It's best not to dwell on it

ChatGPT is a tool. Use it for tasks where the cost of verifying the output is correct is less than the cost of doing it by hand.

I feel this hard with the New York Times.

99% of the time, I feel like it covers subjects adequately. It might be a bit further right than me, but for a general US source, I feel it’s rather representative.

Then they write a story about something happening to low income US people, and it’s just social and logical salad. They report, it appears as though they analytically look at data, instead of talking to people. Statisticians will tell you, and this is subtle: conclusions made at one level of detail cannot be generalized to another level of detail. Looking at data without talking with people is fallacious for social issues. The NYT needs to understand this, but meanwhile they are horrifically insensitive bordering on destructive at times.

“The jackboot only jumps down on people standing up”

• Hozier, “Jackboot Jump”

Then I read the next story and I take it as credible without much critical thought or evidence. Bias is strange.

Talking with an AI model is like talking with that one friend, that is always high that thinks they know everything. But they have a wide enough interest set that they can actually piece together an idea, most of the time wrong, about any subject.

I love that this mirrors the experience of experts on social media like reddit, which was used for training chatgpt...

If it's being designed to answer questions, then it should simply be an advanced search engine that points to actual researched content.

The way it acts now, it's trying to be an expert based one "something a friend of a friend said", and that makes it confidently wrong far too often.

First off, the beauty of these two posts being beside each other is palpable.

Second, as you can see on the picture, it's more like 60%

If the standard is replicating human level intelligence and behavior, making up shit just to get you to go away about 40% of the time kind of checks out. In fact, I bet it hallucinates less and is wrong less often than most people you work with

40% seems low

One thing I have found it to be useful for is changing the tone if what I write.

I tend to write very clinicaly because my job involves a lot of that style of writing. I have started asked chat gpt to rephrase what i write in a softer tone.

Not for everything, but for example when Im texting my girlfriend who is feeling insecure. It has helped me a lot! I always read thrugh it to make sure it did not change any of the meaning or add anything, but so far it has been pretty good at changing the tone.

Also use it to rephrase emails at work to make it sound more professional.

I have frequentley seen gpt give a wrong answer to a question, get told that its incorrect, and the bot fights with me and insists Im wrong. and on other less serious matters Ive seen it immediatley fold and take any answer I give it as "correct"

I use chatgpt as a suggestion. Like an aid to whatever it is that I’m doing. It either helps me or it doesn’t, but I always have my critical thinking hat on.

I did a google search to find out how much i pay for water, the water department where I live bills by the MCF (1,000 cubic feet). The AI Overview told me an MCF was one million cubic feet. It's a unit of measurement. It's not subjective, not an opinion and AI still got it wrong.

Exactly my thoughts.

come on guys, the joke is right there.... 60% of the time it works, every time!

I've been using o3-mini mostly for ffmpeg command lines. And a bit of sed. And it hasn't been terrible, it's a good way to learn stuff I can't decipher from the man pages. Not sure what else it's good for tbh, but at least I can test and understand what it's doing before running the code.

does chat gpt have ADHD?

same with every documentary out there

Deepseek is pretty good tbh. The answers sometimes leave out information in a way that is misleading, but targeted follow up questions can clarify.

This, but for tech bros.

I just use it to write emails, so I declare the facts to the LLM and tell it to write an email based on that and the context of the email. Works pretty well but doesn't really sound like something I wrote, it adds too much emotion.

Exactly this is why I have a love/hate relationship with just about any LLM.

I love it most for generating code samples (small enough that I can manually check them, not entire files/projects) and re-writing existing text, again small enough to verify everything. Common theme being that I have to re-read its output a few times, to make 100% sure it hasn't made some random mistake.

I'm not entirely sure we're going to resolve this without additional technology, outside of 'the LLM'-itself.

i mainly use it for fact checking sources from the internet and looking for bias. i double check everything of course. beyond that its good for rule checking for MTG commander games, and deck building. i mainly use it for its search function.

If you want an AI to be an expert, you should only feed it data from experts. But these are trained on so much more. So much garbage.

I think that AI has now reached the point where it can deceive people ,not equal to humanity.

This, but for Wikipedia.

Edit: Ironically, the down votes are really driving home the point in the OP. When you aren't an expert in a subject, you're incapable of recognizing the flaws in someone's discussion, whether it's an LLM or Wikipedia. Just like the GPT bros defending the LLM's inaccuracies because they lack the knowledge to recognize them, we've got Wiki bros defending Wikipedia's inaccuracies because they lack the knowledge to recognize them. At the end of the day, neither one is a reliable source for information.

Oof let's see, what am I an expert in? Probably system design - I work at (insert big tech) and run a system design club there every Friday. I use ChatGPT to bounce ideas and find holes in my design planning before each session.

Does it make mistakes? Not really? it has a hard time getting creative with nuanced examples (i.e. if you ask it to "give practical examples where the time/accuracy tradeoff in Flink is important" it can't come up with more than 1 or 2 truly distinct examples) but it's never wrong.

The only times it's blatantly wrong is when it hallucinates due to lack of context (or oversaturated context). But you can kind of tell something doesn't make sense and prod followups.

Tl;dr funny meme, would be funnier if true