feel much better now :)

Explanation source: https://xcancel.com/karpathy/status/1733299213503787018

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[–] RedWizard@hexbear.net 17 points 3 weeks ago (3 children)

I'd just like to interject for a moment. What you're referring to as hallucinations is, in fact, a missunderstanding of LLMs/LLM Assistants, or, as I've recently taken to calling it, the "creativity vs. accuracy problem." Hallucinations are not an issue unto themselves but rather the expected behavior of a fully functioning LLM made useful by an LLM Assistant, a system often more complex than just the LLM itself, comprised of a GUI frontend and systems and logic backend that simulates the experience of conversational interaction utilizing an LLM.

Many AI users are consuming the hallucinations of an LLM system every day without realizing it. Through a peculiar turn of events, the term hallucinations, which is widely used today, is often used to identify when the output goes into deemed factually incorrect territory, and many of its users are not aware that LLMs are basically dream machines, where we direct their dreams with prompts. The prompts start the dream, and based on the LLM's hazy recollection of its training documents, most of the time the result goes someplace useful.

There really are hallucinations, and these people are consuming them, but it is just a natural byproduct of the system, not a "bug," but just the LLM doing what it always does. LLMs do not have a "hallucination problem" because, in some sense, hallucination is all LLMs do. The LLM is an essential part of the whole system but not as useful by itself; it can only become more useful in the context of a LLM Assistant. There are many ways to mitigate hallucinations in these systems - using Retrieval Augmented Generation (RAG) to more strongly anchor the dreams in real data through in-context learning is maybe the most common one. Disagreements between multiple samples, reflection, verification chains. Decoding uncertainty from activations. Tool use. All an active and very interesting areas of research.

All that said, I realize that what people actually mean is they don't want an LLM Assistant (a product like ChatGPT etc.) to hallucinate. I know I'm being super pedantic but the LLM has no "hallucination problem." Hallucination is not a bug; it is LLM's greatest feature. The LLM Assistant has a hallucination problem, and we should fix it.

[–] peeonyou@hexbear.net 5 points 3 weeks ago (1 children)

how do you consume hallucinations? jfc

[–] RedWizard@hexbear.net 9 points 3 weeks ago