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Poison Fountain: https://rnsaffn.com/poison2/ https://www.theregister.com/2026/01/11/industry_insiders_see...
Yea, this will work about as well as those image poisoners... they'll eat up more power, but won't have any effect at the end of the day.
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StackOverflow as built back in the days of Web 2.0 where the idea was that user generated content formed in the days of the (relatively) altruistic web. There isn't any clean way to do "contributor gets paid" without adding in an entire mess of "ok, where is the money coming from? Paywalls? Advertising? Subscriptions?" and then also get into the mess of international money transfers (how do you pay someone in Iran fr…
Stack Overflow is making money by selling its database to AI companies. It chose not to reimburse the people who built that database.
You can download the database for free.
Trying to say "give us your payment and tax information so that we can pay you $0.13 for your contributions" would be even more insulting than not paying anyone.
Doing renumeration for people in some countries could get legally challenging too.
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Stack Overflow is making money by selling its database to AI companies. It chose not to reimburse the people who built that database.
https://archive.org/search?query=creator%3A%22Stack+Exchange... You can download the database for free. Trying to say "give us your payment and tax information so that we can pay you $0.13 for your contributions" would be even more insulting than not paying anyone. Doing renumeration for people in some countries could get legally challenging too.
Isn't this a self solving problem? If LLMs won't be able to solve a certain problem, arbitrage opportunities open to solve it as a human (by writing a blog post for example), just like in the old days, people typically did this for fame. I think LLMs can be understood as a really good way to search existing solutions, including combining multiple solutions in the fly. Only if something cannot be "found", we go back t…
Companies will provide incentives for people to generate authentic content. Example X giving $1M reward for the top Articles. Because they can use it for training. In fact, this might be overall good thing, because finally original content will be highly on demand since those companies now use to train their models. But we are probably just in a transition phase. The other thing is that new sources of input will come…
Oh boy I can already see what kind of articles those would be.
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How do you evaluate if content is authentic?
Eventually it won’t matter. People will forget what it was like to have authentic content. They’d look at it like how we might view monks in the middle ages copying the bible a hundred times by hand. Even today people don’t even trust themselves to write an email. You see people on HN and reddit openly admitting they used ai to help make their post because they believe they cannot write. The march to illiteracy and i…
This is already true. Most people on the internet are stuck in tiktok loop anyway. Even chatgpt would struggle to get them. By the time LLMs get good enough, a lot of people who were willing to pay for them would have lost their jobs and they would not be paying for something that costed them their job, many will quit the internet fully. We are looking at value being driven out of internet at a grand scale.
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> He made a new industry. He didn't cannibalize an existing one. I don't see how you can claim the second part is true. Cars directly cannibalized other forms of self transportation.
? Cars don't "eat" horses. I wouldn't equate "making redundant" with "consuming"
It has nothing to do with literally eating.
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The proposed solution is also pretty confused: > For each response, the GenAI tool lists the sources from which it extracted that content, perhaps formatted as a list of links back to the content creators, sorted by relevance, similar to a search engine This literally isn’t possible given the architecture of transformer models and there’s no indication it will ever be.
Technically correct, but the workarounds AI search engines use for grounding results could be a close enough approximation. Might not be accurate, but could be better than nothing. Also Anthropic is doing interesting work in interpretability, who knows what could come out of that. And could be snake oil, but this startup claims to be able to attribute AI outputs to ingested content: https://prorata.ai/
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Inscryption is the GOAT, beautiful game. Played it when I had Covid.
> Inscryption is the GOAT, beautiful game. Played it when I had Covid. Oh Man, Y'know I once beat Inscryption's kaycee's mods challenge without doing any blood sacrifice the whole run after I got bored when I had defeated all kaycee's mods The gecko deck was amazing. I even played some mods of Inscryption. It was so lovely. The people who play inscryption & people who don't aren't the same lol. Played it during covid…
The aesthetic of the game is just so beautiful too. One of my all time favorites.
If the web gets flooded with LLM output and you train on it naively, you’re effectively training on your own prior. That pushes models toward the mean: less surprise, less specificity, more template-y phrasing. It’s like photocopying a photocopy: the sharp edges disappear.
The fix isn’t “never use synthetic data.” It’s to treat it like a controlled ingredient: tag provenance, keep a high-quality human/grounded core, filter aggressively, and anchor training to things that don’t self-contaminate (code that compiles/tests, math with verifiable proofs, retrieval with citations, real user feedback). Otherwise the easiest path is content volume, and volume is exactly what kills signal.