from curbstickle@anarchist.nexus to selfhosted@lemmy.world on 27 Jun 13:23
https://anarchist.nexus/c/selfhosted/p/757813/selfhosted-ai
Yup, I’m posting another this week. Sorry.
This week I’m hoping we can wrangle a solution around AI and our selfhosted community. There are plenty of strong opinions (both pro and con), but one thing is for certain - there needs to be better disclosure in promo posts. Two options (that aren’t mutually exclusive):
- Any posts of an AI focused, AI Developed, etc software gets an [AI] tag. No, a [Not-AI] tag is not needed to accomplish this, thats kind of a “non-golfer” sort of tag.
- Comment requiring an AI disclosure response to every promo post, if its not detailed in the post itself. Specifics (generating docs for commands, translation, whole-boat vibe-coded this app, etc) would be requested.
I will say that having disclosure and/or tagging would mean that comments that just say “slop” or “fuck ai” or whatever would be off topic at that point, that information is already provided, so its just noise (and sometimes pretty uncivil - I’ve been light on that for now due to the need for a rule on this).
The tag [AI] would make it easy to filter out (or search for, if that’s your thing), but there is a wildly different degree of AI use out there, and from the posts with a positive score, its usually due to responsible AI use (translations, a snippet they had to do something obscure with, available to use with AI but doesn’t require it, whatever), which is why I think the disclosure has a place as a benefit to everyone.
Please provide any input or alternative options on this, and I can then put it to a vote like the last one. Comments seem to be the best approach without involving something off-site, but if you have a better idea/option, please share.
threaded - newest
Alternative: make a separate “selfhosted-ai” community for the sloperators.
Just to point out a few projects that allow AI contributions:
If you want all projects related to AI in a different community, it may be easier for you to start “selfhosted_without_ai” or something.
Indeed, AI is a tool, and the human should be an expert who verify its work. What I don’t like are posts about apps that are completely vibe-coded without any thought put into them, which pose dangerous security risks.
Thats the reasoning behind the disclosure bit, I agree its a tool, and great when used correctly.
But if you try and use a hammer like a drill, you’re gonna have a bad time.
It is not ‘just a tool.’ It is not “great.” Too many people focus on how it is used and not how it is created, how it affects us, and how it affects the world.
I’m just going to shortcut this and say two things:
I can guarantee the overwhelming majority (if not all) of your issues have nothing to actually do with LLMs and everything to do with corporations. Power use, data center buildouts, market impact, whatever - none it is an an llm problem. LLMs are just another piece of software, thats all.
Your personal opinion on this, as well as mine, does not change the overall conversation here. So how about we just stick to the topic at hand?
LLMs are inextricably tied to nvidia gpus. Local or cloud, the technology exists to help the shovel salespeople. The gold diggers, everyone this tag is supposed to segregate, have been misled by corporations. Without their lies, and a pliant media, this tag would be unnecessary, and llms would be rolled out in a more limited and responsible way. To promote different uses of gold during a gold rush is going to inflate the bubble and enrich the rich, unless it is properly contextualized. Technology does not exist in a void, pretending it does digs us a deeper hole.
I run my local models on a Mac mini m2, but I could also be using AMD (ROCm), Intel with OpenVINO, or just CPU. Simple edge applications I could even use something like an RK3588.
Being tied to NVidia is marketing from NVidia, not the reality of LLMs.
Congrats, you are in the 1%. And that is exactly the type of additional context I think is necessary when discussing it, thank you.
Sorry, I’m not following here. Are you suggesting I’m in the 1% of income earners? Because if so… LOL not even close, I’m barely in the top 40% by rough math.
Just to note, an apple silicon Mac is one of the most efficient (dollars, wattage, whatever take your pic) ways to run an LLM. Mine was a build target for iOS stuff for a client I’m now repurposing, that was a refurb that cost about $600.
I can’t even buy a GPU for that price these days.
You are in the 1% of llm users.
Do you think anybody is choosing m2s over nvidia? Everybody running on cpu dreams of being rich enough to do real gold digging on an ampere. Amd is the only direct competitor, an order of magnitude smaller, and supports fewer models. I don’t think any hobbyist has one of these alternatives at the top of their wishlist, they are substitutes.
I have two clients I just set up on-prem LLM for with a cluster of Mac studios. Another already had about a half dozen custom servers with radeon pros doing a different job which got repurposed for on-prem.
I don’t think the wishlist really matters, honestly. That’d just be pointing to the marketing team at NVidia IMO.
I actually don’t have any really current NVidia hardware myself, I have mostly AMD GPUs, though ive been looking to pick up an Intel for AV1 purposes. I’d also mention that I recommend apple often (for this specific purpose only) due to their efficiency and power use.
In any case, that doesn’t change the reality here - there is no single specific manufacturer that must be used, and all an LLM is, is software. Its not to blame for what companies are doing any more than Linux is to blame because its preferred as a server OS.
OK, but still, just a clarification like “I’m not buying nor will I ever buy nvidia chips, now here’s a thing I made with ai…” is enough context, in my opinion. Just blindly saying “ai is good for this” is promoting the bubble, as the vast vast majority of llm users are running nvidia chips [either locally or through cloud providers like Anthropic].
Also, whatever financials you showed to convince them it was a good investment, whatever type of business it is, I think it was bullshit. I haven’t seen any proof of efficiency gains at any company rollout of ai, certainly not on macs. Most companies are currently pulling back on token usage is my understanding. ROI has been unmeasurable so far. At best, you informed your clients explicitly this was a highly speculative purchase and may not benefit them.
Edit: []
Thats certainly a take.
I don’t show financials or propose these decisions, I get paid to design and sometimes implement.
As far as whether or not its a benefit, I’m going to have to completely disagree. As I previously mentioned - its a tool. They are great at detecting potential security issues in code data extraction and classification (especially with unstructured or poorly structured sources, like PDFs), knowledge base searches (especially where that knowledge may be spread across multiple internal sources like a wiki, memos, miscellaneous docs, etc), doc review for tone to meet standards, etc.
Your statement that it essentially doesn’t pay to use llms is intrinsically tied to the OpenAI/MS/NVidia/Anthropic/etc “everything can be done with AI now!” marketing nonsense just the same as believing it has payoff for all scenarios. You recognize the “all uses are good uses” as being complete bs, but you’re jumping to “that means no uses are good uses”.
And that is decidedly not true.
The best example is that data ingest I mentioned. I had a client looking to bring in a bunch of differently formatted forms to a database. What they had been doing was taking their regular employees who handle these forms and using them for data entry - a pretty poor use of their time.
Instead, these scans were evaluated by a tuned model specific to their needs. Each form has a unique ID (though the way it could be numbered was very different), which then gets assigned to one of these folks for review at ingest. They are given a new unique number, and a verification flag (3 stages - first employee review, second employee review, and final import acceptance) which was basically the same flow as the previous setup.
The difference is that each person didnt need to hunt across the form to find the details. When the comparison comes up for approval at each stage, they get the snippet being brought in and the field its being applied to. It can be approved for that field, sent back for reevaluation, or sent for human only review (often this is because the scan sucked).
The project took less than 10% of the original timeframe, and the people handling the forms (and previously assigned for ingest) didn’t end up with the stupidly increased workload that originally got assigned.
Again, using a tool at what its good for is what’s important. Using it for what you think that it can do (ie: the executive method) is just piss poor practice due to easily convinced c suite who gobble up marketing nonsense.
Edit: For the record, hardware costs were under $50k. The consulting costs themselves were higher than that, and considering it was to originally take over a year to do, I’d easily bet it was a cost benefit even if they threw out the hardware after (they didn’t, it got repurposed, its not needed for new forms).
I don’t think you need hardly any hardware to do ocr. USPS started doing reliable ocr on 80s hardware. You really think an ai cluster is necessary for that?
Anyways, cool anecdote, not an actual financial study or report, and very long-winded honestly.
Post-edit reply: wow, that’s kinda fucked up not to disclose that they disassembled it already. Looks like they found better uses. That’s your success story?
OCR <> data ingest
OCR wouldn’t work, as I mentioned, because of the varying structures of the forms.
I’m sorry my answer was too “long winded” for you, I was trying to be informative, but clearly you aren’t interested in that. Enjoy your day.
Don’t think that’s true. You can run the whole form through, come out with an identical pdf with searchable/copyable text. Even a completely novel form uses the same alphabet. Add some regex to pull out the fields you need to enter, and on failure give it to a human. All of that can be done with python on a raspberry pi. A decade ago.
github.com/ocrmypdf/OCRmyPDF
You’d be wrong.
The fields aren’t all the same kinds of values, which requires relationship between the data to be evaluated for entry.
You’re assuming this is transposing contents, which was not the issue. Your example is what was initially planned and halted before transitioning to the approach I helped deploy.
That’s how you sound.
Edit: [Completely new information to me, completely different justification for using a supercomputer over a raspberry pi, now the third attempt (1 it required ocr, 2 forms have different structures, 3 logical relationships between data (if/else statements)).]
So I’ll go back to my previous comment; you’re not actually interested in understanding the use, you have a pre-determined (and uninformed) view of use and operation, and providing that information as an example is “long-winded”.
Ill be done with this discussion now. Enjoy your day.
This is the only technical detail [about the need for an llm cluster] in the whole 500 word comment.
Edit: []
There is absolutely zero “AI” involved in the development of any of these. They just use computer programs. No actual intelligence apart from humans.
I think you may be misunderstanding the terminology here.
AI is a general term. LLMs are a subset, as are ML, DL, ANNs, NLP, CV, Expert models, etc.
Today you would define what we have as ANI, where the “N” stands for “Narrow”. This is also known as “weak” AI.
What you’re referring to would be called AGI, where the “G” stands for “General”, where an AI would have a human degree of intelligence. This is pure concept today, and does not exist.
Also on the list would be ASI, where the “S” is for “Super”, where the AI in question has more collective intelligence than humanity across all domains. This is purely hypothetical.
But AI has existed for decades. The first application I know of is Dendral, which was created in the 1950s to analyze mass spectrometry data to identify organic molecules. This was what’s called an Expert model - basically a lot of if-then statements, and led to things like MYCIN.
We don’t need to redefine words here.
There already are.
I’d argue that Lemmy and piefed need a “sub community” or community taxonomy strucutre, but that’s kinda out of scope here.
this comment is a perfect example of what @curbstickle@anarchist.nexus is trying to eliminate/prevent.
Knee-jerk “noise”!
The post asked for alternative options. I suggested an alternative option. It is not knee-jerk, and it is not noise.
For the grifters who promote the myth of “AI”. Let them have their own delusional echo chamber.
+1
Home-AI oriented channels like Reddit’s localllama are filled with self promotion garbage, and more will trickle here over time… I’m not even against self promo or heavy coding assistance, but 9-times-out-of-10, the linked repo is nonsense, or straight-up fraudulent. And being obviously vibe-coded is a common tell.
Good to get ahead of this.
Also, +1 on supressing driveby insults. If the post is tagged up front, there’s no need. That being said, it should be okay for users to call out an obvious grift, or a “nonsense repo” that’s actually pure slop.
Especially if the disclosure is blatantly a lie, absolutely. I’d also say if you see any indicators that they are lying in the disclosure, its still worthy of reporting - but I would say report and separately message the “why”, to limit visibility of seeing those indicators.
This sounds like a review / gating problem. Getting people to self filter / self gate is never going to work, and if it does it will work probably on the wrong people.
Also:
Anything with an [AI] tag, first thing in the title, will have a drive-by downvote issue.
Not sure how to deal with that, or if its even a concern.
EDIT:
Maybe it should be something else that’s not such a loaded keyword?
[ML] for Machine Learning? [SAI]? [LAI]?
I’ve been messing with ‘AI’ for a decade, and even I hate what the term has come to represent.
Oh I’m sure it will be. I don’t know if its a concern though - TBD I suppose.
TBD indeed. But it will effectively ‘downrank’ posts and their visibility, maybe into the negative vote range. I’ve seen highly negative scores across the board in more machine-learning focused subs, and that’s without a tag that catches the eye so easily.
I think even modifying the acronym could make a difference, though (as I ninja edited).
I do like the idea of a different tag, still easy to filter but less of a target like the ai generated communities out there.
Yeah. Just not sure what it should be, heh.
I will say, if it still has “AI” in the tag (like [LAI] or whatever), it would play nicer with keyword filters.
For what it’s worth, I asked my self-hosted LLM (MiMo 2.5, no network access outside my desktop), and it came with [AIT] (AI-Topic).
…I think that’s my favorite so far. [AIP] would work too.
I feel like that “obfuscates” the tag enough to blunt impulse downvotes in /new and feeds, without being deceptive or anything.
Actually both are pretty good - AIT for it as a more discussion oriented, AIP for a project post.
I like it, I think something like that would be a great idea
Oh, both! Yeah. I didn’t even think of that, but [AIT]/[AIP] as separate tags makes a lot of sense.
I’d like being able to filter by either, actually.
I guess two tags runs the risk of “rules too complex for some to follow,” but that’s more of a moderation load question. I have no say in that, heh.
Where should the line be drawn for what is AI coded vs AS assisted (in some manner) and thus tagged?
XerahS is very openly coded with AI and should be tagged. But what about the recent debate about the use of LLM in cURL?
So thats one of the questions that will need to go to a poll, but if I were to give my opinion it would be that any use would mean a tag, and the disclosure area is where it can be detailed.
Otherwise we’d end up with a bajillion differing tags, so a disclosure section makes more sense.
Not tagging for assisted would also mean setting arbitrary lines, and would be way too subjective imo.
So when I write code, I regularly ask an LLM how to do things. A few examples from my history is how I could overlap rows when generating PDF files (have a library for this), how I could assign an empty Char and to create a singleton class. A LLM never changes any of my files, I use it as super-search-engine.
Would that constitute an AI tag?
Yes, because it is a bit different than a search engine. It may not be changing the files, but it is telling you the way to do it. It might give you an outdated method/pattern, it might ignore conventions, and most importantly, it doesn’t really understand the problem its solving. Its not finding the optimal answer, its finding the most common.
So the resulting answer may work, but not necessarily be right. In a disclosure (see the new thread) that would be referred to as “hint” for lllm use.
That doesn’t mean the answer you got was necessarily wrong either, just an answer based on an amalgam of the most common for all the code fed into the model, no matter when the code was written.
It would be put into an ai disclosure, so it qualifies for a tag. Make sense?
Makes sense, thanks for taking the time to explain. <3
Yes, since “AI” doesn’t exist, maybe we should use more accurate terminology. That would certainly deter those who don’t believe in the imaginary grift in “AI”.
My 2 cents are that the issue is promotion not AI, if people started promoting stuff made without AI that would still be spam.
From the rules:
I would propose making this the requirement and not an exception, forbid all promotion of closed source, and allow the 10% requirement for open source projects.
Unfortunately the comments I’ve seen and the reports I get would disagree. Even on older accounts that post and comment plenty.
I like the AI tag idea. I’m someone who has what I’d call a noderate approach to AI, not an AI bro but any means but I’m also okay with some things built with AI if they’re done with care. If others don’t want to see it, fine, then that’s what a tag could be useful with. However the fuck AI/slop comments on something that admits to being AI is annoying to me. (We know it’s AI, they literally said it is).
If it becomes too much content, then yes would be okay with bi-forcating the community, buy only after it becomes a problem.
I’m not consistent about it yet, but because of exactly this, I’m trying to differentiate the two when I talk.
Responsible automation? I use ML or machine learning.
The grift consuming the world? A Tech Bro? “AI”
I think one of the saddest things is the conflation between the two, like you can’t even talk about one without invoking the other. Or it opening up that whole ethical debate, when you’re just talking about, like, a 100M transcription model trained by one research in some university on a potato.
Yeah it’s heresy on Lemmy, but I do find it genuinely useful. My only regret is that I have to use Claude/Anthropic more than I’d like, which is why I have a vested interest in selfhosting myself. I’d rather figure out how to run the larger models myself and cut them off completely, but you even begin to mention that here and you’ll get downvoted to hell.
You don’t even need Claude anymore. GLM 5.2 API is good enough for 95% of the same things and vastly cheaper.
MiMo 2.5 Pro and Kimi are also very good. And then there’s Cerebras API if you just want simple things done quick.
The thing with self hosting, while awesome, is that it requires a lot of hardware and considerable time investment for what’s essentially a “base tier model,” or at best one step down for what’s still a very cheap API. I still love it, especially the privacy and control aspect, but you aren’t running Claude at home unless you’ve got a threadripper or server hardware collecting dust.
…Hence I can understand why people don’t pursue it. Especially since a cursory Google search will lead you to trying the Deepseek distillation on Ollama (which is awful).
That’s where I am okay with hardware, but can’t seem to fit the models on my 3090. I have dreams of something like an A100 someday, but not until there’s a ton of used ones that hit the market. What do you use for your hardware?
I have a single 3090!
That’s the dream GPU, these days.
And I have 128GB CPU RAM. So the best model I can run is MiMo 2.5 (a 300B model) at around 10 tokens/sec, using hybrid CPU inference.
…But that’s the worst-case scenario, for speed. It’s an IQ3_KT quant (a high quality “trellis” quantization type, but very slow on CPU), with a gigantic model that barely fits in my RAM+VRAM combined, with no DFlash or any kind of speculative decoding turned on. I could tune it to be much faster, but I mostly just want “max quality, fast enough to read as it streams, barely fits in memory” for this model.
For speed, or prompts with lots of thinking or context (like agenic use), I just run Qwen 3.6 27B now. That would fit in your 3090 no matter how much CPU RAM you have, but you have to be smart about the backend and quantization you pick. If you just use Ollama, it’s gonna tell you it won’t fit, or use some horrible default that spits out garbage.
…This is what I meant to emphasize.
It’s not just the hardware. You kinda have to be part developer, part enthusiast to even follow this stuff, it up optimally, and keep it up-to-date. If you just try to Google “best LLM for 3090,” you will get absolute garbage.
I’ll have to play around with mine then, because I’ve had not great luck with it, or at least very disappointing. The CPU offloading is fairly slow, but maybe I should try tweaking more
Be sure to try the ik_llama.cpp fork. Basically, it specializes in MoE CPU offloading on Nvidia cards, and more efficient quantization types than mainline llama.cpp:
github.com/ikawrakow/ik_llama.cpp/
And see this repo for specific 3090 configs: github.com/noonghunna/club-3090
Honestly I should just write up my setup in this community too.
The drive by down voting doesn’t bother me at all. I sense that it does intimidate quite a few here. To me it’s pretty darn silly because it’s no longer a filtration mechanism as it was once intended, and now has become a way to vent displeasure, angst, and inner turmoil. However, it is what it is. I can deal with that with ease.
The curb stomping is really the issue to me. I realize there are 8.4 billion other people on this planet and few will align with all of my core beliefs and convictions, which I see as a positive; yaaay diversity! I’m willing to give the space to agree-to-disagree and still be cordial and supportive where it’s needed. (eg: the *arr stack) All I want to do is hang out with selfhosters, learn from them, and share with others what little knowledge I’ve gained along the way. I have no other agenda.
I agree with the [AI] tag. I’m not really sure why that would trigger someone more than [SOLVED], and I agree with the 30 days in the hole. Two weeks would have sufficed imho, but 30 is fine.
Thanks @curbstickle@anarchist.nexus
I agree, there’s valid points on both sides, let’s be civil and request posts are tagged accordingly so that they can be filtered.
Respectful coexistance, is the path forward.
good idea
it won’t solve the “noise” problem though. I was relatively active on !imageai@sh.itjust.works and we were constantly nagged by sloppies even though the community is clearly dedicated to generativeArt
No, but with a rule in place like these, its clearly out of place and can be removed. I don’t harbor any delusions about not seeing those sort of comments.
Would be nice though. And I like being nice.
Maybe y’all would get less hate if the sub was called “generativeArt” instead of grifterly claiming to be “AI”.
i joined the community, i didn’t create it.
I want a community where people can use AI to help build a tool and be able to post about it here. But unfortunately, I’m just not seeing that. The AI-generated apps seem to be coupled to a drive-by, AI generated post (and comment replies) all full of em dashes and the standard Claude slop language.
So, yes, mandate an AI tag. Hold posters to it and remove violators, because it seems to always be the same class of “contributors” that are cosplaying as software developers.
Not sure if your rule changes are touching this, but the worst offenders I don’t want to see here are:
The people doing that remind me of the people who would approach me 20 years ago saying “hey I have an idea for an app I want you to build and I’ll give you 5% of my company. It’s like Facebook for dogs, but I need you to sign an NDA before I say any more”.
The first bullet is, the other two are covered in the current rule 7 that just went live this week.
While part of promo, this is just about its own item here. In part because it could be something like “I wrote some of this script, got some ai help to talk to this closed device, here’s what I’m using” which doesn’t really fit promo, but still garners a lot of negative attention and comments.
I’m a bit hopeful this one would be of slightly broader benefit than just the straight up promo posts (which has a good amount of requirements now to filter out the garbage, though it does put some delays on f/loss projects that are well intentioned).
Just found the other rule post. Looks great!
Sure, that’s github
Fine, but others including myself want that slop as far away from here as possible. Maybe start another community? I suggest calling it c/vibehosted.
And there are people like me who are fine with moderate AI use and would rather judge the project themselves rather than have them rejected outright.
Maybe there should be a community poll
Why a vote to switch up an existing community? The admins have proposed the [AI] tag to mitigate slop projects.
You said you wanted a community to post vibe coded projects, go ahead and set it up. I don’t see why it needs to be foisted onto c/self hosted, unless you have some vested interest in boosting sloppy mcslopface projects.
I’m not sure I understand. First off I’m not the same person as GP. Second, the admins are proposing an AI tag, which I’m supportive of. I’m just saying that I am OK with AI-assisted projects being posted to this community (with the AI tag of course)
i agree with you. i have been working orofessionally as a software developer for over 27 years. i’ll use ai to help research something but i cant atand low effort full ai projects being posted.
i always saw non devs using ai to fully generate something for them personally to fix a very custom need but why do these people post projects thry honestly had no hand in.
Man it is great for creating custom apps to scratch your need. I have custom programs to filter out blocklists for one country and dynamically update firewall rules on unified gateways. Stuff that well never be put in as it would hurt their paid subscription.
I really like having the disclosure comment pinned for a more nuanced explanation of what, if any, AI went into a project or post. I think just a tag can’t capture the levels of AI use.
I’m personally a never-genAI, but, unless we go No AI as a community, I don’t think it makes sense to group all projects that touch AI for documentation with all that use it for testing with all that completely let the AI generate all their code, etc. And I don’t think setting a threshold for which get tagged makes sense either. Basically, a tag is misleading no matter how it’s implemented.
Disagree. Just deal with people that aren’t contributing in a positive manner like normal. It’s easy to identify posts that are dealing with AI and it’s easy to ignore them.
It is.
But people don’t do that. They send in a whole bunch of reports, sometimes multiple with the reason changing to the same variation.
So something is needed here.
Yes this is needed. Thank you for the proposal here.
I would suggest that this probably needs to be really explicit about any AI involvement, i.e. a minimum if AI is used in any capacity in the coding process, it should require the tag. And ideally an explanation if it was used in other parts of the process.
That last post that came up said they used AI ‘for code review only’. In my mind even that deserves the tag, because these terms are so easy to work around. Someone can ‘code up’ the following:
#include <studio.h> int main(void) { printf(“Program that does X thing”); }
(yes, I know the main arguments are not written correctly. You get the point)
and then have the AI reviewer ‘fix’ their code by doing all the actual work. A strict requirement for this tag, for any AI involvement in the creation of the code seems like the key. The code part is going to be where the security issues crop up, and where it’s really important to know who or what is producing the code you’re about to run on your home server.
I think we’re fairly used to a world where people use templates for their websites, documentation, etc. AI use there bothers me less, but an honest disclaimer saying what the AI did would sure go a long way to reducing the hate comments. I think people will still drive-by downvote, but that can’t (and IMO really shouldn’t be) prevented. But without a rule, people aren’t going to be honest.
The scary part is just how emboldened people feel nowadays to just entirely use an AI for all the coding, documentation, website, and then not even put their name on the project. These to me feel like borderline state actor trojan horses disguised as open-source projects.
Legitimate open source developers can spend years writing code to do something very sinplle but useful, and for them to be drowned out by a bunch of completely AI driven, slop posts really bothers me.
Thanks for grappling with this @curbstickle@anarchist.nexus
If you don’t delineate, it will simply be easier to tag everything ai as there was ai involved somewhere and you’re less likely to need to defend yourself.
Actually might be easier to do [AIless]
I think this should be a thing. At the same time, I would also want something similar for funding or platforming fascists, but that is unlikely to end up being done. I think a simple tag, the [AI] one would work, is the best current solution. I think extra detail in the post is a good thing to do, for example AI assisted documentation, AI assisted bug finding, AI assisted vibe coding. They are all different and have different effects on the product and community. If someone uses AI to find bugs in their own code I am all for it, that is a great use if it. If they use AI to write their login system I am not keen at all given the likelihood of intense security issues and the low likelihood that they will ever fix it.
Ooh that would be good
I wonder if there is a database somewhere…
we can vibecode one together!Promoting the imaginary grift of “AI” is almost the same thing as promoting the fascists who are profiting.
I would still prefer an additional [Non-AI] tag. Even if people are arguing against it - it is not same omitting an [AI] tag and consciously saying “I never used and never will use AI”. And the latter is the thing most users who want the AI-tag are looking for.
Same. It removes the ability to have plausible deniability of “oh I just forgot to tag it”—no, if you tagged it “non-AI” and it was actually vibe-coded, you clearly deliberately and consciously lied.
I’m going to actually +1 this as well.
sciactive.com/human-contribution-policy/
Yep. It is a time-suck to see an interesting new project only to check it out and find out it’s AI slop. For some apps, it doesn’t bother me… They may not require the access or stability of critical apps. Other times, I just can’t trust a slop app, and it would be very helpful to know which it is in advance.
I don’t have a problem with AI. I have a problem with vibe-coded apps released as a one-shot and then never maintained or supported. That’s slop.
I also have a problem with the trace apps (lifttrace, nutritrace, etc.) because while they’re entirely vibe-coded, they are actively developed, but they’re posted here by a brand promotion account that doesn’t otherwise contribute to the community. If there’s any “x% self-ptomotion” threshold, they fail it, because it’s 100% self-promotion.
I know I also reported another post as slop recently but I don’t remember what it was.
Yeah. Abandonware isn’t cool generally
Honest question intended to spark discussion.
Does this mean that all “single developer” projects can be considered abandonware (that aren’t open source/forkable)?
Or really “all” non open source software really. Companies “can” die.
IMO, abandonware means software that is a dead-end upon its very release, with no hopes or plans for anyone to every build upon it. Abandonware is generally not extensible, follows no good design philosophy that would let someone else build it up, and embodies essentially nothing.
Even a 100-line throwaway Python script has more utility to someone when it is published on PasteBin or whatever. But something like a binary executable released with no source code, with no support, and with no intent by the developer to ever make anything more of it, that’s abandonware.
Thanks for the definition!
I’m tracking what you’re saying.
Not with f/loss, just account age and they are above the threshold there.
Self hosted AI is such an oxymoron.
How so
“Open source AI models” are a lie. They all are leftovers from SaaS companies. “Self hosting AI” will not only never be competitive with these companies closed source offerings in any meaningful way, but also, the moment they stop publishing open weight models, there is no chance in hell that new, community driven ones will pose any threat to SaaS products.
Not a fan of a tag, since it’s not transparent enough. Sounds like every minor use of AI would warrant a tag, which seems past the point.
The disclosure comment I feel works well. People that care about if/how AI was used can check it to get a proper impression of the scale of and workflow for AI usage, and those who don’t care can ignore it.
I don’t have a problem with people talking about different open source technologies.
But I do have a problem with this comm promoting the grift that “AI” exists.
What exactly is this post about? Chat bots? Image/video processing? Content generation?
None of this stuff is “AI”. Please don’t label it as such. It’s grifter nonsense.
I think tags are a good idea. I would change the tag to [AI / LLM], and maybe some subtags like [chatbot], [image processing], etc. AI is here to stay, or a least until the US realize the hole under their entire economy (Or both in worst case scenerio) , so regulation is a good solution to this. (In my humble opinion)
The cat is out of the bag. AI is common place in coding. I dont see why it matters if it was developed with AI or includes AI. Its the same product with/without.
AI copies from the middle of the curve of quality averages, throwing out the highest and lowest quality examples (for being different).
Use of AI does have bearing on quality.
A skilled team can undo that harm, and a particularly unskilled team may be better off with AI than without.
But it is incorrect to claim that AI has no impact on quality of outcome.
Eh people vastly over estimate how good of a cider they are. If everyone was as good as they say theybarr online we would not be having all these bugs in the software to begin with.
Fair point.
Sure it can have a bearing on quality amoung many other factors that can have a bearing on quality. I dont need to judge all those factors I can judge the end result.
i want a community where AI is not tolerated at all. ai is a corporate grift and there’s no room for it in a self built community founded on resistance of the tech status quo
Sounds like a good solution for me. I think most users dislike completely vibe coded apps, not ai supported apps. So maybe we should be more specific here.
For example: [Vibe-Coded]
This would also support new users finding the right tag.
Personally. I want an AI tag so I know to look more carefully.
I don’t mind AI speeding up a skilled engineer.
But I do mind a crypto bro, turned AI bro, with little experience, too eagerly advertising their vibe coded app.
Its too exhausting to audit everything I may be interested in and the AI tag would help me to budget and optimize my time.