That drives me mad. “Oh, you don’t find AI that useful for developement? You should learn how to talk to it.”. Wasn’t that the point, that it would understand me?
Meh, that was the sales pitch. But name one tool in development that actually does what the sales pitch claimed.
Knowing how to get useful info out of AI does involve knowing how to talk to it. Just like getting the most out of gitlab means knowing how they intend for you to organize your jobs. So AI is just like every other tool, overhyped, underdelivering, and has “some” use.
Ask the model to confirm the answer and it will correct itself, at least when I’ve tried that.
I’m sure there’s a mathematical or programmatic logic as to why, but seeing as I don’t need LLM’s to count letters or invent new types of pseudoscience, I’m not overly interested in it.
If I can’t rely on a system to perform simple tasks I can easily validate, I’m not sure why I’d trust it to perform complex tasks I would struggle to verify.
Imagine a calculator that reported “1+1=3”. It seems silly to use such a machine to do long division.
That’s my point, I don’t use LLMs for those operations, and I’m aware of their faults, but that doesn’t mean they’re useless.
So yeah, I look forward to the AI bubble popping, but I’m still going to use LLMs for type of tasks they’re actually suited for.
I don’t think many people on Lemmy are under the the spell of AI hype, but plenty of people here are knowledgeable enough to know when, and when not, to leverage this useful, but dangerously overhyped and oversold, piece of technology.
A Math PhD will eventually make a simple arithmetic mistake if you ask them to do enough problems. That doesn’t invalidate more difficult proofs they have published in papers
Ask him how many "R"s are in Strawberry
Look, two Rs is accurate as long as you accept that AI knows ‘what you really mean’ and you should have just prompted better.
That drives me mad. “Oh, you don’t find AI that useful for developement? You should learn how to talk to it.”. Wasn’t that the point, that it would understand me?
Meh, that was the sales pitch. But name one tool in development that actually does what the sales pitch claimed. Knowing how to get useful info out of AI does involve knowing how to talk to it. Just like getting the most out of gitlab means knowing how they intend for you to organize your jobs. So AI is just like every other tool, overhyped, underdelivering, and has “some” use.
Git and even GitLab does its job quite well.
IDEs do A LOT of heavy lifting for many devs.
AI was supposed to boost productivity and eventually replace developers altogether.
One of those things is not like the otters.
What the snake oil people never bring up is that companies do try and replace devs with AI and prompts.
Then realize it doesn’t work as non-engineers don’t have the skillset to do it and then come crawling back to engineers to fix the mess.
300?
It’s that or Over 9000!!!
How many pounds of carbon did that answer produce?
There are no “R”'s (capital r) in strawberry.
R and r are the same letter. You can tell because a word that starts with r can be written with R at the start of the sentence
Ask the model to confirm the answer and it will correct itself, at least when I’ve tried that.
I’m sure there’s a mathematical or programmatic logic as to why, but seeing as I don’t need LLM’s to count letters or invent new types of pseudoscience, I’m not overly interested in it.
Regardless, I look forward to the bubble popping.
If I can’t rely on a system to perform simple tasks I can easily validate, I’m not sure why I’d trust it to perform complex tasks I would struggle to verify.
Imagine a calculator that reported “1+1=3”. It seems silly to use such a machine to do long division.
That’s my point, I don’t use LLMs for those operations, and I’m aware of their faults, but that doesn’t mean they’re useless.
So yeah, I look forward to the AI bubble popping, but I’m still going to use LLMs for type of tasks they’re actually suited for.
I don’t think many people on Lemmy are under the the spell of AI hype, but plenty of people here are knowledgeable enough to know when, and when not, to leverage this useful, but dangerously overhyped and oversold, piece of technology.
A Math PhD will eventually make a simple arithmetic mistake if you ask them to do enough problems. That doesn’t invalidate more difficult proofs they have published in papers
Which is why we don’t designate a single Math PhD as a definitive source for all mathematical wisdom.
If I’m handed a proof with a simple arithmetic mistake in the logic, that absolutely invalidates it
But you didn’t say that. You said you can’t trust something that makes basic mistakes. Humans make them all the time. You can’t trust any human?
Beginning to think I’m arguing with a bot
You said
Every single person alive has made silly addition mistakes. Is it silly to trust those people with long division?