Comment by krater23
12 hours ago
And that someone who sayd years over years that the web will die now says again that the web will die means that the other people which say the web will die are wrong?
Most content is now on <10 big platforms. nearby no one has a website just to tell other people some stuff or what he has done for fun. only reason to have a website today is profit. active websites write in the first part of a article only bullshit to get found by google. Sites that are really like in 1999, just fun sites would never been found via google anymore. And now AI crawls all this and steals traffic from this sites without giving credits until no one beside of bot's will reads them anymore.
The web is not dying, the web is already dead! A commercialized part of the money making machine, nothing more anymore.
Next step: AI is dying because there are no new data to learn because it makes no sense anymore to create websites. Welcome to the stone age.
> The web is not dying, the web is already dead!
Says he on a web site.
And the fact this remains a Web site is truly remarkable. The reason it is popular with a niche group of technically minded-users is because Web sites are so hard to come by these days that you need a special place to collect them.
> Web sites are so hard to come by these days that you need a special place to collect them.
When the web was nascent sites like Lycos, AltaVista, Yahoo!, and others created indexes you could browse by category, right?
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> Web sites are so hard to come by these days
and yet day after day, HN is flooded with links to ... wait for it ... web sites (more specifically, content on web sites thought to be potentially interesting to the HN crowdf).
what are you talking about?
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Its weird how people keep saying the rise of AI generated content will "kill AI" as though the companies training models don't have complete archives of all the data they already scraped from the Internet.
It doesn't take all the text of the public Internet for someone to learn to talk, and all these companies are much more in the data curation business for the purposes of teaching models.
Scraping is to make them up to date on current events (and has obvious alternative sources), or the actions of the start up space which don't already have such datasets.
I can't wait to see how the coding performance will start to drop on with newer tools and versions, as people no longer discuss them in the same detail and quantity as they used to. People using LLMs will be stuck in the pre-2023 tools, using new stuff is an uphill battle already (you have to give it the correct docs manually)