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?
It’s perfect for topics you have professional knowledge of but don’t have perfect recall for. It can bring forward the context you need to be refreshed on but you can fact check it because you are an expert in that field.
If you need boilerplate code for a project but don’t remember a specific library or built in function that tackles your problem, you can use AI to generate an example you can then fix to make it run the way you wanted.
Same thing with finding config examples for a program that isn’t well documented but you are familiar with.
Sorry all my examples are tech nerd stuff because I’m just another tech nerd on lemmy
On the inverse I’ve found it to be quite bad at that. I can generally count on the AI answer to be wrong, fundamentally.
Might depend on your industry. It’s garbage at g code.
It probably depends how many good examples it has to pull together from stack overflow etc. it’s usually fine writing python, JavaScript, or powershell but I’d say if you have any level of specific needs it will just hallucinate a fake module or library that is a couple words from your prompt put into a function name but it’s usually good enough for me to get started to either write my own code or gives me enough context that I can google what the actual module is and find some real documentation. Useful to subject matter experts if there is enough training data would be my new qualifier.
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.
This is my one of 2 use cases for AI. I only recently found out after a life of being told I’m terrible at writing, that I’m actually really good at technical writing. Things like guides, manuals, etc that are quite literal and don’t have any soul or personality. This means I’m awful at writing things directed at people like emails and such. So AI gives me a platform where I can enter in exactly what I want to say and tell it to rewrite it in a specific tone or level of professionalism and it works pretty great. I usually have to edit what it gave me so it flows better or remove inaccurate language, but my emails sound so much better now! It’s also helped me put more personality into my resume and portfolio. So who knows, maybe it’ll help me get a better job?
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 just pass the create table statements after the instructions. It does pretty good up to 2 or 3 tables, but it will start to make mistakes when things get complicated
On the plus side, it’ll generate tedious code very well - double checking it is less draining than writing it yourself. Especially because I make more typos than it does - I often use it to get a starting point, then write the business logic myself
I’ve done several AI/ ML projects at nation/ state/ landscape scale. I work mostly on issues that can be solved or at least, goals that can be worked towards using computer vision questions, but I also do all kinds of other ml stuff.
So one example is a project I did for this group: https://www.swfwmd.state.fl.us/resources/data-maps
Southwest Florida water management district (aka “Swiftmud”). They had been doing manual updates to a land-cover/ land use map, and wanted something more consistent, automated, and faster. Several thousands of square miles under their management, and they needed annual updates regarding how land was being used/ what cover type or condition it was in. I developed a hybrid approach using random forest, super-pixels, and UNET’s to look for regions of likely change, and then to try and identify the “to” and “from” classes of change. I’m pretty sure my data products and methods are still in use largely as I developed them. I built those out right on the back of UNET’s becoming the backbone of modern image analysis (think early 2016), which is why we still had some RF in there (dating myself).
Another project I did was for State of California. I developed both the computer vision and statistical approaches for estimating outdoor water use for almost all residential properties in the state. These numbers I think are still in-use today (in-fact I know they are), and haven’t been updated since I developed them. That project was at a 1sq foot pixel resolution and was just about wall-to-wall mapping for the entire state, effectively putting down an estimate for every single scrap of turf grass in the state, and if California was going to allocate water budget for you or not. So if you got a nasty-gram from the water company about irrigation, my bad.
These days I work on a small team focused on identifying features relevant for wildfire risk. I’m trying to see if I can put together a short video of what I’m working on right now as i post this.
Example, fresh of the presses for some random house in California:
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.
Any LLM I tried sucks using Rust. The book is great, you learn all of the essentials of Rust and it is also pretty easy to read.
