The takeaway from all LLM-based AI is the user needs to be smart enough to do whatever they’re asking anyway. All output needs to be verified before being used or relied upon.
The “AI” is just streamlining the process to save time.
Relying on it otherwise is stupid and just proves instantly that you are incompetent.
Relying on it otherwise is stupid and just proves instantly that you are incompetent.
Relying on it in any circumstances (though medical stuff is understandable if you’re simply too poor or don’t have access) while it is exhausting water supplies and polluting the planet is stupid and instantly proves that you are stupid and inconsiderate.
the user needs to be smart enough to do whatever they’re asking anyway
I’m gonna say that’s ideal but not quite necessary. What’s needed is that the user is capable of properly verifying the output. Which anyone who could do it themselves definitely can, but it can be done more broadly. It’s an easier skill to verify a result than it is to obtain that result. Think: how film critics don’t necessarily need to be filmmakers, or the P=NP question in computer science.
This is where domain expertise would come in, no? It’s speeding up the work but it usually outputs generic content, and whatever else it injects while hallucinating. Therefore the validation part holds up I’d say.
But if the output has issues, what’re you going to do, prompt it again? If you are only able to verify but not do the task, you cannot correct the AI’s mistakes yourself.
If you’re unable to brute-force verification (research, testing, consulting the ancient texts), there’s where you stop what you’re doing, and take a breath. Then, consult an expert. Just like the film critic analogy, it’s easier to verify than to create, so you’re saving the expert time and effort while learning about something that you were obviously already passionate enough about to have started this endeavor.
At the risk of sounding like an overly obsequious AI… You know what, you’re completely right. I’m honestly not sure what use case I was imagining when I wrote that last comment.
You were thinking logically about a normal production chain. In that case, QA or whoever says “This is wrong, rework it and correct the issue” and that’s that. With AI, it does the whole thing over again and may or may not come back with the same issue or an entirely new one.
Making text flow naturally, grouping and ordeeing information, good writing.
You can verify two textst have the same facts and information, yet one reads way better than the other. But writing a text that reads well is quite hard.
The takeaway from all LLM-based AI is the user needs to be smart enough to do whatever they’re asking anyway. All output needs to be verified before being used or relied upon.
The “AI” is just streamlining the process to save time.
Relying on it otherwise is stupid and just proves instantly that you are incompetent.
This is absolutely the case, and honestly, at least for now how it needs to be across the board.
Noone should be using AI to do things you’re incapable of doing (or undoing).
Relying on it in any circumstances (though medical stuff is understandable if you’re simply too poor or don’t have access) while it is exhausting water supplies and polluting the planet is stupid and instantly proves that you are stupid and inconsiderate.
I’m gonna say that’s ideal but not quite necessary. What’s needed is that the user is capable of properly verifying the output. Which anyone who could do it themselves definitely can, but it can be done more broadly. It’s an easier skill to verify a result than it is to obtain that result. Think: how film critics don’t necessarily need to be filmmakers, or the P=NP question in computer science.
This is where domain expertise would come in, no? It’s speeding up the work but it usually outputs generic content, and whatever else it injects while hallucinating. Therefore the validation part holds up I’d say.
But if the output has issues, what’re you going to do, prompt it again? If you are only able to verify but not do the task, you cannot correct the AI’s mistakes yourself.
If you’re unable to brute-force verification (research, testing, consulting the ancient texts), there’s where you stop what you’re doing, and take a breath. Then, consult an expert. Just like the film critic analogy, it’s easier to verify than to create, so you’re saving the expert time and effort while learning about something that you were obviously already passionate enough about to have started this endeavor.
I can’t draw, but I could probably photoshop out some minor issues in an AI-generated image.
At the risk of sounding like an overly obsequious AI… You know what, you’re completely right. I’m honestly not sure what use case I was imagining when I wrote that last comment.
You were thinking logically about a normal production chain. In that case, QA or whoever says “This is wrong, rework it and correct the issue” and that’s that. With AI, it does the whole thing over again and may or may not come back with the same issue or an entirely new one.
Making text flow naturally, grouping and ordeeing information, good writing.
You can verify two textst have the same facts and information, yet one reads way better than the other. But writing a text that reads well is quite hard.
If you don’t habe the ability then you would do what you would have 5 years ago: not do it
Either submit without, or not submit at all.