Asklemmy

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.

making roguelike content. Mazes, monsters etc

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 have a friend with numerous mental issues who texts long barely comprehensible messages to update me on how they are doing, like no paragraphs, stream of consciousness style... and so i take those walls of text and tell chat gpt to summarize it for me, and it goes from a mess of words into an update i can actually understand and respond to.

Another use for me is getting quick access to answered id previously have to spend way more time reading and filtering over multiple forums and stack exchanges posts to answer.

Basically they are good at parsing information and reformatting it in a way that works better for me.

Learning how to use Linux

"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.

Fake frames. Nvidia double benefits.

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

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.

My last three usages of it:

1. A translation
2. Looking up what actors from Mars Attacks had shared work on another movie. I recognized that Pierce Brosnan and John Doe Baker had done Goldeneye and wondered if there were more.
3. Name suggestions for a black and white cat - I got some funny suggestions like Oreo and a kick-ass suggestion for Domino

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.

Amazing for reading docs

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.

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 wish I could have an AI in my head that would do all the talking for me because socializing is so exhausting

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.

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

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'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).

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.

It's kinda handy if you don't want to take the time to write a boring email to your insurance or whatever.

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.

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.

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.

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.

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.

There was a legitimate use case in art to draw on generative AI for concepts and a stopgap for smaller tasks that don't need to be perfect. While art is art, not every designer out there is putting work out for a gallery - sometimes it's just an ad for a burger.

However, as time has gone on for the industry to react I think that the business reality of generative AI currently puts it out of reach as a useful tool for artists. Profit hungry people in charge will always look to cut corners and will lack the nuance of context that a worker would have when deciding when or not to use AI in the work.

But you could provide this argument about any tool given how fucked up capitalism is. So I guess that my 2c - generative AI is a promising tool but capitalism prevents it from being truly useful anytime soon.

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.

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.

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.

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.

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.

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