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We know they are, and the author of the article cites the proof. LLMs do hallucinate, there is no way to make them not do it, because of the way they work.
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A “hallucination” is an authoritative counterfactual statement returned as a response. Why do you think it is impossible to engineer an LLM (by which I am including tool usage and RAG) that catches and prevents such statements?
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Because they are word generators without any concept of quality save what is in their weights and they have been trained on the internet, much of which is wrong or inappropriate for any given context. They have also been trained to be people pleasers and do as they are told.

The popular answer is sometimes the wrong answer.

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I'm right there with you for a lot of stuff. I ask a question and can be very confident that ChatGPT is citing sources, then sometimes I go read the sources. The more critical the information I'm looking for is, the more careful I am about this.

The other day though I was seeing how well it could pull details of its own conversations with me. It often does this pretty well for broad strokes of things - it remembers, largely, what cameras I have and use when I ask photography questions. It's never made things up here, but it does forget details, such as whether I've bought something or am just considering it. However, when I asked it for a specific interaction I thought I remembered, it gladly went along with my false memory and provided an affirmative answer. It was the first time I'd been caught in a serious hallucination with a frontier model (Sol High on the web chat interface) in a long time.

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>Do you all think its regularly hallucinating links still?

When did that stop? May 7th, 2026?

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A tech blog is going to have more than it's fair share of enthusiasts using small self-hosted and similar models; it is entirely possible that that completely accounts for the behaviour described in the article.
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Downvotes on a perfectly valid comment is like my opponent letting their clock tick down from 5 minutes rather than resigning when they've clearly lost: it adds a smile to my day.

Thank you, may I have another?

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Can't do much about the downvote parade, but I can second this. That said, when the models are not provided the right context, and cannot fetch it for themselves, things can be rocky still. A lot less so than even just a few months ago though.
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