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by AceJohnny21 hours ago |
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upvoteby ed_elliott_asc1 hours ago|
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The soothing sound of ChatGPT telling us how right and clever we are…how could it possibly hallucinate, certainly not 5.5
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upvoteby john-tells-all1 hours ago|
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There's a big difference between a _puzzle_ and a _mystery_. In a puzzle, the goal state is known, and as more pieces - data - appears, the goal gets closer. You know how far you are from the goal.

A mystery is worse. With each additional piece of data, the goal gets farther away. Everything is more and more confusing.

(Popularized by Malcom Gladwell)

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upvoteby Aurornis1 hours ago|
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I have multiple LLM subscriptions at any given time, plus an array of local models.

When I ask a question outside of my domain of expertise I like to ask all of the LLMs I have access to. I also create separate sessions and ask the same question multiple ways.

It’s revealing to see how many different and contradictory answers I get, most of which are presented confidently.

The last time I ran a medical question through Claude I couldn’t even get consistent answers between sessions.

It’s also scary how easily you can lead each LLM to the answer you have in mind. When I would start asking questions about different options that other LLMs had presented, each session would drift toward that explanation.

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upvoteby 0101010101011 hours ago|
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> The solution to uncertain information isn't more information, which the AI can certainly provide, it's better information, and AI cannot currently provide that.

I'd argue that AI _can_ currently provide that, but that it can't do it _reliably_, and that to non-experts it's impossible to differentiate, which makes it all the more dangerous.

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upvoteby margorczynski1 hours ago|
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Isn't that the case with human "experts"? If you had encounters with doctors, mechanics, etc. you'll know you can get a completely different diagnosis for the same problem which obviously means (in most cases) that the person you thought an expert is wrong.

What is needed are studies that will take a cold look at the actual results because AI seems to be required to be perfect or it is useless. It just needs to be as good as a human for most stuff, but in the long run it will be much better. At least that what extrapolating current reality shows us.

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