Ask Lemmy

They are useful. My teams are seeing modest productivity gains by self reporting, but I'm going to give it another six months to see if it shows up in actual metrics.

I'm enthusiastic about AI but I remain skeptical. I don't mean to always be contrarian but I'm dead in the middle and everyone who says they are great or terrible I tend to offer my experiences in the other direction.

They are not to be trusted to handle customers directly, but they can assist experts when they have to step out of their expertise. For example I can't write Python, but I've been coding for 30 years. I can certainly write some good directions on what needs to be done and I can review code and correct it. So AI has let me write a bunch of complex Python scripts to automate minor parts of my job to let me focus on the hard parts.

For example I can execute GDPR delete requests in a few moments where doing it by hand with Hoppscotch or Postman probably takes me 5-10 minutes. We have a multiple systems and sometimes I have to delete multiple profiles for a given request.

It's great at rubber ducking as long as you think critically about its proposed solutions. It's fine at code review before sending it to an actual person for review. It flags non-issues but it also flags a few actionable fixes.

The important thing though is to never trust it when it comes to anything you don't know about. It's right a fair amount of the time, depending on what you ask, but it's wrong enough that you should never, ever rely on it being right about something. The moment you put your life in its hands, it'll kill you with nothing to say to the survivors but, "Your right about that. Sorry, that was my mistake." And it isn't even sincere. Because it can't be. Because it doesn't think or feel anything.

It enables unskilled people to punch above their weight class, similar to giving a chainsaw to a toddler.

I've used them a little for coding, but it's not always correct. It's often incorrect in subtle ways. Or inefficient in non obvious ways. It gets worse as you build more.

Often it's better overall to do it yourself if you know what you're doing. If you stick to letting the LLM do it, you won't learn much.

They’re useful and getting better, but they’re improving by burning more tokens behind the scenes, and the prices they charge only cover a fraction of the cost. Right now there is no foreseeable path to profitability.

They're annoying to be honest.

I used Qwen 3.5 for some research a few weeks ago, at first the good thing was every sentence was referenced by a link from the internet. So I naturally thought "well, it's actually researching for me, so no hallucination, good". Then I decided to look into the linked URLs and it was hallucinating text AND linking random URL to those texts (???), nothing that the AI outputs was really in the web page that was linked. The subject was the same, output and URLs, but it was not extracting actual text from the pages, it was linking a random URL and hallucinating the text.

Related to code (that's my area, I'm a programmer), I tried to use Qwen Code 3.5 to vibe code a personal project that was already initialized and basically working. But it just struggles to keep consistency, it took me a lot of hours just prompting the LLM and in the end it made a messy code base hard to be maintained, I asked to write tests as well and after I checked manually the tests they were just bizarre, they were passing but it didn't cover the use cases properly, a lot of hallucination just to make the test pass. A programmer doing it manually could write better code and keep it maintainable at least, writing tests that covers actual use cases and edge cases.

Related to images, I can spot from very far most of the AI generated art, there's something on it that I can't put my finger on but I somehow know it's AI made.

In conclusion, they're not sustainable, they make half-working things, it generates more costs than income, besides the natural resources it uses.

This is very concerning in my opinion, given the humanity history, if we rely on half-done things it might lead us to very problematic situations. I'm just saying, the next Chernobyl disaster might have some AI work behind it.

More capable than the crowd here lets on. My take is like this, unchecked capitalism is a danger to mankind. The pervasiveness of LLM’s right now is just a symptom of that. The rich are the problem, not the AI.

It is a tool; a very good one along many axes. I think people that think it isn’t good for writing code are misinformed or intentionally disingenuous. It is extremely good at that, but it is just a tool not a replacement.

But it is the applications in pure maths, virology, protein folding, etc. where it gets really interesting.

Water consumption, power consumption, and profit motives aside, they are fascinating tools.

That said, If Anyone Builds It, Everyone Dies is a fascinating take on how this could all go wrong.

In any case, I can’t understand the people that say stuff like, “It is just autocomplete on steroids,” or “it is just a probabilistic prediction tool.” Okay, but like… that’s all we are too.

Summary, interesting tools being used for profit at the expense of economies, the environment, and creative fields.

You’re gonna get a very anti-AI bias on here

They're a straight up scam.

They’re digital yes men, mostly, and really lack in the nuance when you prompt them to answer on anything you have a deep knowledge of.

They might be good given time, probably a lot of time, but right now all they're doing is allowing that well meaning roommate that puts your cast iron in the dishwasher to also ruin Wikipedia articles and fuck up open source projects.

LLMs exist, AI doesn’t.

Anyone who calls LLMs ‘AI’ is betraying they don’t understand what the labels are. Their opinions on the subject should be summarily dismissed, and ridiculed if they persist.

LLMs have vanishingly narrow legitimate use cases, none of which have proven justifiable to be wielded unsupervised.

They’re pervasive in an annoying way, and the boosters are using them for utterly ridiculous things.

They have their very limited uses. For short things they can be useful, within reason. “How do you take these results and transform them into X in Python” then take a very squinty look at it and figure out where it went wrong. Then, try asking a couple follow-ups and the code just scrambles.

For writing I’ve found they're pretty useless, because I can’t figure out how to prompt them to not sound like they’re in the marketing department and blowing smoke.

But they can be a good starting point for finding information when I’m looking for something that’s really a Reddit question, rather than something I can summarize into keywords for a search engine. Still, too often useless.

I recently had someone send me “is it cheaper to air bnb or get a hotel at $destination” and it was absurdly incorrect, as in off by a factor of two. When it would have taken mere seconds more to get correct information. I have relatives who work in professions which literally define accuracy (accounting and law) and they rely on them for stuff like that, and it’s so probably incorrect

From what I can tell, they are best used to plan mass shootings, or your suicide.

It's a fun toy to play with... but ffs keep it away from actually being used irl for serious purposes... these are not trustworthy at least not in this stage, LLMs are just public beta testing...

(Also the increse in demand in ram usage and the resulting rise in cost of consumer electronics is cringe af)

Privacy wise... yea don't plan a revolt or confess your crimes on there, unless you have an offline LLM...

lightweight models will dominate in the future, datacenter grade heavy LLMs will die off. There's no real way to profit off of the heavier models even now.

They are guessing machines, predicting the next token. At best it's equivalent to the language center of the brain, but it still needs many capabilities like logical reasoning to weight and evaluate different actions and outcomes wrt values or goals to not just mimic the behavior of thinking agents. It's one of many steps in a long line of experimentation and engineering building towards AGI but we still have no idea how close it really is, maybe 10 years, 50 years, 500 years, etc. They are useful for specific tasks like a hammer or newspaper or search engine, but because of all the fear based investing to not miss the next big thing people with more money than brains invested heavily without understanding the limitations or actually capabilities of the technology.

I think it's fascinating tech. And fun to play with. But I think a lot if the every-day use-cases are more of a gimmick. In the good old times we could look up facts on Wikipedia. Or google why the yellow light on the router started flashing and we'd find an answer on Reddit. Now we ask ChatGPT, but that alone doen't increase my quality of life. I'd rather have it sort the mess on my 8TB hdd, find a cheaper insurance company for the car. Do my stupid paperwork at home... And maybe I'd like an AI robot to do the chores for me. Laundry, dishes... So I can relax and do other things. But I feel it's still early days for the really useful tasks. AI is more useful for replacing callcenter workers, assisting programmers... And unfortunately it's bad for the environment and makes computer hardware unaffordable.

As a video producer, the AI baked into the Adobe suite is very useful (generative fill, harmonize, and neural filters in Photoshop, generative extend and AI noise reduction in Premiere, lots of older stuff in After Effects).

As far as LLMs go, I get a lot out of talking through things with Claude, or coding silly little toys that only matter to me. But I’d never trust an agent with tools or access. And Anthropic’s own research is a good place to start for why that won’t change anytime soon.

Moderately useful for basic tasks you’re going to review. Extremely useful for puff stuff like marketing where you don’t care about little mistakes. Those generic corporate emails? Done. Random picture of dude with your product? Easy.

Where it’s never going to be worth it is places you have to be 100% right. Finance is a big one. So of course they’re trying to shove it in that stuff too.

It's useful to churn through a lot of data and do tedious repetitive tasks.

You have to check the results. I've had it give me correct results and wrong results compared to known data points.

Today I tasked Gemini Pro to assist me code a quite simple web GUI in Python using NiceGUI and besides somewhat doing what I asked it to do it also added a bunch of childish emojis to buttons and removed my name from the project and replaced it with 'admin'. This is a real tool that I develop for a hand full of my very real coworkers and my boss is paying Google for this shit. Next time I much rather give the task to one of our apprentices and point them to the docu then having a supposedly 'Pro' model do random shit I haven't asked it to do.

LLMs are a.parlor truck that makes text output look natural, but massively unreliable like a game of telephone. Good for a laugh or two, but absolutely not worth wrecking the hardware sector over and not needing to be jammed into everything and endlessly nagging users about it.

Worse than web searches from a decade ago, and used to further fill results with generated slop. Certainly not ready for prime time, and the core design means it never will be for all the uses they are pretending it would be helpful for.

I hate it.

I am an IT guy, and AI has just about killed my enthusiasm for tech, I made a post about it a month or two ago, and it is still valid.

Given enough time and research it won't be too many more years before they're ready for production use. Of course that use will probably be mass surveillance and suppression of dissent.

One of my hobbies seems like it should be be easy for AI to move into. Crochet patterns are often fairly mathematically based. However every generated pattern I’ve looked at has been nonsensical garbage. Images that look cute and plausible at first pass are basically imagination. It used to be really easy to spot but it is getting harder/more subtle.

I used to work in healthcare and when I first got access to chat GPT I asked it some simple differential diagnosis questions. It gave a few very common possibilities for the symptoms I gave but completely ignore an important red flag that even a first year med student should (probably would) keep in mind.

Those can be useful, best use I've found for LLMs is figuring something out based on vague descriptions. Like if there's a word on the tip of my tongue, but i just can't recall it. Up until now LLMs have figured it out instantly.

It can have some other handful of use cases where factual information isnithat important. Maybe just venting, though with caution as it has propensity to reinforce any negative loop.

Though it most definitely isn't worth the cost to economy or the environment.

I’m currently working on a degree in a moderately research/writing heavy major, and I don’t use it at all. The things I’m researching are too niche, I don’t want my writing edited to be less interesting, and school policy prohibits it for anything but brainstorming ideas. Which, I already know what I’m interested in, I don’t need it to tell me that even if it could.

I have straight A’s and no intention of changing how I (don’t) use AI.