And then people will complain about that saying it’s almost all hype and no substance.

Then that one tech bro will keep insisting that lemmy is being unfair to AI and there are so many good use cases.

No one is denying the 10% use cases, we just don’t think it’s special or needs extra attention since those use cases already had other possible algorithmic solutions.

Tech bros need to realize, even if there are some use cases for AI, there has not been any revolution, stop trying to make it happen and enjoy your new slightly better tool in silence.

Best part is the noise it makes when the fans finally shut down, it is finally at peace.

Hey remember when computers become essential to day to day life and schools started making it part of their curriculum? Yeah me neither.

For gen x and millennials, they got those skills for free cause their toys incentivized them. As in we got that for free.

It was never guaranteed for that to keep being true. And giving you basic knowledge for the world is usually what schools should do but they never did cause there is money to be made with dumbed down tools.

I am demanding experience for entry level work, simply because the entry-level work pool has zero knowledge how things work.

And they don’t need to, that’s not what entry level means.

If a skill isn’t needed in day to day life anymore and is needed for the job you’re putting out, it’s no longer a common knowledge skill.

When the talent pool changes, so should expectations.

The difference is that you don’t need to be car savvy not to get into an accident. But you do need to be tech savvy not to be at risk of cyberthreats.

Drivers truly don’t need to know how a car works, software is not like that.

Also, you can get by without a car, whereas most people need at least an email address.

Edit: I don’t understand the downvotes. Do people think that you need to know about how engines work to drive a car. Or do people don’t think you need to understand file structure to manage excel files?

I have it parse huge policy memos into things I actually might give a shit about.

I’ve used it to run though a bunch of semi-structured data on documents and pull relevant data. It’s not necessarily precise but it’s accurate enough for my use case.

Here are two cases from your original comment that would have data loss. I get you didn’t use the phrase “data loss” but that doesn’t mean your examples didn’t have that flaw.

Sorry if you view all this as lemmy being “anti ai”. For me, I’m a big fan of ML and what things like image recognition can do. I’m not a fan of LLMs becoming so overhyped that it basically gave the other ML use cases a bad name.

I read this comment chain and no? They are giving you actual criticism about the fundamental behaviour of the technology.

The person basically explained the broken telephone game and how “summarizing” will always have data loss by definition, and you just responded with:

In this case it actually summarized my post(I guess you could make the case that my post is an opinion that’s shared by many people–so forer-y in that sense)

Just because you couldn’t notice the data loss doesn’t mean the principle isn’t true.

Your basically saying translating something from English to Spanish and then back to English again is flawless cause it worked for some words for you.

Yep, pretty much every single “good” use case of AI I’ve seen is basically a band aid solution to enshitification.

You know what’s a good solution to that? Removing the profit motive.

Cool. Yeah I think the best use case of AI is just gonna be better search of unorganized that. Having said that though, it would never be as good as a good search engine with organized data.

But does it actually link the source or does it just say a basic answer and you have to take a leap of faith?