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.

"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.

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.

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.

I use it to re-tone and clarify corporate communications that I have to send out on a regular basis to my clients and internally. It has helped a lot with the amount of time I used to spend copy editing my own work. I have saved myself lots of hours doing something I don't really like (copy-editing) and more time doing the stuff I do (engineering) because of it.

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'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 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

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.

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.

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.

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.

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…

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.

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