I use it to ask questions that I can’t find search results for or don’t have the words to ask. Also for d&d character art I share with my playgroup lol.

Idk if it counts as GenAI but I use Waifu2x to remove jpg artifacts and upscale textures to a useable state.

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.

Sometimes it’s helpful if I’m having trouble making a specific excel formula

It is sometimes good at building SQL code examples, but almost always needs fine-tuning since it doesn’t know the schema specifics.

Having said that one time it gave me code that resulted in an error, then I went back to GPT and said “This code you gave me is giving this error, can you fix it?” and all it would do is say something like “Correct, that code is wrong and will give an error.”

I’ve learned more C/C++ programming from the GitHub Copilot plugin than I ever did in my entire 42 year life. I’m not a professional, though, just a hobbyist. I used to struggle through PHP and other languages back in the day but after a year of Copilot I’m now leveraging templates and the C++ STL with ease and feelin’ like a wizard.

Hell maybe I’ll even try Rust.

AI is really good as a starting point for literally any document, report, or email that you have to write. Put in as detailed of a prompt as you can, describing content, style, and length and cut out 2/3 or more of your work. You’ll need to edit it - somewhat heavily, probably - but it gives you the structure and baseline.

I use a lot of AI/DL-based tools in my personal life and hobbies. As a photographer, DL-based denoising means I can get better photos, especially in low light. DL-based deconvolution tools help to sharpen my astrophotos as well. The deep learning based subject tracking on my camera also helps me get more in focus shots of wildlife. As a birder, tools like Merlin BirdID’s audio recognition and image classification methods are helpful when I encounter a bird I don’t yet know how to identify.

I don’t typically use GenAI (LLMs, diffusion models) in my personal life, but Microsoft Copilot does help me write visualization scripts for my research. I can never remember the right methods for visualization libraries in Python, and Copilot/ChatGPT do a pretty good job at that.

OP seems to be talking about generative AI rather than AI broadly. Personally I have three main uses for it:

• It has effectively replaced google for me.
• Image generation enables me to create pictures I’ve always wanted to but never had the patience to practise.
• I find myself talking with it more than I talk with my friends. They don’t seem interested in anything I’m but chatGPT atleast pretends to be

Genuinely, nothing so far.

I’ve tinkered with it but I basically don’t trust it. For example I don’t trust it to summarise documents or articles accurately, every time I don’t trust it to perform a full and comprehensive search and I don’t trust it not to provide me false or inaccurate information.

LLMs have potential to be useful tools, but what’s been released is half baked and rushed to market as part of the current bubble.

Why would I use tools that inherently “hallucinate” - I. E. are error strewn? I don’t want to fact check the output of an LLM.

This is in many ways the same as not relying on Wikipedia for information. It’s a good quick summary but you have to take everything with a pinch of salt and go to primary sources. I’ve seen Wikipedia be wildly inaccurate about topics I know in depth, and I’ve seen AI do the same.

So pass until the quality goes up. I don’t see that happening in the near future as the focus seems to be monetisation, not fixing the broken products. Sure, I’ll tinker occasionally and see how it’s getting on but this stuff is basically not fit for purpose yet.

As the saying goes, all that glitters is not gold. AI is superficially impressive but once you scratch the surface and have to actually rely on it then it’s just not fit for purpose beyond a curio for me.

AI isn’t useless, but it’s current forms are just rebranded algorithms with every company racing to get theirs out there. AI is a buzzword for tools that were never supposed to be labeled AI. Google has been doing summary excerpts for like a decade. People blindly trusted it and always said “Google told me”. I’d consider myself an expert on one particular car and can’t tell you how often those “answers” were straight up wrong or completely irrelevant to one type of car (hint, Lincoln LS does not have a blend door so heat problems can’t be caused by a faulty blend door).

You cite Google searches and summarization as it’s strong points. The problem is, if you don’t know anything about the topic or not enough, you’ll never know when it makes mistakes. When it comes to Wikipedia, journal articles, forum posts, or classes, mistakes are possible there too. However, those get reviewed as they inform by knowledgeable people. Your AI results don’t get that review. Your AI results are pretending to be master of the universe so their range of results is impossibly large. That then goes on to be taken is pure fact by a typical user. Sure, AI is a tool that can educate, but there’s enough it proves it gets wrong that I’d call it a net neutral change to our collective knowledge. Just because it gives an answer confidently doesn’t mean it’s correct. It has a knack for missing context from more opinionated sources and reports the exact opposite of what is true. Yes, it’s evolving, but keep in mind one of the meta tech companies put out an AI that recommended using Elmer’s glue to hold cheese to pizza and claimed cockroaches live in penises. ChatGPT had it’s halluconatory days too, it just got forgotten due to Bard’s flop and Cortana’s unwelcome presence.

Use the other two comments currently here as an example. Ask it to make some code for you. See if it runs. Do you know how to code? If not, you’ll have no idea if the code works correctly. You don’t know where it sourced it from, you don’t know what it was trying to do. If you can’t verify it yourself, how can you trust it to be accurate?

The biggest gripe for me is that it doesn’t understand what it’s looking at. It doesn’t understand anything. It regurgitates some pattern of words it saw a few times. It chops up your input and tries to match it to some other group of words. It bundles it up with some generic, human-friendly language and tricks the average user into believing it’s sentient. It’s not intelligent, just artificial.

So what’s the use? If it was specifically trained for certain tasks, it’d probably do fine. That’s what we really already had with algorithmic functions and machine learning via statistics, though, right? But sparsing the entire internet in a few seconds? Not a chance.

Edit: can’t beleive I there’d a their

When troubleshooting, it’s nice to be able to ask copilot about the issue in human language and have it actually understand my question (unlike a search engine) and pull from and reference relevant documentation in its answers. Going back and forth with it has saved me several hours of searching for something that I had never even heard of a couple of times.

It’s also great for rewriting things in a specific tone. I can give it a bland/terse/matter-of-fact paragraph and get back a more fun or professional or friendly version that would feel ridiculously cringe if I attempted to write it myself, but the AI makes it work somehow.

Troublehsooting technology.

I’ve been using Linux as my daily driver for a year and a half and my learning is going a lot quicker thanks to AI. It’s so much easier to ask a question and get an answer instead of searching through stack overflow for 30 minutes.

That isn’t to say that the LLM never gives terrible advice. In fact, two weeks ago, I was digging through my logs for a potential intruder (false alarm) and the LLM gave me instructions that ended up deleting journal logs completely.

The good far outweighs the bad for sure tho.

The Linux community specifically has an anti-AI tilt that is embarrassing at times. LLMs are amazing, and much like random strangers on the internet, you don’t blindly trust/follow everything they say, and you’ll be just fine.

The best way I think of AI is that it’s going through a bubble not unlike the early days of the internet. There was a lot of overvalued companies and scams, but it still ushered in a new era.

Another analogy that comes to mind is how people didn’t trust wikipedia 20 years ago because anyone could edit it, and now it is one of the most trusted sources for information out there. AI will never be as ‘dumb’ as it is today, which is ironic because a lot of the perspective I see on AI was formed around free models from 2023.

Software developer here, who works for a tiny company of 2 7 employees and 2 owners.

We use CoPilot in Visual Studio Professional and it’s saved us countless hours due to it learning from your code base. When you make a enterprise software there are a lot of standards and practices that have been honed over time; that means we write the same things over and over and over again, this is a massive time sink and this is where LLMs come in and can do the boring stuff for us so we can actually solve the novel problems that we are paid for. If I write a comment of what I’m about to do it will complete it.

For boiler plate stuff it’s mostly 100% correct, for other things it can be anywhere from 0-100% and even if not complete correct it takes less time to make a slight change than doing it all ourselves.

One of the owners is the smartest person I’ve ever met and also the lead engineer, if he can find it useful then it has its use cases.

We even have a tool based on AI that he built that watches our project. If I create a new model or add a field to a model, it will scaffold a lot of stuff, for instance the Schemas (Mutations and Queries), the Typescript layer that integrates with GraphQL, and basic views. This alone saves us about 45 minutes per model. Sure this could likely be achieved without an LLM, but it’s a useful tool and we have embraced it.

I use it for little Python projects where it’s really really useful.

I’ve used it for linux problems where it gave me the solution to problems that I had not been able to solve with a Google search alone.

I use it as a kickstarter for writing texts by telling it roughly what my text needs to be, then tweaking the result it gives me. Sometimes I just use the first sentence but it’s enough to give me a starting point to make life easer.

I use it when I need to understand texts about a topic I’m not familiar with. It can usually give me an idea of what the terminology means and how things are connected which helps a lot for further research on the topic and ultimately undestanding the text.

I use it for everyday problems like when I needed a new tube for my bike but wasn’t sure what size it was so I told it what was written on the tyre and showed it a picture of the tube packaging while I was in the shop and asked it if it was the right one. It could tell my that it is the correct one and why. The explanation was easy to fact-check.

I use Photoshop AI a lot to remove unwanted parts in photos I took or to expand photos where I’m not happy with the crop.

Honestly, I absolutely love the new AI tools and I think people here are way too negative about it in general.