What is the legitimate use-case for generative AI?

It's kinda handy if you don't want to take the time to write a boring email to your insurance or whatever.
- I sorta disagree though, based on my experience with llms.
  The email it generates will need to be read carefully and probably edited to make sure it conveys your point accurately. Especially if it's related to something as serious as insurance.
  If you already have to specifically create the prompt, then scrutinize and edit the output, you might as well have just written the damn email yourself.
  It seems only useful to write slop that doesn't matter that only gets consumed by other machines and dutifully logged away in a slop container.
  
  It does sort of solve the 'blank page problem' though IMO. It sometimes takes me ages to start something like a boring insurance letter because I open up LibreOffice and the blank page just makes me want to give up. If I have AI just fart out a letter and then I start to edit it, I'm already mid-project so it actually does save me some time in that way.
  
  For us who are bad at writing though that's exactly why we use it. I'm bad with greetings, structure, things that people expect and I've had people get offended at my emails because they come off as rude. I don't notice those things. For that llms have been a godsend. Yes, I of course have to validate it, but it conveys the message I'm trying to usually
- Yeah that's how I use it, essentially as an office intern. I get it to write cover letters and all the other mindless piddly crap I don't want to do so I can free up some time to do creative things or read a book or whatever. I think it has some legit utility in that regard.
- I get the point here but I think it’s the wrong approach. If you feel the email needs too much business fluff, just write it more casual and get to the point quicker.

People keep meaning different things when they say "Generative AI". Do you mean the tech in general, or the corporate AI that companies overhype and try to sell to everyone?
The tech itself is pretty cool. GenAI is already being used for quick subtitling and translating any form of media quickly. Image AI is really good at upscaling low-res images and making them clearer by filling in the gaps. Chatbots are fallible but they're still really good for specific things like generating testing data or quickly helping you in basic tasks that might have you searching for 5 minutes. AI is huge in video games for upscaling tech like DLSS which can boost performance by running the game at a low resolution then upscaling it, the result is genuinely great. It's also used to de-noise raytracing and show cleaner reflections.
Also people are missing the point on why AI is being invested in so much. No, I don't think "AGI" is coming any time soon, but the reason they're sucking in so much money is because of what it could be in 5 years. Saying AI is a waste of effort is like saying 3D video games are a waste of time because they looked bad in 1995. It will improve.
- AI is huge in video games for upscaling tech like DLSS which can boost performance by running the game at a low resolution then upscaling it, the result is genuinely great
  frame gen is blurry af and eats shit on any fast motion. rendering games at 640x480 and then scaling them to sensible resolutions is horrible artistic practice.
  
  rendering games at 640x480 and then scaling them to sensible resolutions is horrible artistic practice.
  Is that a reason a lot of pixel art games are looking like shit? I remember the era of 320x240 and 640x480 and the modern pixel art are looking noticeably worse.

In the context of programming:
Good for boilerplate code and variables naming when what you want is for the model to regurgitate things it has seen before.
Short pieces of code where it's much faster to verify that the code is correct than to write the code yourself.
Sometimes, I know how to do something but I'll wait for Copilot to give me a suggestion, and if it looks like what I had in mind, it gives me extra confidence in the correctness of my solution. If it looks different, then it's a sign that I might want to rethink it.
It sometimes gives me suggestions for APIs that I'm not familiar with, prompting me to look them up and learn something new (assuming they exist).
There's also some very cool applications to game AI that I've seen, but this is still in the research realm and much more niche.

I treat it as a newish employee. I don't let it do important tasks without supervision, but it does help building something rough that I can work on.

I wrote guidelines for my small business. Then I uploaded the file to chatgpt and asked it to review it.
It made legitimately good suggestions and rewrote the documents using better sounding English.
Because of chatgpt I will be introducing more wellness and development programs.
Additionally, I need med images for my website. So instead of using stock photos, I was able to use midjourney to generate a whole bunch of images in the same style that fit the theme of my business. It looks much better.

shitposting.
Need some weidly specific imagery about whatever you're going on about? It got you covered

Money. It's always about money. But more seriously, I also wonder what's the point since all my interactions with GenAI have been disappointment after disappointment. But I read Dev saying that it's great at creating drafts

I use it to help with programming and writing. Not as a way to have something so it for me but as something that can show me how to do something I am stuck on or give me ideas when Im drawing a blank.
Kinda like an interactive rubber duck. Its solutions arent always right or accurate but it does help me get past things I struggle with.

I use it to sort days and create tables which is really helpful. And the other thing that really helped me and I would have never tried to figure out on my own:
I work with the open source GIS software qgis. I'm not a cartographer or a programmer but a designer. I had a world map and wanted to create geojson files for each country. So I asked chatgpt if there was a way to automate this within qgis and sure thing it recommend to create a Python script that could run in the software, to do just that and after a few tweaks it did work. that saved me a lot of time and annoyances. Would it be good to know Python? Sure but I know my brain has a really hard time with code and script. It never clicked and likely never will. So I'm very happy with this use case. Creative work could be supported in a drafting phase but I'm not so sure about this.

Here's some uses:
skin cancer diagnoses with llms has a high success rate with a low cost. This is something that was starting to exist with older ai models, but llms do improve the success rate. source
VLC recently unveiled a new feature of using ai to generate subtitles, i haven't used it but if it delivers then it's pretty nice
for code generation, I agree it's more harmful than useful for generating full programs or functions, but i find it quite useful as a predictive text generator, it saves a few keystrokes. Not a game changer but nice. It's also pretty useful at generating test data so long as it's hard to create but easy (for a human) to validate.

"at worst it spits out garbage code that you spend more time debugging than if you had just written it by yourself."
I've not experienced this. Debugging for me is always faster than writing something entirely from scratch.
- 100% agree with this.
  It is so much faster for me to give the ai the api/library documentation than it would be for me to figure out how that api works. Is it a perfect drop-in, finished piece of code? No. But that is not what I ask the ai for. I ask it for a simple example which I can then take, modify, and rework into my own code.

I generate D&D characters and NPCs with it, but that's not really a strong argument.
For programming though it's quite handy. Basically a smarter code completion that takes the already written stuff into account. From machine code through assembly up to higher languages, I think it's a logical next step to be able to tell the computer, in human language, what you actually are trying to achieve. That doesn't mean it is taking over while the programmer switches off their brain of course, but it already saved me quite some time.

Idea generation.
E.g., I asked an LLM client for interactive lessons for teaching 4th graders about aerodynamics, esp related to how birds fly. It came back with 98% amazing suggestions that I had to modify only slightly.
A work colleague asked an LLM client for wedding vow ideas to break through writer's block. The vows they ended up using were 100% theirs, but the AI spit out something on paper to get them started.
- Those are just ideas that were previously "generated" by humans though, that the LLM learned
  
  Those are just ideas that were previously "generated" by humans though, that the LLM learned
  That’s not how modern generative AI works. It isn’t sifting through its training dataset to find something that matches your query like some kind of search engine. It’s taking your prompt and passing it through its massive statistical model to come to a result that meets your demand.

For coding it works really well if you give it examples like "i have code that looked like this .... And i made it to look like this .... If i give you another piece of code that's similar to the first can you convert it to the second for me". Been great to reduce the amount of boring grunt work so I can focus on the more fun stuff
- In C#, when programming save/load in video games, it can be super tedious. I am self taught and i didnt have the best resources, so the only way i could find to ensure its saving the correct variables was to manually input every single variable into a text file. I dont care if its plaintext, if people want to edit their save then more power to them. The issue is that there are potentially tens of hundreds of different variables that need to be saved for the gamestate to be accurately recreated.
  So its really nice that i can just copy/paste my classes into gpt and give it the syntax for a single variable to be saved, then have it do the rest. I do have to browse through and ensure its actually getting all the variables, but it turns a potentially mindnumbing 4 hour long process into maybe a 20 minute one thats relatively engaging.
  Also if you know a better way lmk. I read that you can simply hash the object into a text file and then unhash it, but afaik unhashing something is next to impossible and i could never figure it out anyways.
  
  You could encrypt and decrypt it with keys.
  Or you can do something simple like scramble the letters like a cypher, still able to edit manually but it wouldn't be as readable and obvious what everything does.
  Or you can can encode it, same issue as the last but they'll have to know what it was encoded with to decode it before editing.
  Or you can just turn it into bytes so the file is more awkward to work with.
  You could probably mix a bunch of these together if you care enough. U don't think any are THE standard and foolproof but they're options

Best use is to ask it questions that you're not sure how to ask. Sometimes you come across a problem that you're not really even sure how to phrase, which makes Googling difficult. LLM's at least would give you a better sense of what to Google

I have a very good friend who is brilliant and has slogged away slowly shifting the sometimes-shitty politics of a swing state's drug and alcohol and youth corrections policies from within. She is amazing, but she has a reading disorder and is a bit neuroatypical. Social niceties and honest emails that don't piss her bosses or colleagues off are difficult for her. She jumped on ChatGPT to write her emails as soon is it was available, and has never looked back. It's been a complete game changer for her. She no longer spends hours every week trying to craft emails that strike that just-right balance. She uses that time to do her job, now.
- I hope it pluralizes 'email' like it does 'traffic' and not like 'failure'.

I have had some decent experiences with Copilot and coding in C#. I've asked it to help me figure out what was wrong with a LINQ query I was doing with an XDocument and it pointed me in the right direction where I figured it out. It also occasionally has some super useful auto complete blocks of code that actually match the pattern of what I'm doing.
As for art and such, sometimes people just want to see some random bizarre thing realized visually that they don't have the ability (or time/dedication) to realize themselves and it's not something serious that they would be commissioning an artist for anyway. I used Bing image creator recently to generate a little character portrait for an online DND game I'm playing in since I couldn't find quite what I was looking for with an image search (which is what I usually do for those).
I've seen managers at my job use it to generate fun, relevant imagery for slideshows that otherwise would've been random boring stock images (or just text).
It has actual helpful uses, but every major corporation that has a stake in it just added to or listened to the propaganda really hard, which has caused problems for some people; like the idiot who proudly fired all of his employees because he replaced all their jobs with automation and AI, then started hunting for actual employees to hire again a couple months later because everything was terrible and nothing worked right.
They're just tools that can potentially aid people, but they're terrible replacements for actual people. I write automated tests for a living, and companies will always need people for that. If they fired me and the other QAs tomorrow, things would be okay for a short while thanks to the automation we've built, but as more and more code changes go into our numerous and labyrinthine systems, more and more bugs would get through without someone to maintain the automation.

If you don’t know what you are doing and ask LLMs for code then you are gonna waste time debugging it without understanding but if you are just asking it for boiler plate stuff, or are asking it to add comments and print outs to console for existing code for debugging, it’s really great for that. Sometimes it needs chastising or corrections but so do humans.
I find it very useful but not worth the environmental cost or even the monetary cost. With how enshittified Google has become now though I find that ChatGPT has become a necessary evil to find reliable answers to simple queries.

It has value in natural language processing, like turning unstructured natural language data into structured data. Not suitable for all situations though, like situations that cannot tolerate hallucinations.
Its also good for reorganizing information and presenting it in a different format; and also classification of semantic meaning of text. It's good for pretty much anything dealing with semantic meaning, really.
I see people often trying to use generative AI as a knowledge store, such as asking an AI assistant factual questions, but this is an invalid usecase.

What doesn't exist yet, but is obviously possible, is automatic tweening. Human animators spend a lot of time drawing the drawings between other drawings. If they could just sketch out what's going on, about once per second, they could probably do a minute in an hour. This bullshit makes that feasible.
We have the technology to fill in crisp motion at whatever framerate the creator wants. If they're unhappy with the machine's guesswork, they can insert another frame somewhere in-between, and the robot will reroute to include that instead.
We have the technology to let someone ink and color one sketch in a scribbly animatic, and fill that in throughout a whole shot. And then possibly do it automatically for all labeled appearances of the same character throughout the project.
We have the technology to animate any art style you could demonstrate, as easily as ink-on-celluloid outlines or Phong-shaded CGI.
Please ignore the idiot money robots who are rendering eye-contact-mouth-open crowd scenes in mundane settings in order to sell you branded commodities.
- For the 99% of us who don't know what tweening is and were scared to Google it in case it was perverted, it's short for in-betweening and means the short frames of an animation in-between two main scenes
- Have you seen this? There was another paper, but I can't remember the name of it right now.
  
  I had not. There's a variety of demos for guessing what comes between frames, or what fills in between lines... because those are dead easy to train from. This technology will obviously be integrated into the process of animation, so anything predictable Just Works, and anything fucky is only as hard as it used to be.

I'd say there are probably as many genuine use-cases for AI as there are people in denial that AI has genuine use-cases.
Top of my head:
Text editing. Write something (e.g. e-mails, websites, novels, even code) and have an LLM rewrite it to suit a specific tone and identify errors.
Creative art. You claim generative AI art is soulless and poor quality, to me, that indicates a lack of familiarity with what generative AI is capable of. There are tools to create entire songs from scratch, replace the voice of one artist with another, remove unwanted background noise from songs, improve the quality of old songs, separate/add vocal tracks to music, turn 2d models into 3d models, create images from text, convert simple images into complex images, fill in missing details from images, upscale and colourise images, separate foregrounds from backgrounds.
Note taking and summarisation (e.g. summarising meeting minutes or summarising a conversation or events that occur).
Video games. Imagine the replay value of a video game if every time you play there are different quests, maps, NPCs, unexpected twists, and different puzzles? The technology isn't developed enough for this at the moment, but I think this is something we will see in the coming years. Some games (Skyrim and Fallout 4 come to mind) have a mod that gives each NPC AI generated dialogue that takes into account the NPC's personality and history.
Real time assistance for a variety of tasks. Consider a call centre environment as one example, a model can be optimised to evaluate calls based on language and empathy and correctness of information. A model could be set up with a call centre's knowledge base that listens to the call and locates information based on a caller's enquiry and tells an agent where the information is located (or even suggests what to say, though this is currently prone to hallucination).

I use it for parsing through legalese or terms and conditions. IT IS NOT PERFECT. I wouldn't trust it ever over a lawyer. But it's great for things like "Is there anything here that is extra unusual or weirdly anti-consumer or very bad for privacy?". I think it's great for that.
People here are just "it will take jobs it's inherently evil". They said the same about Photoshop, and computers before. I think there are evil uses for it sure, but that doesn't mean that it has no valid usages
- Great use for it!

I need help getting started. I’m not an idea person. I can make anything you come up with but I can’t come up with the ideas on my own.
I’ve used it for an outline and then I rewrite it with my input.
Also, I used it to generate a basic UI for a project once. I struggle with the design part of programming so I generated a UI and then drew over the top of the images to make what I wanted.
I tried to use Figma but when you’re staring at a blank canvas it doesn’t feel any better.
I don’t think these things are worth the cost of AI ( ethically, financially, socially, environmentally, etc). Theoretically I could partner with someone who is good at that stuff or practice till I felt better about it.

I don't use it for anything. I have had no involvement and it will stay that way.

I use it for coding, mostly as a time saver. Generally as I'm typing, it will give a suggestion that's functionally the same as what I was going to type anyway so I hit tab and go to the next line. It's able to do this accurately for around 80% of the total lines that I'm writing and going from writing full lines to writing 0-3 characters + tab on most of those lines makes a massive speed difference. It's especially great for writing one off scripts when I'm doing something that's not even a coding project, but there's some tedious file juggling involved. Writing a script completely by hand for that often would take slightly longer than just doing the task manually, and as I said, it's a one-off. But writing the script with copilot often takes as little as 10% of the time which is really nice.
Even in cases where I don't already know how to solve a problem (particularly a problem involving specific integrations) it can often be faster to ask it how to solve the problem and then look up the specific functions, endpoints, etc it uses in the docs rather than trying to find those doc entries directly with a search. And if it hallucinates a function that doesn't exist in the docs then I tell it that and it often successfully corrects itself. When it fails more than once I've generally found that there's a high probability that the SDK/API/etc I'm looking at doesn't have anything that does what I need so it's time for me to start rethinking my approach
Outside of coding, I also use stable diffusion to generate images of D&D characters I'm creating instead of image searching and settling for something kind of close to what I was picturing.
I also regularly use SD when I stumble upon some art I'd like to use as a desktop wallpaper, but can't find at high enough resolution. I just upscale it and proceed. Sometimes I'll have something at the wrong aspect ratio and use generative fill to extend the edges of the image to the desired aspect ratio, those parts of the image are nothing special, but the important part is the original image and I just need some filler to prevent it from abruptly ending before the edges of the screen.
One last case is if I need to put together a tediously long document, I generally find that having it generate a first draft with the right structure and then iterating a bunch on that comes more easily than starting with an empty page.

I use LLMs for search results when conventional search engines aren't providing relevant results, and then I can fact-check whatever answers the LLMs give me. Especially using them to ask questions that are easy to verify, like mathematical questions where I can check the validity of the answers. Or similarly programming questions where I can read through the solution, check the documentation for any functions used, and make sure the output is logical, and make any tweaks if the LLM gives a nearly-correct answer. I always ask LLMs to cite their sources so I can check those too.
I also sometimes use LLMs for formatting, like when I copy text off a PDF and the spacing is all funky.
I don't use LLMs for this, but I imagine that they would be a better replacement for previous automated translation tools. Translation seems to be one of the most obvious applications since LLMs are just language pattern recognition at the end of the day. Obviously for anything important they need to be checked by a human, but they would e.g. allow for people to participate in online communities where they don't speak the community's language.

I think genAI would be pretty neat for ~~bit banging tests~~ fuzzing, aka. Throwing semi-random requests and/or signals at some device in the hopes of finding obscure edge-cases or security holes.
- Fuzzing.
  
  Thank you for the correction.

i’ve written bots that filter things for me, or change something to machine-readable formats
the most successful thing i’ve done is have a bot that parses a web page and figures out the date/time in standard format, gets a location if it’s listed in the description and geocodes it, and a few other fields to make an ical for pretty much any page
i think the important thing is that gen ai is good at low risk tasks that reduce but don’t eliminate human effort - changing something from having to do a bunch of data entry to skimming for correctness

I just use it for fun. Like, my own personal iPhone backgrounds and stuff. Sometimes I’ll share them with friends or on Mastodon or whatever, but that’s about it.
Gemini is fun to dink around with. When it works…

Fake frames. Nvidia double benefits.
Note: Tis a joke, personally I think DLSS frame generation is cool, as every frame is "fake" anyway.

It's pretty good at looking up readily available knowledge that doesn't have a lot of nuance to it. There's a lot of stuff you can look up but it always comes with a grain of salt.
Home remedies, bunch of baby facts like poop color meaning, recipes and adjustments, programming examples (requires very prompting skills).
Rewriting stuff into business English is another very nice use case. Tell the AI your qualitifations, ask to make a cover letter for "job description" then review. Drafting text and summarising also pretty good.
Adding modifiers to questions like "list of 20 for X" for a brainstorming or "include how scientifically reliable the claim is on scale of 1-10" really help with getting a good answer and some nuance to whatever claims.
It's touted as the be all end all but in reality the use cases are very specific in my experience.

Another point valid for GPTs is getting started on ideas and things, sorting out mind messes, getting useful data out of large amounts of clusterfucks of text, getting a general direction.
Current downsides are you cannot expect factual answers on topics it has no access to as it'll hallucinate on these without telling you, many GPT provides use your data so you cannot directly ask it sensitive topics, it'll forget datapoints if your conversation goes on too long.
As for image generation, it's still often stuck in the uncanny valley. Only animation topics benefit right now within the amateur realm. Cannot say how much GPTs are professionally used currently.
All of these are things you could certainly do yourself and often better/faster than an AI. But sometimes you just need a good enough solution and that's where GPTs shine more and more often. It's just another form of automation - if used for repetitive/stupid tasks, it's fine. Just don't expect it to just build you a piece of fully working bug-free software just by asking it. That's not how automation works. At least not to date.

AI saves time. There are few use cases for which AI is qualitatively better, perhaps none at all, but there are a great many use cases for which it is much quicker and even at times more efficient.
I'm sure the efficiency argument is one that could be debated, but it makes sense to me in this way: for production-level outputs AI is rarely good enough, but creates really useful efficiency for rapid, imperfect prototyping. If you have 8 different UX ideas for your app which you'd like to test, then you could rapidly build prototype interfaces with AI. Likely once you've picked the best one you'll rewrite it from scratch to make sure it's robust, but without AI then building the other 7 would use up too many man-hours to make it worthwhile.
I'm sure others will put forward legitimate arguments about how AI will inevitably creep into production environments etc, but logistically then speed and efficiency are undeniably helpful use cases.
- As some witty folks have put it, LLMs can't give you anything truly, interestingly new when all they're capable of is some weighted average of what's already there. And I'll be clear in saying I hate with the force of a tsunami the way AI is being shoved at us by desperate CEOs, and how it's being used to kill labor, destroy copyright law, increase income inequality, destroy the environment, and increase the power of huge corporations headed by assholes like Altman and Musk. But AI is getting pretty good at that weighted-average-of-what's-out-there, and a lot of the work done in several industries can benefit from that. For me, one of the great perversities or tragedies of AI is that it could be a targeted, useful tool but, instead, it's a hammer to further erode freedom. Even the coders, editors, advertisers, educators, etc. using it to do their jobs are participating in a short-term selloff of their profession to their CEOs, shareholders, etc. at the expense of large numbers of their colleagues or potential colleagues who will now never get jobs.
  It's like if someone invented the wheel and Sam Altman immediately patented it and sold it to Raytheon.

I use it for providing a text summary of YouTube videos that I can parse quickly. Because everything has to be a gorram video these days.

I was asked to officiate my friend's wedding a few months back, I'm no writer, and I wanted to do a bit better than just a generic wedding ceremony for them
So I fired up chatgpt, told it I needed a script for a wedding ceremony, described some of the things I wanted to mention, some of the things they requested, and it spit out a pretty damn good wedding ceremony. I gave it a little once over and tweaked a little bit of what it gave me but 99% of it was pretty much just straight chatgpt. I got a lot of compliments on it.
I think that's sort of the use case. For those of us who aren't professional writers and public speakers, who have the general idea of what we need to say for a speech or presentation but can't quite string the words together in a polished way.
Here's pretty much what it spit out (Their wedding was in a cave)
Cell Phone Reminder
Officiant: Before we begin, I’d like to kindly remind everyone to silence your phones and put them away for the ceremony. Groom and Bride want this moment to be shared in person, free from distractions, so let's focus on the love and beauty of this moment.
Giving Away the Bride
And before we move forward, we have a special moment. Tradition asks: Who gives this woman to be married to this man?
[Response from Bride's dad]
Thank you.
Greeting
Welcome, everyone. We find ourselves here in this remarkable setting—surrounded by the quiet strength of these ancient walls, a fitting place for Groom and Bride to declare their love. The cave, much like marriage, is carved out over time—through patience, care, and sometimes a little hard work. And yet, what forms is something enduring, something that stands the test of time.
Today, we’re here to witness Groom and Bride join their lives together in marriage. In this moment, we’re reminded that love is not about perfection, but about commitment—choosing one another, day after day, even when things get messy, or difficult, or dark. And through it all, we trust in love to guide us, just as God’s love guides us through life’s journey.
Declaration of Intent
[Officiant turns toward Groom and Bride]
Groom, Bride, you are about to make promises to each other that will last a lifetime. Before we continue, I’ll ask each of you to answer a very important question.
Officiant: Groom, do you take Bride to be your lawfully wedded wife, to have and to hold, for better or for worse, in sickness and in health, for as long as you both shall live?
Groom: I do.
Officiant: Bride, do you take Groom to be your lawfully wedded husband, to have and to hold, for better or for worse, in sickness and in health, for as long as you both shall live?
Bride: I do.
Exchange of Vows
Officiant: Now, as a sign of this commitment, Groom and Bride will exchange their vows—promises made not just to each other, but before all of us here and in the sight of God.
[Groom and Bride share their vows]
Rings
Officiant: The rings you’re about to exchange are a symbol of eternity, a reminder that your love, too, is without end. May these rings be a constant reminder of the vows you have made today, and of the love that surrounds and holds you both.
[Groom and Bride exchange rings]
Officiant: And now, by the power vested in me, and with the blessing of God, I pronounce you husband and wife. Groom you may kiss your bride.
[Groom and Bride kiss]
Officiant: Friends and family, it is my great honor to introduce to you, for the first time, Mr. and Mrs. [Name].
I pretty much just tweaked the formatting, worked in a couple little friendly jabs at the groom, subbed their names in for Bride and Groom, and ad-libbed a little bit where appropriate

making roguelike content. Mazes, monsters etc

Learning how to use Linux
- Ha! I use it to write Ansible.
  In my case, YAML is a tool of Satan and Ansible is its 2001-era minion of stupid, so when I need to write Ansible I let the robots do that for me and save my sanity.
  I understand that will make me less likely to ever learn Ansible, if I use a bot to write the 'code' for me; and I consider that to be another benefit as I don't need to develop a pot habit later, in the hopes of killing the brain cells that record my memory of learning Ansible.

My understanding is that it will eventually used to improve autocorrect, when they get it working properly.

There is no point. There are billions of points, because there are billions of people, and that's the point.
You know that there are hundreds or thousands of reasonable uses of generative AI, whether it's customer support or template generation or brainstorming or the list goes on and on. Obviously you know that. So I'm not sure that you're asking a meaningful question. People are using a tool to solve various problems, but you don't see the point in that?
If your position is that they should use other tools to solve their problems, that's certainly a legitimate view and you could argue for it. But that's not what you wrote and I don't think that's what you feel.

There are some great use cases, for instance transcribing handwritten records and making them searchable is really exciting to me personally. They can also be a great tool if you learn to work with them (perhaps most importantly, know when not to use them - which in my line of work is most of the time).
That being said, none of these cases, or any of the cases in this thread, is going to return the large amounts of money now being invested in AI.
- Generative AI is actually really bad at transcription. It imagines dialogues that never happened. There was some institution, a hospital I think? They said every transcription had at least one major error like that.
  
  This is an issue if it's unsupervised, but the transcription models are good enough now that with oversight then they're usually useful: checking and correcting the AI generated transcription is almost always quicker than transcribing entirely by hand.
  If we approach tasks like these assuming that they are error-prone regardless whether they are done by human or machine, and will always need some oversight and verification, then the AI tools can be very helpful in very non-miraculous ways. I think it was Jason Koebler said in a recent 404 podcast that at Vice he used to transcribe every word of every interview he did as a journalist, but now transcribes everything with AI and has saved hundreds of work hours doing so, but he still manually checks every transcript to verify it.

I like using it to help get the ball rolling on stuff and organizing my thoughts. Then I do the finer tweaking on my own. Basically I kinda use a sliding scale of the longer it takes me to refine an AI output for smaller and smaller improvements is what determines when I switch to manual.

simple tasks you can verify yourself and you're just rolling dice for some time saved. everything else is kinda shit

I use it in a lot of tiny ways for photo-editing, Adobe has a lot of integration and 70% of it is junk right now but things like increasing sharpness, cleaning noise, and heal-brush are great with AI generation now.

I think LLMs could be great if they were used for education, learning and trained on good data. The encyclopedia Britannica is building an AI exclusively trained on its data.
It also allows for room for writers to add more to the database, to provide broader knowledge for the AI, so people keep their jobs.

I know they are being used to, and are decently good for, extracting a single infornation from a big document (like a datasheet). Considering you can easily confirm the information is correct, it's quite a nice use case

I hate questions like this due to 1 major issue.
A generative ai with "error free" Output, is very differently useful than one that isn't.
Imagine an ai that would answer any questions objectively and unbiased, would that threaten job? Yeah. Would it be an huge improvement for human kind? Yeah.
Now imagine the same ai with a 10% bs rate, like how would you trust anything from it?
Currently generative ai is very very flawed. That is what we can evaluate and it is obvious. It is mostly useless as it produces mostly slop and consumes far more energy and water than you would expect.
A "better" one would be differently useful but just like killing half of the worlds population would help against climate change, the cost of getting there might not be what we want it to be, and it might not be worth it.
Current market practice, cost and results, lead me to say, it is effectively useless and probably a net negative for human kind. There is no legitimate usage as any usage legitimizes the market practice and cost given the results.

Just today I needed a pdf with filler english text, not lorem. ChatGPT was perfect for that. Other times when I'm writing something I use it to check grammar. It's way better at it than grammarly imo, and faster and makes the decisions for me BUT PROOF-READ IT. if you really fuck the tenses up it won't know how to correct it, it'll make things up. Besides these: text manipulation. I could learn vim, write a script, or I could just copy "remove the special characters" enter -> done.
I use perplexity for syntax. I don't code with it, but it's the perfect one stop shop for "how does this work in this lang again" when coding. For advanced/new/unpopular APIs it's back to the olds school docs, but you could try to give it the link so it parses it for you, it's usually wonky tho.

I have personally found it fantastic as a programming aid, and as a writing aid to write song lyrics. The art it creates lacks soul and any sense of being actually good but it's great as a "oh I could do this cool thing" inspiration machine

Programming quick scripts and replacement for Google/Wikipedia more than anything. I chat to it on an app to ask about various facts or info I wanted to know. And it usually gets in depth pretty quickly.
Also cooking. I've basically given up on recipe sites, except for niche, specific things. AI gets stuff relatively right and quickly adjusts if I need substitutions. (And again, hands free for my sticky flour fingers).
And ideation. Whether I'm coming up with names, or a specific word, or clothes, or a joke, I can ask AI for 50 examples and I can usually piece together a result I like from a couple of those.
Finally, I'll admit I use it as a sounding board to think through topics, when a real human who can empathise would absolutely be better. Sadly, the way modern life is, one isn't always available. It's a small step up from ELIZA.
The key is that AI is part of the process. Just as I would never say "trust the first Google result with your life", because its some internet rando who might say anything, so too should you not let AI have the final word. I frequently question or correct it, but it still helps the journey.

I wish I could have an AI in my head that would do all the talking for me because socializing is so exhausting
- Other people would then have AIs in their heads to deal with the responses.
  A perfect world, where nothing is actually being said, but goddamn do we sound smart saying it
  
  Yes

Amazing for reading docs
- Absolutely this. I've found AI to be a great tool for nitty-gritty questions concerning some development framework. While googling/duckduckgo'ing, you need to match the documentation pretty specifically when asking about something specific. AI seems to be much better at "understanding" the content and is able to match with the documentation pretty reliably.
  For example, I was reading docs up and down at ElasticSearch's website trying to find all possible values for the status field within an aggregated request. Google only lead me to general documentations without the specifics. However, a quick loosely worded question to chatGPT handed me the correct answer as well as a link to the exact spot in the docs where this was specified.

I recently had to digitize dozens of photos from family scrapbooks, many of which had annoying novelty pattern borders cut out of the edges. Sure, I could have just cropped the photos more to hide the stupid zigzagged missing portions. But I had the beta version of Photoshop installed with the generative fill function, so I tried it. Half the time it was garbage, but the other half it filled in a bit of grass or sky convincingly enough that you couldn't tell the photo was damaged. +1 acceptable use case for generative AI, I guess.