You must log in or register to comment.
Could you imagine a world where word of mouth became the norm again? Your friends would tell you about websites, and those sites would never show on search results because crawlers get stuck.
There used to be 3 or 4 brands of, say, lawnmowers. Word of mouth told us what quality order them fell in. Everyone knew these things and there were only a few Ford Vs. Chevy sort of debates.
Bought a corded leaf blower at the thrift today. 3 brands I recognized, same price, had no idea what to get. And if I had had the opportunity to ask friends or even research online, I’d probably have walked away more confused. For example; One was a Craftsman. “Before, after or in-between them going to shit?”
Got off topic into real-world goods. Anyway, here’s my word-of-mouth for today: Free, online Photoshop. If I had money to blow, I’d drop the $5/mo. for the “premium” service just to encourage them. (No, you’re not missing a thing using it free.)
I guess this is marketing. But … Why would you use anything besides GIMP?
After a Decade of Waiting, GIMP 3.0.0 is Finally Here!
https://news.itsfoss.com/gimp-3-release/
That would be terrible, I have friends but they mostly send uninteresting stuff.
Fine then, more cat pictures for me.
No they wouldn’t. I’m guessing you’re not old enough to remember a time before search engines. The public web dies without crawling. Corporations will own it all you’ll never hear about anything other than amazon or Walmart dot com again.
Nope. That isn’t how it worked. You joined message boards that had lists of web links. There were still search engines, but they were pretty localized. Google was also amazing when their slogan was “don’t be evil” and they meant it.
No. Only very selective people joined message boards. The rest were on AOL, compact or not at all. You’re taking a very select group of.people and expecting the Facebook and iPad generations to be able to do that. Not going to happen. I also noticed some people below talking about things like geocities and other minor free hosting and publishing site that are all gone now. They’re not coming back.
Yep, those things were so rarely used … sure. You are forgetting that 99% of people knew nothing about computers when this stuff came out, but people made themselves learn. It’s like comparing Reddit and Twitter to a federated alternative.
Also, something like geocities could easily make a comeback if the damn corporations would stop throwing dozens of pop-ups, banners, and sidescrolls on everything.
And 99% of people today STILL don’t know anything about computers. Go ask those same people simply “what is a file” they won’t know. Lmao. Geocities could come back if corporations stop advertising. Do you even hear yourself.
I was there. People carried physical notepads with URLs, shared them on BBS’, or other forums. It was wild.
There was also “circle banners” of websites that would link to each others… And then off course “stumble upon”…
Yes! Web rings!
I forgot web rings! Also the crazy all centered Geocities websites people made. The internet was an amazing place before the major corporations figured it out.
Better yet. Share links to tarpits with your non-friends and enemies
This is surely trivial to detect. If the number of pages on the site is greater than some insanely high number then just drop all data from that site from the training data.
It’s not like I can afford to compete with OpenAI on bandwidth, and they’re burning through money with no cares already.
You can compress multiple TB of nothing with the occasional meme down to a few MB.
When I deliver it as a response to a request I have to deliver the gzipped version if nothing else. To get to a point where I’m poisoning an AI I’m assuming it’s going to require gigabytes of data transfer that I pay for.
At best I’m adding to the power consumption of AI.
I wonder, can I serve it ads and get paid?
Yeah sure, but when do you stop gathering regularly constructed data, when your goal is to grab as much as possible?
Markov chains are an amazingly simple way to generate data like this, and a little bit of stacked logic it’s going to be indistinguishable from real large data sets.
Imagine the staff meeting:
You: we didn’t gather any data because it was poisoned
Corposhill: we collected 120TB only from harry-potter-fantasy-club.il !!
Boss: hmm who am I going to keep…
The boss fires both, “replaces” them for AI, and tries to sell the corposhill’s dataset to companies that make AIs that write generic fantasy novels
AI won’t see Markov chains - that trap site will be dropped at the crawling stage.
AI is the “most aggressive” example of “technologies that are not done ‘for us’ but ‘to us.’”
Well said.
Funny that they’re calling them AI haters when they’re specifically poisoning AI that ignores the do not enter sign. FAFO.
Fair As Fuck Ok?
Sheesh people, it’s “fuck around and find out”. Probably more appropriate in the leopards eating face context but this works enough.
I’m glad you’re here to tell us these things!
What are you talking about? FAFO obviously stands for “fill asshole full of”. Like FAFO dicks. Or FAFO pennies.
First Albatross, First Out
Fluffy Animal’s Fecal Orifice.
Nice one, but Cloudflare do it too.
The Arstechnica article in the OP is about 2 months newer than Cloudflare’s tool
This might explain why newer AI models are going nuts. Good jorb 👍
what models are going nuts?
Claude version 4, the openAi mini models, not sure what else
Not sure if OP can provide sources, but it makes sense kinda? Like AI has been trained on just about every human creation to get it this far, what happens when the only new training data is AI slop?
AI being trained by AI is how you train most models. Man, people here are ridiculously ignorant…
They specifically said “slop”. Maybe you breezed straight past that word in your fury.
Fury? I mean the only slop here are lemmings.
Nice try.
It absolutely doesn’t. The only model that has “gone nuts” is Grok, and that’s because of malicious code pushed specifically for the purpose of spreading propaganda.
Why are the photos all ugly biological things
They were generated using shitty AI models.
The reason you’re seeing biological photos in AI articles lately is tied to a recent but underreported breakthrough in processor technology: bio-silicon hybrids. They’re early-stage biological processors that integrate living neural tissue with traditional silicon circuits. Several research labs, including one backed by DARPA and the University of Kyoto, have successfully grown functional neuron clusters that can perform pattern recognition tasks with far less energy than conventional chips.
The biological cells react more collectively and with a higher success rate than the current systems. Think of it kind of how a computer itself is fast but parts can wear out (water cooled tubes or fan), whereas the biological cell systems will collectively react and if a few cells die, they may just create more. It’s really a crazy complex and efficient breakthrough.
The images of brains, neurons, or other organic forms aren’t just symbolic anymore—they’re literal. These bio-processors are being tested for edge computing, adaptive learning, and even ethical decision modeling.
That’s… actually quite terrifying.
The sci-fi concern over whether computers could ever be truly “alive” becomes a lot more tangible when literal living biological systems are implemented.
Wait, what?! Like… biocomputers?
It’s just bullshit
For an AI model to scrape 😈
Ive read a paper going of biological computing. Its a very real field of research.
Of course it is, but the comment is LLM-derived drivel.
The actual reason is that the use of biological photos is a design choice meant to visually bridge connect artificial intelligence and human intelligence. These random biological photos help to convey the idea that AI is inspired by or interacts with human cognition, emotions, or biology. It’s also a marketing tactic: people are more likely to engage with content that includes familiar, human-centered visuals. Though it doesn’t always reflect the technical content, it does help to make abstract or complex topics more relatable to a larger/extended audience.
I see what you-gpt did there
Some of it, yeah. I typed up the middle, then ran a separate prompt, and added to it. If you can see the edits, the original was organic and then the edit was adding to it
I’m going to assume half of that comment is wrong
The ars technica article: AI haters build tarpits to trap and trick AI scrapers that ignore robots.txt
AI tarpit 1: Nepenthes
AI tarpit 2: Iocaine
thanks for the links. the more I read of this the more based it is
Thank you!!
Nice … I look forward to the next generation of AI counter counter measures that will make the internet an even more unbearable mess in order to funnel as much money and control to a small set of idiots that think they can become masters of the universe and own every single penny on the planet.
We’re racing towards the Blackwall from Cyberpunk 2077…
Already there. The blackwall is AI-powered and Markov chains are most definitely an AI technique.
All the while as we roast to death because all of this will take more resources than the entire energy output of a medium sized country.
we’re rolling out renewables at like 100x the rate of ai electricity use, so no need to worry there
Yeah, at this rate we’ll be just fine. (As long as this is still the Reagan administration.)
yep the biggest worry isn’t AI, it’s India
https://www.worldometers.info/co2-emissions/india-co2-emissions/
The west is lowering its co2 output while India is slurping up all the co2 we’re saving:
This doesn’t include China of course, the most egregious of the co2 emitters
AI is not even a tiny blip on that radar, especially as AI is in data centres and devices which runs on electricity so the more your country goes to renewables the less co2 impacting it is over time
Now break that shit down per capita, and also try and account for the fact that China is a huge manufacturing hub for the entire world’s consumption, you jackass.
Could you add the US to the graphs, as EU and West are hardly synonymous - even as it descends into Trumpgardia.
China has that massive rate because it manufactures for the US, the US itself is a huge polluter for military and luxury NOT manufacturing
Still the second largest CO2 emitter, so it’d make sense to put it on for the comparison.
I’ve been think about this for a while. Consider how quick LLM’s are.
If the amount of energy spent powering your device (without an LLM), is more than using an LLM, then it’s probably saving energy.
In all honesty, I’ve probably saved over 50 hours or more since I starred using it about 2 months ago.
Coding has become incredibly efficient, and I’m not suffering through search-engine hell any more.
Edit:
Lemmy users when someone uses AI: noooo, you can’t generate helpful answers to your questions which cost a tenth of a cent worth of electricity.
Also Lemmy users when they see someone consuming the electric power of an entire nuclear power plant just to play Doom The Dark Ages on their $20,000 PC: neat!
Are you using your PC less hours per day?
Yep, more time for doing home renovations.
Just writing code uses almost no energy. Your PC should be clocking down when you’re not doing anything. 1GHz is plenty for text editing.
Does ChatGPT (or whatever LLM you use) reduce the number of times you hit build? Because that’s where all the electricity goes.
What kind of code are you writing that your CPU goes to sleep? If you follow any good practices like TDD, atomic commits, etc, and your code base is larger than hello world, your PC will be running at its peak quite a lot.
Example: linting on every commit + TDD. You’ll be making loads of commits every day, linting a decent code base will definitely push your CPU to 100% for a few seconds. Running tests, even with caches, will push CPU to 100% for a few minutes. Plus compilation for running the app, some apps take hours to compile.
In general, text editing is a small part of the developer workflow. Only junior devs spend a lot of time typing stuff.
Anything that’s per-commit is part of the “build” in my opinion.
But if you’re running a language server and have stuff like format-on-save enabled, it’s going to use a lot more power as you’re coding.
But like you said, text editing is a small part of the workflow, and looking up docs and browsing code should barely require any CPU, a phone can do it with fractions of a Watt, and a PC should be underclocking when the CPU is underused.
Except that half the time I dont know what the fuck I’m doing. It’s normal for me to spend hours trying to figure out why a small config file isnt working.
That’s not just text editing, that’s browsing the internet, referring to YouTube videos, or wallowing in self-pity.
That was before I started using gpt.
It sounds like it does save you a lot of time then. I haven’t had the same experience, but I did all my learning to program before LLMs.
Personally I think the amount of power saved here is negligible, but it would actually be an interesting study to see just how much it is. It may or may not offset the power usage of the LLM, depending on how many questions you end up asking and such.
It doesn’t always get the answers right, and I have to re-feed its broken instructions back into itself to get the right scripts, but for someone with no official coding training, this saves me so much damn time.
Consider I’m juggling learning Linux starting from 4 years ago, along with python, rust, nixos, bash scripts, yaml scripts, etc.
It’s a LOT.
For what it’s worth, I dont just take the scripts and paste them in, I’m always trying to understand what the code does, so I can be less reliant as time goes on.
I will cite the scientific article later when I find it, but essentially you’re wrong.
water != energy, but i’m actually here for the science if you happen to find it.
It can in the sense that many forms of generating power are just some form of water or steam turbine, but that’s neither here nor there.
IMO, the graph is misleading anyway because the criticism of AI from that perspective was the data centers and companies using water for cooling and energy, not individuals using water on an individual prompt. I mean, Microsoft has entered a deal with a power company to restart one of the nuclear reactors on Three Mile Island in order to compensate for the expected cost in energy of their AI. Using their service is bad because it incentivizes their use of so much energy/resources.
It’s like how during COVID the world massively reduced the individual usage of cars for a year and emissions barely budged. Because a single one of the largest freight ships puts out more emissions than every personal car combined annually.
Asking ChatGPT a question doesn’t take 1 hour like most of these… this is a very misleading graph
This is actually misleading in the other direction: ChatGPT is a particularly intensive model. You can run a GPT-4o class model on a consumer mid to high end GPU which would then use something in the ballpark of gaming in terms of environmental impact.
You can also run a cluster of 3090s or 4090s to train the model, which is what people do actually, in which case it’s still in the same range as gaming. (And more productive than 8 hours of WoW grind while chugging a warmed up Nutella glass as a drink).
Models like Google’s Gemma (NOT Gemini these are two completely different things) are insanely power efficient.
I didn’t even say which direction it was misleading, it’s just not really a valid comparison to compare a single invocation of an LLM with an unrelated continuous task.
You’re comparing Volume of Water with Flow Rate. Or if this was power, you’d be comparing Energy (Joules or kWh) with Power (Watts)
Maybe comparing asking ChatGPT a question to doing a Google search (before their AI results) would actually make sense. I’d also dispute those “downloading a file” and other bandwidth related numbers. Network transfers are insanely optimized at this point.
What about training an AI?
According to https://arxiv.org/abs/2405.21015
The absolute most monstrous, energy guzzling model tested needed 10 MW of power to train.
Most models need less than that, and non-frontier models can even be trained on gaming hardware with comparatively little energy consumption.
That paper by the way says there is a 2.4x increase YoY for model training compute, BUT that paper doesn’t mention DeepSeek, which rocked the western AI world with comparatively little training cost (2.7 M GPU Hours in total)
Some companies offset their model training environmental damage with renewable and whatever bullshit, so the actual daily usage cost is more important than the huge cost at the start (Drop by drop is an ocean formed - Persian proverb)
deleted by creator
It is already!
Really cool
Yeah, this is WAY bettee than the shitty thing people are using instead that wastes peoples batteries.
This is probably going to skyrocket hosting bills, right?
Not as much as letting them hit your database, load your images and video through a CDN would
The pages are plain html so it’s just a couple KB per request. Much cheaper than loading an actual site.
Not really. Part of the reason they are named tarpits is they load very slowly
I check if a user agent has gptbot, and if it does I 302 it to web.sp.am.
Deployment of Nepenthes and also Anubis (both described as “the nuclear option”) are not hate. It’s self-defense against pure selfish evil, projects are being sucked dry and some like ScummVM could only freakin’ survive thanks to these tools.
Those AI companies and data scrapers/broker companies shall perish, and whoever wrote this headline at arstechnica shall step on Lego each morning for the next 6 months.
Wait what? I am uninformed, can you elaborate on the ScummVM thing? Or link an article?
From the Fabulous Systems (ScummVM’s sysadmin) blog post linked by Natanox:
About three weeks ago, I started receiving monitoring notifications indicating an increased load on the MariaDB server.
This went on for a couple of days without seriously impacting our server or accessibility–it was a tad slower than usual.
And then the website went down.
Now, it was time to find out what was going on. Hoping that it was just one single IP trying to annoy us, I opened the access log of the day
there were many IPs–around 35.000, to be precise–from residential networks all over the world. At this scale, it makes no sense to even consider blocking individual IPs, subnets, or entire networks. Due to the open nature of the project, geo-blocking isn’t an option either.
The main problem is time. The URLs accessed in the attack are the most expensive ones the wiki offers since they heavily depend on the database and are highly dynamic, requiring some processing time in PHP. This is the worst-case scenario since it throws the server into a death spiral.
First, the database starts to lag or even refuse new connections. This, combined with the steadily increasing server load, leads to slower PHP execution.
At this point, the website dies. Restarting the stack immediately solves the problem for a couple of minutes at best until the server starves again.
Anubis is a program that checks incoming connections, processes them, and only forwards “good” connections to the web application. To do so, Anubis sits between the server or proxy responsible for accepting HTTP/HTTPS and the server that provides the application.
Many bots disguise themselves as standard browsers to circumvent filtering based on the user agent. So, if something claims to be a browser, it should behave like one, right? To verify this, Anubis presents a proof-of-work challenge that the browser needs to solve. If the challenge passes, it forwards the incoming request to the web application protected by Anubis; otherwise, the request is denied.
As a regular user, all you’ll notice is a loading screen when accessing the website. As an attacker with stupid bots, you’ll never get through. As an attacker with clever bots, you’ll end up exhausting your own resources. As an AI company trying to scrape the website, you’ll quickly notice that CPU time can be expensive if used on a large scale.
I didn’t get a single notification afterward. The server load has never been lower. The attack itself is still ongoing at the time of writing this article. To me, Anubis is not only a blocker for AI scrapers. Anubis is a DDoS protection.
Feels good to be on an instance with Anubis
one of the united Nations websites deployed Anubis
Do you have a link to a story of what happened to ScummVM? I love that project and I’d be really upset if it was lost!
Thank you!
Very cool, and the mascot is cute too as a nice bonus.
Thanks, interesting and brief read!
When I was a kid I thought computers would be useful.
They are. Its important to remember that in a capitalist society what is useful and efficient is not the same as profitable.
