In a perfect, utopian world, yes. AI can go a lot of good. In the world that we are living in? No.
But it’s still good to keep an eye on what people are using AI to do, and how their capability is evolving. Even if you hate AI. If anything, so you can be prepare for what’s to come.
When the product is a solution in search of a problem, keeping an open mind is a good way to get it stuffed full of garbage. I was told the same thing about NFTs and Metaverse and Blockchain: a radical benefit is just around the corner!
If it arrives (huge if), it’ll be Big Tech’s job to explain it to us, and it should be very apparent
Keeping an eye on it doesn’t mean you need to think it’s a good thing. Keep an eye on it like how you would keep an eye on a developing hurricane or pandemic.
I think that LLMs amaze rich investors and boomers with their naturalistic-enough language and responses, and they invest in and prop up the tech because they think, in the nearish future, that it can replace a ton of human jobs, both menial and creative. Eliminating manual labor jobs is great if it’s paired with Universal Basic Income.
I think that the fervor around AI is more economic anxiety than anything. If people’s income and oppurtunities were mostly equal, no new tech would make people think they’re being disenfranchised from society.
I do use it quite often in my work. I just downloaded an Excel worksheet with all standard mailtexts (I work at a company offering courses), about 500x3. I gave it a list of criteria they should follow, and made it find those that didn’t. This worked pretty well. And it can work pretty well so long as you’re in control and you don’t take the result as truth.
That’s beside the obvious privacy issues, obviously. I hardly ever use LLMs outside of work (though when I do, I like to run models locally).
it can work pretty well so long as you’re in control and you don’t take the result as truth.
But doesn’t this make the whole point null and void? Like obviously if you’re running it through and getting an output you do have to take elements of it as truth.
What I mean is that you have to be able to judge whether the output is correct. So you don’t take its truth at face value.
In my example, obviously correct input is filtered out, leaving only potential errors. It takes much less effort to upload a sheet and give criteria and instructions than to manually look through everything (though, granted, you can probably come pretty far with just ctrl+f too).
There are things LLMs are good at, but they’re just a tool like any other.
I use LLMs for the following, you can decide for yourself if they are major enough:
Generating example solutions to maths and physics problems I encounter in my coursework, so I can learn how to solve similar problems in the future instead of getting stuck. The generated solutions, if they come up with the right answer, are almost always correct and if I wonder about something I simply ask.
Writing really quick solutions to random problems I have in python or bash scripts, like “convert this csv file to this random format my personal finance application uses for import”.
Helping me when coding, in a general way I think genuinely increases my productivity while I really understand what I push to main. I don’t send anything I could not have written on my own (yes, I see the limitations in my judgement here).
Asking things where multiple duckduckgo searches might be needed. E.g. “Whats the history of EU+US sanctions on Iran, when and why were they imposed/tightened and how did that correlate with Iranian GDP per capita?”
What does this cost me? I don’t pay any money for the tech, but LLM providers learn the following about me:
What I study (not very personal to me)
Generally what kinds of problems I want to solve with code (I try to keep my requests pretty general; not very personal)
The code I write and work on (already open source so I don’t care)
Random searches (I’m still thinking about the impact of this tbh, I think I feel the things I ask to search for are general enough that I don’t care)
There’s also an impact on energy and water use. These are quite serious overall. Based on what I’ve read, I think that my marginal impact on these are quite small in comparison to other marginal impacts on the climate and water use in other countries I have. Of course there are around a trillion other negative impacts of LLMs, I just once again don’t know how my marginal usage with no payment involved lead to a sufficient increase in their severity to outweigh their usefulness to me.
Is “AI” even worth it?
Seriously, is there really a major use case for LLM besides data collection (which they can still do without LLM)?
In a perfect, utopian world, yes. AI can go a lot of good. In the world that we are living in? No.
But it’s still good to keep an eye on what people are using AI to do, and how their capability is evolving. Even if you hate AI. If anything, so you can be prepare for what’s to come.
When the product is a solution in search of a problem, keeping an open mind is a good way to get it stuffed full of garbage. I was told the same thing about NFTs and Metaverse and Blockchain: a radical benefit is just around the corner!
If it arrives (huge if), it’ll be Big Tech’s job to explain it to us, and it should be very apparent
Keeping an eye on it doesn’t mean you need to think it’s a good thing. Keep an eye on it like how you would keep an eye on a developing hurricane or pandemic.
Touche. I apologize for responding to the argument I’ve seen elsewhere, not the one you were making.
Not for the peasantry, no.
Machine learning
consilidation of information, resources and potentially “the narrative”.
oh, for the user you mean?
I think it could be good for faster language translations between different languages
It’s a great way to poke at software looking for security holes en masse. Lots of vulnerabilities are ready to be exploited at scale with LLMs.
Perhaps, but see the tons of imagined issues raised on bug bounty sites by LLMs. Maybe it’s right sometimes, but it’s very often wrong!
You don’t have to be right 100% of the time when scanning for vulnerabilities. You only have to be right once. It’s a fundamentally different game.
That’s true. Offense is always easier than defense.
I think that LLMs amaze rich investors and boomers with their naturalistic-enough language and responses, and they invest in and prop up the tech because they think, in the nearish future, that it can replace a ton of human jobs, both menial and creative. Eliminating manual labor jobs is great if it’s paired with Universal Basic Income.
I think that the fervor around AI is more economic anxiety than anything. If people’s income and oppurtunities were mostly equal, no new tech would make people think they’re being disenfranchised from society.
I do use it quite often in my work. I just downloaded an Excel worksheet with all standard mailtexts (I work at a company offering courses), about 500x3. I gave it a list of criteria they should follow, and made it find those that didn’t. This worked pretty well. And it can work pretty well so long as you’re in control and you don’t take the result as truth.
That’s beside the obvious privacy issues, obviously. I hardly ever use LLMs outside of work (though when I do, I like to run models locally).
But doesn’t this make the whole point null and void? Like obviously if you’re running it through and getting an output you do have to take elements of it as truth.
What I mean is that you have to be able to judge whether the output is correct. So you don’t take its truth at face value.
In my example, obviously correct input is filtered out, leaving only potential errors. It takes much less effort to upload a sheet and give criteria and instructions than to manually look through everything (though, granted, you can probably come pretty far with just ctrl+f too).
There are things LLMs are good at, but they’re just a tool like any other.
I use LLMs for the following, you can decide for yourself if they are major enough:
What does this cost me? I don’t pay any money for the tech, but LLM providers learn the following about me:
There’s also an impact on energy and water use. These are quite serious overall. Based on what I’ve read, I think that my marginal impact on these are quite small in comparison to other marginal impacts on the climate and water use in other countries I have. Of course there are around a trillion other negative impacts of LLMs, I just once again don’t know how my marginal usage with no payment involved lead to a sufficient increase in their severity to outweigh their usefulness to me.
If you are using DDG for searches and concerned about privacy related to using LLMs, have you tried duck.ai?
You can also download some LLMs and run them locally.