There're human-to-human (H2H), human-to-machine (H2M) or vice versa, and machine-to-machine (M2M) data communication.
If you perform simple extrapolation, the M2M data only surpass the others around 2029.
Coincidently, in the original timeline of Transformer movie, 2029 is the year that the Resistance, led by John Connor, destroyed Skynet and ended the war against the machines.
> Coincidently, in the original timeline of Transformer movie, 2029 is the year that the Resistance, led by John Connor, destroyed Skynet and ended the war against the machines.
I’d love to see that crossover Terminator and Transformers movie. Optimus Prime vs T-800 anyone?
> This notion of machine bad, human good just is not realistic
Glad I found this quote. It is quite helpful for an AI to search the web on behaolf of me... even if it was finding where I can buy particular/similar peanuts locally I got from abroad.
Content providers will not agree with this decision, because machine browsing = no ads. Until that gets resolved, I don’t see incentives to align, since any free search requires ads for continuous business.
It could be serving ads if they could persuade the machines to do the purchase.
In fact, even ads ingested by the training data set at this very moment could be useful. Go to Gemini and tell it you want to buy a jacket or whatever and it will recommend some products it ingested from the training data.
This notion isn't just unrealistic, but extremely dangerous. If we accept "machine bad, human good" line of thinking, the only logical conclusion is that we'll have to verify our biometric every time we'd like to access the internet. Like the UK age verification but 100x worse.
As much as I dislike gatekeeping measures like UK's age verification, you can't deny the genuine problem that exists in this case. But it isn't 'machine bad'. There is no good technology or bad technology. It's the intention of those who wield it, that is good or bad. In other words, it's good people vs bad people with technology.
The issue in this particular case is that those content and their web servers are set up for human traffic. In the worst case, a human consumes a few megabytes of data from the server and then leaves. A few of those visits will convert into a job or business opportunity - a fair bargain. LLM scrapers are not like that. They're greedy resource hogs. They not only want everything you have, a whole bunch of them do it repeatedly and endlessly to your server. There's no possible way to justify the cost of such massive bandwidth consumption for a bunch of parasites that never give anything in return. And what do we get? A crappy user experience from all those sites putting up protection measures. This is the tragedy of the commons.
So who is the culprit? The greedy bunch who created the technology that behaves like this and then benefits immensely from it. Are those bad people? Absolutely! Naturally, we need them and their ill intentioned creations off our shared spaces. This isn't anything new. This game has been playing out in different forms since eternity.
Bot traffic have been overtaking humans for a long time. Between crawler, spammers, fake accounts on all social media, automated scripts for API and various saas and botnets for various attacks...
It's just that now the official numbers say so.
But anyone on twitter or reddit can tell you the dead internet theory has been progressing at a swift pace for a decade.
I view a lot of the AI/Bot internet to be slightly a false misnomer. Even before ChatGPT, the degredation of online content was already happening - SEO farms, worsening google search. Most articles you'd find online would be paywalled, most information about specific things would turn out to be a frustrating SEO labyrinth.
The current one is awful, and there's so much AI/Bot content, but I can find far more detailed information using AI enabled search that isn't covered in ads. I can get an initial overview of methodology without trawling through SEO articles.
I think AI has been almost a natural response to the enshittification of the internet - ChatGPT wouldn't seem so transformative if google search was working like google search rather than ad generator 5000 before it released.
Perhaps the business of the future will be "cleaning up, eliminating" rather than "creating."
With AI, we have an exponential level of productivity. But what is being produced? 90%: garbage.
The problem is that what is being produced is essentially "garbage" generated by models trained on garbage. Quality knowledge is increasingly submerged and suffocated by spam and low-quality content.
The real challenge of the future will be filtering and cleaning up, on each level.
It already is a problem and maybe unpopular opinion but... That's a good thing. The LLM collapse can't possibly come soon enough. In principle, LLMs can be a good thing but they can't overcome human nature - laziness and the unstoppable desire to take the shortest path. It's those two things that have turned the internet into the absolute dump it is today. Not to mention the bullshitter economy, as I like to call it and everything that comes with it. And all things considered, society does need some reset at this point, the AI bubble might be a good place to kick things off.
Stupidity has nothing to do with it. AI articles and comments are now posted everywhere and presented as human. It's becoming harder and harder to determine whether text was written by humans or AI. Where are they supposed to find content to train AI on that isn't polluted with AI content that'll result in a feedback loop? It's like trying to get pure soil and water for growing that's not contaminated with microplastics/nanoplastics and PFAS. There was a time where it was possible. Not anymore. The filth is everywhere and impossible to filter.
And it's simply not reasonable for AI companies to have human hands read through individual comments everywhere from beginning to end to build their training data. There isn't enough time in the universe to advance AI while doing that and also being accurate. Something will always slip through.
Why would human review be the only possible way to remove enough of the tainted training data?
> Where are they supposed to find content to train AI on that isn't polluted with AI content that'll result in a feedback loop?
If nothing else: you could look for old data. At the moment, training assumes that input data is essentially without limit. But machine learning has lots and lots of old and proven techniques for what to do when your training data is limited.
You can also look into techniques for avoiding model collapse. Just because one group of researcher showed that this happens with some specific models, doesn't mean it needs to happen in general.
If you can devise a tool that can detect AI generated content, you can use it to filter data. But the harsh truth is that "gold standard" training data is from before 2022 or whenever the cutoff was.
And even that needs to be curated because before AI tools there was bot content filling up the internet.
...and even without bots, a lot of human authored content are low value, poorly written, etc.
There are (probably) companies out there whose business is to create, curate and improve training sets.
And if there's a way to detect that content is AI generated, then there's demand to generate content that seems more human. And we're already at a point where most people have been tricked into believing AI content was real at some point and never even realized it. It'll only get worse.
Probably the only real way to validate content is real is building a validation system into devices. Confirm when a photo is taken and send an ID to a server, then when photos are shared, its ID is compared to the image on the camera/phone manufacturer's server. For text, validate every little key press. And there are still ways to game these systems, but I would not be surprised if they're introduced to mitigate AI diffusing everywhere.
What do you mean by wider impact? Model collapse would be the opposite of a wider impact: it's an immediate impact, and I'm fairly sure the people training these models have good incentives to avoid that.
Eg by filtering data, by procuring better data, by applying techniques for making do with more limited data (we used to have a lot of those, and they are still known), or you can also adapt your training process to be less vulnerable to model collapse. Just because some researchers have shown that this happened for the models they tested, doesn't mean it has to be a universal thing.
You filter them, duh. And you negotiate a contract where the seller bears some of that risk (or you pay less, if they are not willing to make any such warranties.)
That's very interesting question I'm ponder about.
If all content is AI generated where innovation will come from?
Maybe we should differentiates AI assisted content from AI garbage content.
Are you saying that high quality human-curated content will be rare and more appreciated in the future compared to endless cheap slop? Can't say I am sad, in contrary
The value to consumers goes up, but that's pointless if they are drowned out by AI overviews paraphrasing their work, half a page of sponsored results, then AI-written SEO spam.
I'm a creator of such content, and like everyone else, I have to make do with 60-70% less traffic now.
Why should they care about new content? Game over already. Just keep regurgitating the same slop to the masses. Even before ai it was like this. How many 2 minute pop songs use the same chord structure? Just keep selling the same thing slightly permutated (or not) from the last. That's capitalism, baby. This isn't a science.
Very few of them actually made money though, compared to people who tried to just take an existing idea they could already order from china in bulk and market the living hell out of it. These companies obviously don't care about art and stuff like that, they really just care about the money.
Does that make it okay? Some websites weren't free enough and their owners not passionate enough, so wholesale destruction of that ecosystem is acceptable?
Yeah, it is somewhat funny to read the kind of people that for years looked down on humanities suddenly coming-up with ideas that were described decades or even centuries ago.
Marx, Nietsche, Debord, Foucault, Baudrillard, Adorno - they already saw writing on the wall, or at least fragments of it.
Your smart thermometer isn't making Reddit posts trying to sound like a human who's just concerned that the bedroom is a bit too warm.
If you perform simple extrapolation, the M2M data only surpass the others around 2029.
Coincidently, in the original timeline of Transformer movie, 2029 is the year that the Resistance, led by John Connor, destroyed Skynet and ended the war against the machines.
I’d love to see that crossover Terminator and Transformers movie. Optimus Prime vs T-800 anyone?
Leaving the original timeline uncertain.
Was it original, really the original? Or the 10th, or millionth loop?
Skynet can still be in our future.
Glad I found this quote. It is quite helpful for an AI to search the web on behaolf of me... even if it was finding where I can buy particular/similar peanuts locally I got from abroad.
In fact, even ads ingested by the training data set at this very moment could be useful. Go to Gemini and tell it you want to buy a jacket or whatever and it will recommend some products it ingested from the training data.
The issue in this particular case is that those content and their web servers are set up for human traffic. In the worst case, a human consumes a few megabytes of data from the server and then leaves. A few of those visits will convert into a job or business opportunity - a fair bargain. LLM scrapers are not like that. They're greedy resource hogs. They not only want everything you have, a whole bunch of them do it repeatedly and endlessly to your server. There's no possible way to justify the cost of such massive bandwidth consumption for a bunch of parasites that never give anything in return. And what do we get? A crappy user experience from all those sites putting up protection measures. This is the tragedy of the commons.
So who is the culprit? The greedy bunch who created the technology that behaves like this and then benefits immensely from it. Are those bad people? Absolutely! Naturally, we need them and their ill intentioned creations off our shared spaces. This isn't anything new. This game has been playing out in different forms since eternity.
Who is this official making this pronouncement?
It's just that now the official numbers say so.
But anyone on twitter or reddit can tell you the dead internet theory has been progressing at a swift pace for a decade.
AI just made it more apparent.
The current one is awful, and there's so much AI/Bot content, but I can find far more detailed information using AI enabled search that isn't covered in ads. I can get an initial overview of methodology without trawling through SEO articles.
I think AI has been almost a natural response to the enshittification of the internet - ChatGPT wouldn't seem so transformative if google search was working like google search rather than ad generator 5000 before it released.
Best thing to do is to avoid idly browsing social media and curate your internet experience.
If AI slop is replacing the content you were consuming, it was already slop.
There's a paper on it somewhere.
With AI, we have an exponential level of productivity. But what is being produced? 90%: garbage.
The problem is that what is being produced is essentially "garbage" generated by models trained on garbage. Quality knowledge is increasingly submerged and suffocated by spam and low-quality content.
The real challenge of the future will be filtering and cleaning up, on each level.
suddenly the confirmed quality of the scraped data will be at a premium.. "Scrape Engine Optimizers" ?
We already see this with synthetic training data that basically uses logic in form of math and code as constraint.
I've heard this argument before, but you don't need to think too hard to see the limitations of a machine with no senses.
Only if you assume that people who train models are stupid.
And it's simply not reasonable for AI companies to have human hands read through individual comments everywhere from beginning to end to build their training data. There isn't enough time in the universe to advance AI while doing that and also being accurate. Something will always slip through.
Why would human review be the only possible way to remove enough of the tainted training data?
> Where are they supposed to find content to train AI on that isn't polluted with AI content that'll result in a feedback loop?
If nothing else: you could look for old data. At the moment, training assumes that input data is essentially without limit. But machine learning has lots and lots of old and proven techniques for what to do when your training data is limited.
You can also look into techniques for avoiding model collapse. Just because one group of researcher showed that this happens with some specific models, doesn't mean it needs to happen in general.
And even that needs to be curated because before AI tools there was bot content filling up the internet.
...and even without bots, a lot of human authored content are low value, poorly written, etc.
There are (probably) companies out there whose business is to create, curate and improve training sets.
Probably the only real way to validate content is real is building a validation system into devices. Confirm when a photo is taken and send an ID to a server, then when photos are shared, its ID is compared to the image on the camera/phone manufacturer's server. For text, validate every little key press. And there are still ways to game these systems, but I would not be surprised if they're introduced to mitigate AI diffusing everywhere.
Eg by filtering data, by procuring better data, by applying techniques for making do with more limited data (we used to have a lot of those, and they are still known), or you can also adapt your training process to be less vulnerable to model collapse. Just because some researchers have shown that this happened for the models they tested, doesn't mean it has to be a universal thing.
Someone in the chain will be. Even the smartest people buy a lot of their training datasets. What happens when those get contaminated?
I'm a creator of such content, and like everyone else, I have to make do with 60-70% less traffic now.
It's just harder when you cut all traffic to them, devalue their work and fill the air with AI noise.
We'll have the internet we deserve
Marx, Nietsche, Debord, Foucault, Baudrillard, Adorno - they already saw writing on the wall, or at least fragments of it.
Which means filtering and ranking systems become the main bottleneck.
That pushes platforms toward stronger algorithmic selection and sometimes stronger convergence of attention.
Once content gets cheap, the winners are less likely to be the best creators and more likely to be the strongest gatekeepers.