Can absolutely never blindly trust the hallucinating plagiarism machine.
It’s great where either facts don’t matter or you’re personally in a position to vet all of its “factual” output 100%. Text revision, prompting for additional perspectives, prompting to challenge beliefs and identify gaps. Reformatting, quick and easy data extraction, outlining, brainstorming.
In most cases I’ve seen AI used, the person spends as much time correcting it than they would if they just did the work without AI. So maybe it makes you feel more productive because a bunch of stuff happens all at once, but at least for text generation, I think it’s more of a placebo.
You cannot in all seriousness use a LLM as a research tool. That is explicitly not what it is useful for. A LLM’s latent space is like a person’s memory : sure there is some accurate data in there, but also a lot of “misremembered” or “misinterpreted” facts, and some bullshit.
Think of it like a reasoning engine. Provide it some data which you have researched yourself, and ask it to aggregate it, or summarize it, you’ll get some great results. But asking it to “do the research for you” is plain stupid. If you’re going to query a probabilistic machine for accurate information, you’d be better off rolling dice.
Exactly my point - except that the word “reasoning” is far too generous, as it implies that there would be some way for it to guarantee that its logic is sound, not just highly resembling legible text.
I don’t understand. Have you ever worked an office job? Most humans have no way to guarantee their logic is sound yet they are the ones who do all of the reasoning on earth. Why would you have higher standards for a machine?
This question betrays either your non-use or misuse of the products available. You’re either just reading the headlines of the screw-ups or you’re just bad at using the tool.
To directly answer your question:
Quick scripts in a variety of languages. Tested before being used on real data/systems.
Creating visual graphs of data in python and Jupyter notebooks with no prior knowledge of python itself or the tools it’s running. In this case, I was able to update the way I wanted it to look in natural language, have it suggest code changes, and immediately try them in the notebook with great results.
Improving the sentiment of correspondence. Proofread before sending. It has better grammar and flow than a surprising number of correspondences I’ve come across at work. Sure, English may be their second language but it doesn’t change the fact.
Quickly finding documentation pertaining to the query which, yes, you need to go read to verify any answers any LLM provides. Anyone using it regularly should know this by now.
Quick “do this in command line. What options are required” which is then immediately tested.
In one case, a news story was referenced in passing in a podcast I listen to. It stuck with me days later and I wanted to find actual articles written about it. I was able to describe what I was looking for in natural language and included as many details as I could remember and asked it to find articles for me. I found exactly what I was after.
But were you actually looking for a real response to your question?
It’s worse at all programming tasks except boilerplate, especially with its tendency to inject booby traps. Not knowing how to use the programming language it emits becomes a significant problem.
Comparing a language model to an idiot is unfair to the idiot.
A normal search engine works for everything else.
Any well-defined query I’ve ever made of an LLM has resulted in hilariously bad results, but I suppose I was expecting it to do something that I couldn’t already do better myself.
I’m a systems administrator, not a programmer. Like I said, quick scripts. An LLM could probably parse my comment better than you, evidently.
Comparing a language model to an idiot is unfair to the idiot.
Oof… Was this in reply to my bit about better grammar and ESL individuals?
A normal search engine works for everything else.
Fuck no. Especially the python visualization point.
Any well-defined query I’ve ever made of an LLM has resulted in hilariously bad results, but I suppose I was expecting it to do something that I couldn’t already do better myself.
I suppose you’re just a god among men then. For the rest of us, it’s useful and you’ve been given plenty of good answers to your disingenuous question.
I don’t really query, but it’s good enough at code generation to be occasionally useful. If it can spit out 100 lines of code that is generally reasonable, it’s faster to adjust the generated code than to write it all from scratch. More generally, it’s good for generating responses whose content and structure are easy to verify (like a question you already know the answer to), with the value being in the time saved rather than the content itself.
Nope, just gotta know what it IS, what it ISN’T, and how to correctly write prompts for it to return data that you can use to formulate your own conclusion.
When using AI, it’s only as smart as the operator.
No you don’t understand. The word AI, which was invented to describe this kind of technology, should not be used to describe this technology. It should instead be reserved for some imaginary magical technology that may exist in the future.
In what ways are you benefiting from a bevy of factually dubious query responses?
Can absolutely never blindly trust the hallucinating plagiarism machine.
It’s great where either facts don’t matter or you’re personally in a position to vet all of its “factual” output 100%. Text revision, prompting for additional perspectives, prompting to challenge beliefs and identify gaps. Reformatting, quick and easy data extraction, outlining, brainstorming.
Reformatting and outlining as long as you go over and revise it again anyway, seemingly making that moot.
Data extraction as long as you don’t care if the data is mangled.
Brainstorming is a good one, since off-the-wall ideas can be useful in that context.
In most cases I’ve seen AI used, the person spends as much time correcting it than they would if they just did the work without AI. So maybe it makes you feel more productive because a bunch of stuff happens all at once, but at least for text generation, I think it’s more of a placebo.
It can at least get one unstuck, past an indecision paralysis, or give an outline of an idea. It can also be useful for searching though data.
If all I want is something blatantly false or legible yet nonsensical, like a modern lorem ipsum, it’s a real time-saver.
Why not just use lorem ipsum? It’s just a copy/paste, and without the liability of having false information if you forget to proofread it.
I guess ChatGPT is just completely useless, then.
You cannot in all seriousness use a LLM as a research tool. That is explicitly not what it is useful for. A LLM’s latent space is like a person’s memory : sure there is some accurate data in there, but also a lot of “misremembered” or “misinterpreted” facts, and some bullshit.
Think of it like a reasoning engine. Provide it some data which you have researched yourself, and ask it to aggregate it, or summarize it, you’ll get some great results. But asking it to “do the research for you” is plain stupid. If you’re going to query a probabilistic machine for accurate information, you’d be better off rolling dice.
Exactly my point - except that the word “reasoning” is far too generous, as it implies that there would be some way for it to guarantee that its logic is sound, not just highly resembling legible text.
I don’t understand. Have you ever worked an office job? Most humans have no way to guarantee their logic is sound yet they are the ones who do all of the reasoning on earth. Why would you have higher standards for a machine?
I have higher expectations for machines than humans, yes.
Sounds like a recipe for disappointment tbh. But on the other hand, sounds like you trust techno marketing a bit too much.
No, I just know how to spot the lies in a datasheet.
I"m not sure what lie and what datasheet you’re referring to ?
Just in general.
This question betrays either your non-use or misuse of the products available. You’re either just reading the headlines of the screw-ups or you’re just bad at using the tool.
To directly answer your question:
But were you actually looking for a real response to your question?
It’s worse at all programming tasks except boilerplate, especially with its tendency to inject booby traps. Not knowing how to use the programming language it emits becomes a significant problem.
Comparing a language model to an idiot is unfair to the idiot.
A normal search engine works for everything else.
Any well-defined query I’ve ever made of an LLM has resulted in hilariously bad results, but I suppose I was expecting it to do something that I couldn’t already do better myself.
I’m a systems administrator, not a programmer. Like I said, quick scripts. An LLM could probably parse my comment better than you, evidently.
Oof… Was this in reply to my bit about better grammar and ESL individuals?
Fuck no. Especially the python visualization point.
I suppose you’re just a god among men then. For the rest of us, it’s useful and you’ve been given plenty of good answers to your disingenuous question.
I don’t really query, but it’s good enough at code generation to be occasionally useful. If it can spit out 100 lines of code that is generally reasonable, it’s faster to adjust the generated code than to write it all from scratch. More generally, it’s good for generating responses whose content and structure are easy to verify (like a question you already know the answer to), with the value being in the time saved rather than the content itself.
It’s good at regurgitating boilerplate, from what I’ve gathered.
Someone doesn’t know how to use ChatGPT
Oh, is there an arcane invocation that magically imbues it with reason?
Nope, just gotta know what it IS, what it ISN’T, and how to correctly write prompts for it to return data that you can use to formulate your own conclusion.
When using AI, it’s only as smart as the operator.
Well, it’s not AI, for starters.
As much as I hate to do this, it is AI, as ML is a part of Artificial Intelligence.
It isn’t AGI, some might say it may be, but they are wrong. But the model is learning.
An LLM is not capable of learning. It won’t hallucinate less with additional training input.
Just the notion of a computer having hallucinations should suggest that it’s doing more than just basic code.
It’s not ‘intelligent’, but it has ‘learned’ enough beyond standard CPU instructions.
That’s why it’s not a General AI, but it’s still an AI.
I also talk about gremlins inside CPUs, but that doesn’t mean I think there are magical critters turning a crank inside them.
It’s called a metaphor, brother.
Regardless, it’s all code that’s eventually run on a CPU, so there isn’t any step where magic is injected.
Keep going…
No you don’t understand. The word AI, which was invented to describe this kind of technology, should not be used to describe this technology. It should instead be reserved for some imaginary magical technology that may exist in the future.
From what I’ve seen online, most people differentiate between AI and AGI, which is cool.
So then don’t call it AI.
I thought the sarcasm in my comment was self evident 🤔
New version of people who know how to search the web vs those who don’t. Currently shit search results broken by search companies notwithstanding.