I’ve seen a lot of sentiment around Lemmy that AI is “useless”. I think this tends to stem from the fact that AI has not delivered on, well, anything the capitalists that push it have promised it would. That is to say, it has failed to meaningfully replace workers with a less expensive solution - AI that actually attempts to replace people’s jobs are incredibly expensive (and environmentally irresponsible) and they simply lie and say it’s not. It’s subsidized by that sweet sweet VC capital so they can keep the lie up. And I say attempt because AI is truly horrible at actually replacing people. It’s going to make mistakes and while everybody’s been trying real hard to make it less wrong, it’s just never gonna be “smart” enough to not have a human reviewing its’ behavior. Then you’ve got AI being shoehorned into every little thing that really, REALLY doesn’t need it. I’d say that AI is useless.
But AIs have been very useful to me. For one thing, they’re much better at googling than I am. They save me time by summarizing articles to just give me the broad strokes, and I can decide whether I want to go into the details from there. They’re also good idea generators - I’ve used them in creative writing just to explore things like “how might this story go?” or “what are interesting ways to describe this?”. I never really use what comes out of them verbatim - whether image or text - but it’s a good way to explore and seeing things expressed in ways you never would’ve thought of (and also the juxtaposition of seeing it next to very obvious expressions) tends to push your mind into new directions.
Lastly, I don’t know if it’s just because there’s an abundance of Japanese language learning content online, but GPT 4o has been incredibly useful in learning Japanese. I can ask it things like “how would a native speaker express X?” And it would give me some good answers that even my Japanese teacher agreed with. It can also give some incredibly accurate breakdowns of grammar. I’ve tried with less popular languages like Filipino and it just isn’t the same, but as far as Japanese goes it’s like having a tutor on standby 24/7. In fact, that’s exactly how I’ve been using it - I have it grade my own translations and give feedback on what could’ve been said more naturally.
All this to say, AI when used as a tool, rather than a dystopic stand-in for a human, can be a very useful one. So, what are some use cases you guys have where AI actually is pretty useful?
When I need to make a joke about how inept AI is, I’ll use AI to capture an example of it saying the most efficient way to get to the moon is to put a 2 liter bottle of coke in your asshole, wide end first, remove the cap and immediately sit on an opened sleeve of mentos.
I use it like an intern/other team member since the non-profit I work for doesn’t have any money to hire more people. Things like:
- Taking transcripts of meetings and turning them into neat and ordered meeting minutes/summaries, or pulling out any key actions/next steps
- Putting together objectives and agendas for meetings based on some loose info and ideas I give it
- Summarise the key points from articles/long documents I don’t have tome or patience to read through fully.
- Making my emails sound more professional/nicer/make up for my brainfarts
- Giving me ideas on how to format/word slides and documents depending on what tone I want to employ - is it meant for leadership? Other team members?
- Make my writing more organised/better structured/more professional sounding
- Writing emails in foreign languages with a professional tone. Caveat is I’m fluent enough in those languages to know if the output sounds right. Before AI I would rely on google translate (meh), dictionaries, language forums, etc and it would take me HOURS to write a simple email using the correct terminology. Also helpful to check grammar and sentence structure in ways that aren’t always picked up by Word.
- I sound more like a robot than an actual robot, so I ask the robot to reword my emails/messages to sound more “human” when the need arises (like a colleague is leaving, had a baby, etc).
- Bouncing off ideas. This doesn’t always work and I know it doesn’t actually have an opinion, but it helps get the ball rolling, especially if I’m struggling with procrastination.
- If my sentences are too long for a document, I ask it to shorten/reword and it’s pretty capable of doing that without losing too much of the essence of what I want to get across
Of course I don’t just take whatever it spits out and paste it. I read through everything, make sure it still sounds more or less like “me”. Sometimes it’ll take a couple of prompts to get it to go where I want it, and takes a bit of review and editing but it saves me literal hours. It’s not necessarily perfect, but it does the job. I get it’s not a panacea, and it’s not great for the environment, but this tech is literally saving my sanity right now.
I couldn’t let an AI do any of this for me.
As in… I couldn’t let anyone make my emails more professional or whatever.
It’s not like I think my emails are always the best and can not be improved upon, it’s just that my emails are “me”.
I never have cause to write an email in a foreign language.
To each their own ¯\(ツ)/¯
New question: does anyone NOT IN TECH have a use case for AI?
This whole thread is 90% programming, 9% other tech shit, and like 2 or 3 normal people uses
Our DM, a dentist, so not in tech, used it to put together a D&D campaign, and so far it’s been fantastic.
A lot of people on Lemmy work in tech so responses are going to lean heavily in that direction. I’m not in tech and if you check my answer to this you’ll have a number of examples. I also know a few people who wanted to learn a new language and asked ChatGPT for a day by day programme and some free sources and they were pretty happy with the results they got. I imagine you can do that with other subjects. Other people I know have used it to make images for things like club banners or newsletters.
Aside from coding assistants, the other use case I’ve come across recently is sentiment analysis of large datasets from free text survey responses. Just started exploring it so not sure how well it works yet, but the ridiculous amount of bias I see introduced in manual reviews is just awful. A machine can potentially be less inclined to try fitting summaries to the VP’s presupposed opinion than some lackie interns or self serving consultancy.
Here’s mine, that works outside of tech:
It’s a great source for second opinions.
Say you want to make a CV, but you don’t know where to even begin. You could give it a description of what you’ve been doing and ask it to help you figure out what jobs fit the skillset and how to present your skills better.
It’s a good tool for such rough estimations that give you ground to improve upon.
This works well for planning or making up documentation. Saves a lot of time, with minimal impact to quality, because you’re not mindlessly copying or believing the output.
I’m also considering it for assisting me in learning Japanese. Just enough to be able to read in it. We’ll see how it does.
I have enough education and skill and talent to not need AI.
Sorry for the rest of you. Not really.
I put this comment into chatgpt and it diagnosed you with narcissistic personality disorder.
But I’m sure you already knew that.
Hopefully AI will help aid social skills at some point.
What a lucky day it will be for you
i use it to autoblog about my love for the capitalist hellscape that is our green earth on linkedin dot com
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to correct/rephrase a sentence or two if my sentence sounds too awkward
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if I’m having trouble making an excel formula
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I run some TTRPG groups and having AI take in some context and generate the first draft of flavor text for custom encounters is nice. Also for generating background art and player character portraits is an easy win for me.
This is my current best use for it as well. Having a unique portrait for every named NPC helps them stand out quite a bit better and the players respond much more strongly to all of them.
Timing traffic lights. They could look down the road and see when nothing is coming, to let the other direction go, like a traffic cop. It would save time and gas.
Or, here me out, we could use roundabouts/traffic circles. No need for AI or any kind of sensor, just physical infrastructure to keep traffic flowing.
Absolutely, but there are a few problems with this. First, I live in the US. Americans do NOT know how to negotiate a roundabout. There is a roundabout near my house. The instructions of how to use it are posted on signs as you approach. They are wrong. They actually have inside lanes exiting across the outside lanes that can continue around. So not only is it wrong but it’s teaching the locals here what NOT to do at a normal roundabout.
Second, they don’t fit at existing intersections.
Third, I think they would be more expensive than just a piece of tech attached to traffic lights that already exist.
I mean the best solution would be some good public transportation, but I’m trying to be more realistic here. That’s for more civilized nations. In the US the car rules. And the bigger, the better.
I live in the US. Americans do NOT know how to negotiate a roundabout.
As do I, but I think the main problem is that we don’t need to properly learn to use a roundabout, because the only times we have roundabouts are when they’re completely unnecessary/unhelpful. The three roundabouts I use most often are:
- right next to a stoplight, so they get jammed when there are a lot of cars waiting
- middle of a residential area, with stoplights/stop signs a block or two away preventing too much contention
- in a somewhat busy area where most of the traffic is going straight, so it functions like a speed bump
If we can figure out those continuous flow intersections, we can figure out roundabouts. We just need to actually use them.
Second, they don’t fit at existing intersections.
They absolutely do, especially at the ones where they’d make the most impact (i.e. busy intersections with somewhat even traffic going all directions). You may actually save space because you don’t need special turn lanes. They are a little more tricky in smaller intersections, but those tend to have pretty light traffic anyway.
I think they would be more expensive
Initial cost, sure, because the infrastructure is already there. But longer term, it should reduce costs because you don’t need to service all of those traffic signals, you need fewer lanes (so less road maintenance), and there should be fewer accidents, which means less stress on emergency services.
Putting in a new roundabout vs a new signal is a different story, the roundabout is going to be significantly cheaper since you just need to dump a bit of concrete instead of all of the electronics needed for a signal.
In the US the car rules
Unfortunately, yes, but roundabouts move more traffic, so they’re even better for a car-centric transit system. If we had better mass transit, we wouldn’t need to worry as much about intersections because there’d be a lot less traffic in general.
If we go with “AI signals,” we’re going to spend millions if not billions on it, because that’s what government contractors do. And I think the benefits would be marginal. It’s better, IMO, to change the driving culture instead of trying to optimize the terrible culture we have.
I think it’s useful for spurring my own creativity in writing because I have a hard time getting started. To be fair to me I pretty much tear the whole thing down and start over but it gives me ideas.
Scripting, both frameworks and finished code with testing and iteration.
More often than not it gives me decent answers for the kind of info I’m searching for. Saves me a lot of time digging through ad layden pages and search results.
Converting code too! I’ve used LLMs to go from Node -> GoLang, and that’s basically how I learned to code in Go coming from a less low-level background. You can also ask about what the current best practices are.
So far, I’ve only found it really useful for two things. One is generating text, where I’ve found using an LLM to generate a title based on a given piece of text is more effective than using other summarisation models, especially for a short piece of text.
I’ve also found it okay for basic, generic scripts, like trying to figure out what the equivalent Powershell commands for a bash script would be to do something quick, rather than try and learn it from scratch.
For me, I use Whisper for transcribing/translating audio data. This has helped me to double check claims about a video’s translation (there’s a lot of disinformation going around for topics involving certain countries at war).
Nvidia’s DLSS for gaming.
Different diffusion models for creating quick visual recaps of previous D&D sessions.
Tesseract OCR to quickly copy out text from an image (although I’m currently looking for a better one since this one is a bit older and, while it gets the text mostly right, there’s still a decent amount that it gets wrong).
LLMs for brainstorming or in the place of some stack overflow questions when picking up a new programming language.
I also saw an interesting use case from a redditor:
I had about 80 VHS family home videos that I had converted to digital
I then ran the 1-4 hour videos through WhisperAI Large-v3 transcription and pasted those transcripts into a prompt which had a little bit of background information on my family like where we live and names of everyone who might show up in the videos, and then gave the prompt some examples of how I wanted the file names to look, for example:
1996 Summer - Jane’s birthday party - Joe’s Soccer game - Alaska cruise - Lanikai Beach
And then had Claude write me titles for all the home videos and give me a little word doc to put in each folder which catalogues all the events in each video. It came out so good I have been considering this as a side business
There is one thing I would find genuinely useful that seems within its current capabilities. I’d like to be able to give an AI a summary of my current knowledge on a subject, along with a batch of papers or articles, and have it give me one or more of the following:
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A summary of the papers omitting the stuff I already know
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A summary of any prerequisite background info I don’t already know, but isn’t in the papers
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A summary of all the points on which the papers are in agreement
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A summary of any points where the papers are in contention.
This is indeed very much possible. Just try it.
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I’ve been learning docker over the last few weeks and it’s been very helpful for writing and debugging docker-compose configs. My server how has 9 different services running on it.
I use it for python development sometimes, maybe once per day. I’ll paste in a chunk of code and describe how I want it altered or fixed and that usually goes pretty well. Or if I need a generic function that I know will have been coded a million times before I’ll just ask ChatGPT for it.
It’s far from “useless” and has made me somewhat more productive. I can’t see it replacing anyone’s job though, more of a supplemental tool that increases output.
I’ve definitely run into this as well in my own self-hosting journey. When you’re learning it’s easier to get it to just draft up a config - then learn what the options mean after the fact then it is to RTFM from the beginning.
I sometimes have Señor GPT rewrite my nonsensical ramblings into coherent and decipherable text. I recently did that for a paper in my last class. lol
I wrote a bunch of shit, had GPT rewrite it, added a couple quotes from my sources and called it a day.I’m also currently on a single player, open world adventure with GPT. Myself and the townspeople iust confronted the suspicious characters on the edge of town. They claim to not be baddies but they’re being super sus. I might just attack anyway.
