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I’m convinced people who can’t tell when a chat bot is hallucinating are also bad at telling whether something else they’re reading is true or not. What online are you reading that you’re not fact checking anyway? If you’re writing a report you don’t pull the first fact you find and call it good, you need to find a couple citations for it. If you’re writing code, you don’t just write the program and assume it’s correct, you test it. It’s just a tool and I think most people are coping because they’re bad at using it

I just tried out Gemini.

I asked it several questions in the form of 'are there any things of category x which also are in category y?' type questions.

It would often confidently reply 'No, here's a summary of things that meet all your conditions to fall into category x, but sadly none also fall into category y'.

Then I would reply, 'wait, you don't know about thing gamma, which does fall into both x and y?'

To which it would reply 'Wow, you're right! It turns out gamma does fall into x and y' and then give a bit of a description of how/why that is the case.

After that, I would say '... so you... lied to me. ok. well anyway, please further describe thing gamma that you previously said you did not know about, but now say that you do know about.'

And that is where it gets ... fun?

It always starts with an apology template.

Then, if its some kind of topic that has almost certainly been manually dissuaded from talking about, it then lies again and says 'actually, I do not know about thing gamma, even though I just told you I did'.

If it is not a topic that it has been manually dissuaded from talking about, it does the apology template and then also further summarizes thing gamma.

...

I asked it 'do you write code?' and it gave a moderately lengthy explanation of how it is comprised of code, but does not write its own code.

Cool, not really what I asked. Then command 'write an implementation of bogo sort in python 3.'

... and then it does that.

...

Awesome. Hooray. Billions and billions of dollars for a shitty way to reform web search results into a coversational form, which is very often confidently wrong and misleading.

I beg someone to help me. There is this new guy at my workplace, officially as a developer who can't write code at all. He has pasted an entire project I did into ChatGPT with "optimize this" and pull requested it. I swear.

Because of I haven't found anyone asking the same question on a search index, ChatGPT won't tell me to just use Google or close my question as a duplicate when it's not a duplicate.

Reminder that all these Chat-formatted LLMs are just text-completion engines trained on text formatted like a chat. You're not having a conversation with it, it's "completing" the chat history you're providing it. By randomly(!) choosing the next text tokens that seems like they best fit the text provided.

If you don't directly provide, in the chat history and/or the text completion prompt, the information you're trying to retrieve, you're essentially fishing for text in a sea of random text tokens that seems like it fits the question.

It will always complete the text, even if the tokens it chooses minimally fit the context, it chooses the best text it can but it will always complete the text.

This is how they work, and anything else is usually the company putting in a bunch of guide bumpers to reformat prompts into coaxing the models to respond in a "smarter" way (see GPT-4o and "chain of reasoning")

sigh people do talk about this, they complain about it non-stop. These same people probably aren't using it as intended, or are deliberately trying to farm a "gotcha" response. AI is a very neat tool which can do a lot of things well, but it's important to recognize its limitations. I don't use it for things I don't understand because I won't recognize if it's spitting out nonsense, but for topics I do understand it's hard to overstate how efficient and time saving it is.

Because in a lot of applications you can bypass hallucinations.

• getting sources for something
• as a jump off point for a topic
• to get a second opinion
• to help argue for r against your position on a topic
• get information in a specific format

In all these applications you can bypass hallucinations because either it's task is non-factual, or it's verifiable while promoting, or because you will be able to verify in any of the superseding tasks.

Just because it makes shit up sometimes doesn't mean it's useless. Like an idiot friend, you can still ask it for opinions or something and it will definitely start you off somewhere helpful.

Depending on the task, it’s quicker to verify the AI response than work through the blank page phase.

Because most people are too lazy to bother with making sure the results are accurate when they sound plausible. They want to believe the hype, and lack critical thinking.

Probably because they're not checking them

My job uses a data science platform that has a special ai assistant trained on its own docs.

The first time I tried using it, it used the wrong language. The second time I used it, it was hallucinating its own functions, but after looking up the docs I told it what function to use and it gave me code that worked

I have not used it a third time. I don’t think i will.

I only use it for complex searches with results I can usually parse myself like ''list 30 typical household items without descriptions or explainations with no repeating items'' kind of thing.

They don't give you the answer, they give you a rough idea of where to look for the answer.

I've used them to generate chunks of boilerplate code that was 80% of what I needed, because I knew what I needed and wanted to save time.

It's usually good for ecosystems with good and loads of docs. Whenever docs are scarce the results become shitty. To me it's mostly a more targeted search engine without the crap (for now)

The only reason i use ChatGPT for some quick stuff is just that search engines suck so bad.

Big businesses know, they even ask people like me to add extra measures in place. I like to call it the concorde effect. Youre trying to make a plane that can shove air out of the way faster than it wants to move, and this takes an enormous amount of energy that isn't worth the time save, or the cost. Even if you have higher airspeed when it works, if your plane doesn't make it to destination it isn't "faster".

We hear a lot about the downsides of AI, except that doesn't fit the big corpo narrative and people don't care enough really. If youre just a consumer who has no idea how this really works, the investments companiess make into shoving it everywhere makes it seem like it's not a problem and it looks like there's only AI hype and no party poopers.

Treat it like a janitor rather than an answer machine and you'll have a better time. I call it my bitch bot.

They're trying not to lose money on the developments

It depends upon what you use ChatGPT for and if you know how to use it productively. For example if I ask ChatGPT coding questions it is often very helpful. If I ask it history questions it constantly makes things up. You also again need to know how to use it, like people who claim ChatGPT is not helpful for coding you ask them how they use it and they basically just ask ChatGPT to do their whole project for them and when it fails they claim it is useless. But that's not the productive way to use it, the productive way to use it is like a replacement for StackOverflow or to provide you examples of how to use some library, or things like that, not doing your whole project for you. Of course, people often use it incorrectly so it's probably not a good idea to allow its use in the workplace, but for individual use it can be very helpful.

What are you talking about? We mention this on a daily basis. That's the #1 complaint about ChatGPT when used for factual purposes